Software Testing Metrics & KPIs

Nowadays, quality is the driving force behind the popularity as well as the success of a software product, which has drastically increased the requirement to take effective measures for quality assurance. Therefore, to ensure this, software testers are using a defined way of measuring their goals and efficiency, which has been made possible with the use of various software testing metrics and key performance indicators. The metrics and KPIs serve a crucial role and help the team determine the metrics that calculate the effectiveness of the testing teams and help them gauge the quality, efficiency, progress, and the health of the software testing.

Therefore, to help you measure your testing efforts and the testing process, here is a list of some critical software testing metrics as well as key performance indicators.

The Fundamental Software Testing Metrics:

Software testing metrics, which are also known as software test measurement, indicates the extent, amount, dimension, capacity, as well as the rise of various attributes of a software process and tries to improve its effectiveness and efficiency imminently. Software testing metrics are the best way of measuring and monitoring the various testing activities performed by the team of testers during the software testing life cycle. Moreover, it helps convey the result of a prediction related to a combination of data. Hence, the various software testing metrics used by software engineers around the world are:

  1. Derivative Metrics: Derivative metrics help identify the various areas that have issues in the software testing process and allows the team to take effective steps that increase the accuracy of testing.
  2. Defect Density: Another important software testing metrics, defect density helps the team in determining the total number of defects found in a software during a specific period of time- operation or development. The results are then divided by the size of that particular module, which allows the team to decide whether the software is ready for the release or whether it requires more testing. The defect density of a software is counted per thousand lines of the code, which is also known as KLOC. The formula used for this is:
  3. Defect Density = Defect Count/Size of the Release/Module

  4. Defect Leakage: An important metric that needs to be measured by the team of testers is defect leakage. Defect leakage is used by software testers to review the efficiency of the testing process before the product’s user acceptance testing (UAT). If any defects are left undetected by the team and are found by the user, it is known as defect leakage or bug leakage.
  5. Defect Leakage = (Total Number of Defects Found in UAT/ Total Number of Defects Found Before UAT) x 100

  6. Defect Removal Efficiency: Defect removal efficiency (DRE) provides a measure of the development team’s ability to remove various defects from the software, prior to its release or implementation. Calculated during and across test phases, DRE is measured per test type and indicates the efficiency of the numerous defect removal methods adopted by the test team. Also, it is an indirect measurement of the quality as well as the performance of the software. Therefore, the formula for calculating Defect Removal Efficiency is:
  7. DRE = Number of defects resolved by the development team/ (Total number of defects at the moment of measurement)

  8. Defect Category: This is a crucial type of metric evaluated during the process of the software development life cycle (SDLC). Defect category metric offers an insight into the different quality attributes of the software, such as its usability, performance, functionality, stability, reliability, and more. In short, the defect category is an attribute of the defects in relation to the quality attributes of the software product and is measured with the assistance of the following formula:
  9. Defect Category = Defects belonging to a particular category/ Total number of defects.

  10. Defect Severity Index: It is the degree of impact a defect has on the development of an operation or a component of a software application being tested. Defect severity index (DSI) offers an insight into the quality of the product under test and helps gauge the quality of the test team’s efforts. Additionally, with the assistance of this metric, the team can evaluate the degree of negative impact on the quality as well as the performance of the software. Following formula is used to measure the defect severity index.
  11. Defect Severity Index (DSI) = Sum of (Defect * Severity Level) / Total number of defects

  12. Review Efficiency: The review efficiency is a metric used to reduce the pre-delivery defects in the software. Review defects can be found in documents as well as in documents. By implementing this metric, one reduces the cost as well as efforts utilized in the process of rectifying or resolving errors. Moreover, it helps to decrease the probability of defect leakage in subsequent stages of testing and validates the test case effectiveness. The formula for calculating review efficiency is:
  13. Review Efficiency (RE) = Total number of review defects / (Total number of review defects + Total number of testing defects) x 100

  14. Test Case Effectiveness: The objective of this metric is to know the efficiency of test cases that are executed by the team of testers during every testing phase. It helps in determining the quality of the test cases.
  15. Test Case Effectiveness = (Number of defects detected / Number of test cases run) x 100

  16. Test Case Productivity: This metric is used to measure and calculate the number of test cases prepared by the team of testers and the efforts invested by them in the process. It is used to determine the test case design productivity and is used as an input for future measurement and estimation. This is usually measured with the assistance of the following formula:
  17. Test Case Productivity = (Number of Test Cases / Efforts Spent for Test Case Preparation)

  18. Test Coverage: Test coverage is another important metric that defines the extent to which the software product’s complete functionality is covered. It indicates the completion of testing activities and can be used as criteria for concluding testing. It can be measured by implementing the following formula:
  19. Test Coverage = Number of detected faults/number of predicted defects.

    Another important formula that is used while calculating this metric is:
    Requirement Coverage = (Number of requirements covered / Total number of requirements) x 100

  20. Test Design Coverage: Similar to test coverage, test design coverage measures the percentage of test cases coverage against the number of requirements. This metric helps evaluate the functional coverage of test case designed and improves the test coverage. This is mainly calculated by the team during the stage of test design and is measured in percentage. The formula used for test design coverage is:
  21. Test Design Coverage = (Total number of requirements mapped to test cases / Total number of requirements) x 100

  22. Test Execution Coverage: It helps us get an idea about the total number of test cases executed as well as the number of test cases left pending. This metric determines the coverage of testing and is measured during test execution, with the assistance of the following formula:
  23. Test Execution Coverage = (Total number of executed test cases or scripts / Total number of test cases or scripts planned to be executed) x 100

  24. Test Tracking & Efficiency: Test efficiency is an important component that needs to be evaluated thoroughly. It is a quality attribute of the testing team that is measured to ensure all testing activities are carried out in an efficient manner. The various metrics that assist in test tracking and efficiency are as follows:
    • Passed Test Cases Coverage: It measures the percentage of passed test cases.
    • (Number of passed tests / Total number of tests executed) x 100

    • Failed Test Case Coverage: It measures the percentage of all the failed test cases.
    • (Number of failed tests / Total number of test cases failed) x 100

    • Test Cases Blocked: Determines the percentage of test cases blocked, during the software testing process.
    • (Number of blocked tests / Total number of tests executed) x 100

    • Fixed Defects Percentage: With the assistance of this metric, the team is able to identify the percentage of defects fixed.
    • (Defect fixed / Total number of defects reported) x 100

    • Accepted Defects Percentage: The focus here is to define the total number of defects accepted by the development team. These are also measured in percentage.
    • (Defects accepted as valid / Total defect reported) x 100

    • Defects Rejected Percentage: Another important metric considered under test track and efficiency is the percentage of defects rejected by the development team.
    • (Number of defects rejected by the development team / total defects reported) x 100

    • Defects Deferred Percentage: It determines the percentage of defects deferred by the team for future releases.
    • (Defects deferred for future releases / Total defects reported) x 100

    • Critical Defects Percentage: Measures the percentage of critical defects in the software.
    • (Critical defects / Total defects reported) x 100

    • Average Time Taken to Rectify Defects: With the assistance of this formula, the team members are able to determine the average time taken by the development and testing team to rectify the defects.
    • (Total time taken for bug fixes / Number of bugs)

  25. Test Effort Percentage: An important testing metric, test efforts percentage offer an evaluation of what was estimated before the commencement of the testing process vs the actual efforts invested by the team of testers. It helps in understanding any variances in the testing and is extremely helpful in estimating similar projects in the future. Similar to test efficiency, test efforts are also evaluated with the assistance of various metrics:
    • Number of Test Run Per Time Period: Here, the team measures the number of tests executed in a particular time frame.
      (Number of test run / Total time)

    • Test Design Efficiency: The objective of this metric is to evaluate the design efficiency of the executed test.
      (Number of test run / Total Time)

    • Bug Find Rate: One of the most important metrics used during the test effort percentage is bug find rate. It measures the number of defects/bugs found by the team during the process of testing.
      (Total number of defects / Total number of test hours)

      Number of Bugs Per Test: As suggested by the name, the focus here is to measure the number of defects found during every testing stage.
      (Total number of defects / Total number of tests)

    • Average Time to Test a Bug Fix: After evaluating the above metrics, the team finally identifies the time taken to test a bug fix.
      (Total time between defect fix & retest for all defects / Total number of defects)
  26. Test Effectiveness: A contrast to test efficiency, test effectiveness measures and evaluates the bugs and defect ability as well as the quality of a test set. It finds defects and isolates them from the software product and its deliverables. Moreover, the test effectiveness metrics offer the percentage of the difference between the total number of defects found by the software testing and the number of defects found in the software. This is mainly calculated with the assistance of the following formula:
  27. Test Effectiveness (TEF) = (Total number of defects injected + Total number of defects found / Total number of defect escaped) x 100

  28. Test Economic Metrics: While testing the software product, various components contribute to the cost of testing, like people involved, resources, tools, and infrastructure. Hence, it is vital for the team to evaluate the estimated amount of testing, with the actual expenditure of money during the process of testing. This is achieved by evaluating the following aspects:
    • Total allocated the cost of testing.
    • The actual cost of testing.
    • Variance from the estimated budget.
    • Variance from the schedule.
    • Cost per bug fix.
    • The cost of not testing.
  29. Test Team Metrics: Finally, the test team metrics are defined by the team. This metric is used to understand if the work allocated to various test team members is distributed uniformly and to verify if any team member requires more information or clarification about the test process or the project. This metric is immensely helpful as it promotes knowledge transfer among team members and allows them to share necessary details regarding the project, without pointing or blaming an individual for certain irregularities and defects. Represented in the form of graphs and charts, this is fulfilled with the assistance of the following aspects:
    • Returned defects are distributed team member vise, along with other important details, like defects reported, accepted, and rejected.
    • The open defects are distributed to retest per test team member.
    • Test case allocated to each test team member.
    • The number of test cases executed by each test team member.

Software Testing Key Performance Indicators(KPIs):

A type of performance measurement, Key Performance Indicators or KPIs, are used by organizations as well as testers to get data that can be measured. KPIs are the detailed specifications that are measured and analyzed by the software testing team to ensure the compliance of the process with the objectives of the business. Moreover, they help the team take any necessary steps, in case the performance of the product does not meet the defined objectives.

In short, Key performance indicators are the important metrics that are calculated by the software testing teams to ensure the project is moving in the right direction and is achieving the target effectively, which was defined during the planning, strategic, and/or budget sessions. The various important KPIs for software testers are:

  1. Active Defects: A simple yet important KPI, active defects help identify the status of a defect- new, open, or fixed -and allows the team to take the necessary steps to rectify it. These are measured based on the threshold set by the team and are tagged for immediate action if they are above the threshold.
  2. Automated Tests: While monitoring and analyzing the key performance indicators, it is important for the test manager to identify the automated tests. Through tricky, it allows the team to track the number of automated tests, which can help catch/detect the critical and high priority defects introduced in the software delivery stream.
  3. Covered Requirements: With the assistance of this key performance indicator the team can track the percentage of requirements covered by at least one test. The test manager monitors the these this KPI every day to ensure 100% test and requirements coverage.
  4. Authored Tests: Another important key performance indicator, authored tests are analyzed by the test manager, as it helps them analyze the test design activity of their business analysts and testing engineers.
  5. Passed Tests: The percentage of passed tests is evaluated/measured by the team by monitoring the execution of every last configuration within a test. This helps the team in understanding how effective the test configurations are in detecting and trapping the defects during the process of testing.
  6. Test Instances Executed: This key performance indicator is related to the velocity of the test execution plan and is used by the team to highlight the percentage of the total instances available in a test set. However, this KPI does not offer an insight into the quality of the build.
  7. Test Executed: Once the test instances are determined the team moves ahead and monitors the different types of test execution, such as manual, automates, etc. Just like test instances executed, this is also a velocity KPI.
  8. Defects Fixed Per Day: By evaluating this KPI the test manager is able to keep a track of the number of defects fixed on a daily basis as well as the efforts invested by the team to rectify these defects and issues. Moreover, it allows them to see the progress of the project as well as the testing activities.
  9. Direct Coverage: This KPI helps to perform a manual or automated coverage of a feature or component and ensures that all features and their functions are completely and thoroughly tested. If a component is not tested during a particular sprint, it will be considered incomplete and will not be moved until it is tested.
  10. Percentage of Critical & Escaped Defects: The percentage of critical and escaped defects is an important KPI that needs the attention of software testers. It ensures that the team and their testing efforts are focused on rectifying the critical issues and defects in the product, which in turn helps them ensure the quality of the entire testing process as well as the product.
  11. Time to Test: The focus of this key performance indicator is to help the software testing team measure the time that a feature takes to move from the stage of “testing” to “done”. It offers assistance in calculating the effectiveness as well as the efficiency of the testers and understanding the complexity of the feature under test.
  12. Defect Resolution Time: Defect resolution time is used to measure the time it takes for the team to find the bugs in the software and to verify and validate the fix. Apart from this, it also keeps a track of the resolution time, while measuring and qualifying the tester’s responsibility and ownership for their bugs. In short, from tracking the bugs and making sure the bugs are fixed the way they were supposed to, to closing out the issue in a reasonable time, this KPI ensures it all.
  13. Successful Sprint Count Ratio: Though a software testing metric, this is also used by software testers as a KPI, once all the successful sprint statistics are collected. It helps them calculate the percentage of successful sprints, with the assistance of the following formula:
  14. Successful Sprint Count Ratio: (Successful Sprint / Total Number of Sprints) x 100

  15. Quality Ratio: Based on the passed or failed rates of all the tests executed by the software testers, the quality ratio, is used as both a software testing metrics as well as a KPI. The formula used for this is:
  16. Quality Ratio: (Successful Tests Cases / Total Number of Test Cases) x 100

  17. Test Case Quality: A software testing metric and a KPI, test case quality, helps evaluate and score the written test cases according to the defined criteria. It ensures that all the test cases are examined either by producing quality test case scenarios or with the assistance of sampling. Moreover, to ensure the quality of the test cases, certain factors should be considered by the team, such as:
    • They should be written for finding faults and defects.
    • Test & requirements coverage should be fully established.
    • The areas affected by the defects should be identified and mentioned clearly.
    • Test data should be provided accurately and should cover all the possible situations.
    • It should also cover success and failure scenarios.
    • Expected results should be written in a correct and clear format.
  18. Defect Resolution Success Ratio: By calculating this KPI, the team of software testers can find out the number of defects resolved and reopened. If none of the defects are reopened then 100% success is achieved in terms of resolution. Defect resolution success ratio is evaluated with the assistance of the following formula:
  19. Defect Resolution Success Ratio = [ (Total Number of Resolved Defects) – (Total Number of Reopened Defects) / (Total Number of Resolved Defects) ] x 100

  20. Process Adherence & Improvement: This KPI can be used for the software testing team to reward them and their efforts if they come up with any ideas or solutions that simplify the process of testing and make it agile as well as more accurate.

Conclusion:

Software testing metrics and key performance indicators are improving the process of software testing exceptionally. From ensuring the accuracy of the numerous tests performed by the testers to validate the quality of the product, these play a crucial role in the software development lifecycle. Hence, by implementing and executing these software testing metrics and performance indicators you can increase the effectiveness as well as the accuracy of your testing efforts and get exceptional quality.

Why we Expanded our Technology Portfolio?

The ThinkSys growth story is known to a few already. For the longest time, we were known as a QA-focused organization. Over time we added a strong Test Automation thread to that story. Adding new skills and technology areas, the company grew organically and now our several highly-talented engineers provide impeccable service in the field of custom software development, web and mobile app development, Cloud, and a multitude of other software services. As technology continues to become a driver of business transformation, we at ThinkSys strive to meet the end-to-end software development and testing needs of our current client as well as future clients. This meant an expansion of the areas we work in. Here’s what drove out thinking.

The Inclusion of Big Data, IoT, and AI:

For many years, big data, IoT, and AI have been impacting organizations across several industries and applications. Although they have all contributed to businesses in unimaginable ways, it is the convergence of these three powerful technologies that can drive next-generation innovation and transformation: from smart manufacturing to precision surgery, energy automation to smart RFID tags, building automation to smart farming, predictive maintenance systems to chatbots, climate control to intelligent shipment tracking – the things that big data, IoT and AI are helping achieve is incredible! Our customers are also impacted by these technology movements. We started seeing more opportunity to marry these technologies into the solutions we were already providing. It seemed clear, to continue to serve the market we just had to add these three disruptive technologies to our development and testing portfolio to enable our customers to leverage the stunning benefits and experience growth like never before.

  1. Big Data:
    As technology makes inroads into the business world, the problem of information overload has become rampant. Organizations grappling with massive amounts of data are embracing new strategies such as big data to analyze data and uncover critical insights. According to a report, revenue from big data is expected to reach $210 billion by 2020. We believe that big data has the immense capability in discovering hidden patterns, unknown correlations, customer preferences, and other vital information, enabling organizations to make informed decisions. Our big data services include predictive analytics, data mining, text mining, data optimization, data management, & forecasting that can enable organizations to uncover hidden business opportunities and accelerate business growth. By making smart, data-driven decisions, organizations can identify risks ahead of time and improve operations and risk management.
  2. bid data services

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  3. IoT:
    The explosion of IoT has completely transformed the technology world and is bringing the physical and digital aspects of life closer than ever. The total economic value-add for IoT is expected to reach $1.9 trillion by 2020. IoT is enabling businesses to boost operational efficiency and transform their business models. We at ThinkSys are quite certain IoT has the capability to create a world of opportunities; with a more direct integration of the physical world with the digital, IoT will improve business efficiency and accuracy through more intelligent data capture from the edges and more seamless automation. As IoT makes its way into every sector, we aim to cater to the distinct demands of every commercial enterprise and industry. Our end-to-end customized IoT consulting services and implementation solutions can enable organizations to optimize operations, reduce costs, and achieve revenue goals.
  4. IoT consulting services

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  5. AI:
    A fundamental shift in business operations is being brought about by AI; according to reports, global spending on AI is expected to reach a whopping $57.6 billion by 2021. Although AI finds great application across industries such as banking, finance, e-commerce, healthcare, and telecommunication, it is reinventing the way goods are manufactured and delivered. The recent proliferation of AI has brought with it a multitude of associated technologies that are enabling organizations to automate processes, improve efficiency and transform businesses. Our foray into AI marks the beginning of our digital journey into advanced AI technologies such as cognitive computing, machine learning, natural language processing, among others. We are already working on solutions that will bring in the required intelligence to improve the speed of processes, reduce errors, and increase accuracy, and precision – thus enabling our clients to be agile, smart and innovative.
  6. AI Services

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    Drive Business Value:

    At ThinkSys, we believe technology has the power to fuel business transformation. Leveraging our capabilities and knowledge of the latest tools and applications, we offer time-tested and reliable technology services across a comprehensive portfolio of advanced technologies. Our team of experienced and knowledgeable experts make use of the latest strategies and deliver solutions to solve complex business problems. By expanding our technology portfolio and including big data, IoT, and AI into our service offering, we aim to assist businesses in understanding the information contained within large data sets, to automate critical business processes, and enable them to drive substantial business value in all that they do.

Google has a New Cloud Platform – What Does it Mean for Application Development?

Google’s foray into the cloud computing space is the talk of the town. By offering a suite of public cloud computing services such as compute, storage, networking, big data, IoT, machine learning, and application development, Google has now joined the likes of Amazon and Microsoft and hopes to take over the cloud computing market. Since the platform is a public cloud offering, services can be accessed by application developers, cloud administrators, and other IT professionals over the internet or by using a dedicated network connection.

google cloud platform for application development

What Google New Cloud Platform Means For Application Development?

According to Gartner, by 2021, the PaaS market is expected to attain a total market size of $27.3 billion. In addition to the core cloud computing products such as Google Compute Engine, Google Cloud Storage, and Google Container Engine, what’s particularly exciting for the application development world is the Google App Engine – a platform-as-a-service (PaaS) offering that enables developers to build scalable web applications as well as mobile and IoT backends. It offers access to Google’s scalable hosting, software development kit (SDK), and a host of built-in services and APIs. Here’s a list of features application developers can leverage:

  • Access to familiar languages and tools: Since developers are most comfortable developing apps using languages that they are familiar with, the Google Cloud Platform allows them to choose the language of their choice – from Java, PHP, Node.js, Python, C#,.Net, Ruby or any other language you prefer. Access to a collection of tools and libraries that include Google Cloud SDK, Cloud Shell, Cloud Tools for Android Studio, IntelliJ, PowerShell, Visual Studio etc. make application development all the more efficient. And with custom runtimes, you can bring any library and framework to the App Engine by supplying a Docker container.
  • Hassle-free Coding: Despite being proficient in coding, developers often end up managing several other aspects of the application development life-cycle beyond the purview of their role. The Google Cloud Platform offers a range of infrastructure capabilities such as patch and server management, as well as security features like firewall, Identity and Access Management, and SSL/ TLS certificates. With all these other facets of development taken care of, developers can enjoy hassle-free coding, without worrying about managing the underlying infrastructure.
  • Scalable Mobile Backends: Depending on the type of mobile application that is required to be built, the Google Cloud Platform automatically scales the hosting environment. With Cloud Tools for IntelliJ, one can easily deploy Java backends for cloud apps to the Google App Engine flexible environment. Integration with Firebase mobile platform provides an easy-to-use front-end with a scalable and reliable backend, and access to functionalities such as databases, analytics, crash reporting and more.
  • Quick Deployment: Quick deployment is a top priority for any developer; if one can’t deploy apps quickly, someone else will and might eat into your market share and customer base. Being a fully-managed platform, Google Cloud Platform allows developers to quickly build and deploy applications and scale as required, and not worry about managing servers or configurations. What’s more, Google’s Cloud Deployment Manager allows you to specify all the resources needed for the application and to perform repeatable deployments quickly and efficiently.
  • High Availability: Making applications available anytime, anywhere, and on any device has become a requisite. The Google App Engine allows developers to build highly scalable applications on a fully managed serverless platform. All they have to do is simply upload their code and allow Google to manage the app’s availability — without having to provision or maintain a single server. Since the engine scales applications automatically in response to the amount of traffic they receive, you can ensure high availability and only pay for the resources used.
  • Easy Testing: The impact of an app failure is extremely profound. Not only does it cost a lot but it also impacts customer trustworthiness. Do you know? In 2017, software failures resulted in losses of over $1.7 trillion. The Google Cloud Platform integrates with the Firebase Test Lab that provides cloud-based infrastructure for testing mobile apps. With Firebase Test Lab, app developers can initiate the testing of apps across a wide variety of devices and configurations and view test results directly on their console. And if there are problems in the app, they can debug the cloud backend using Stackdriver Debugger without affecting end-user experience.
  • Seamless Versioning: Users need updated information about the version of the app installed on their devices. This means that versioning is a critical component of the application upgrade and maintenance strategy. When developing apps in the App Engine, one can easily create development, test, staging, and production environments and host different versions of the app. Each version then runs within one or more instances, depending on how much traffic it has been configured to handle.
  • Health Monitoring: Providing users with high-quality app experiences requires app developers to carry out timely performance monitoring. As applications get more complex and distributed, Google Stackdriver offers powerful application diagnostics to debug and monitor the health and performance of these apps. By aggregating metrics, logs, and events, it offers deep insight into multiple issues. This helps speed up root-cause analysis and reduce mean time to resolution.

Streamline Application Development:

The Google Cloud Platform – with its application development and integration services – could change the face of application development. With access to popular languages and tools and an open and flexible framework that is fully managed, it enables app developers to improve productivity and become more agile. Developers can focus on simply writing code and run all applications in a serverless environment. Since the App Engine automatically scales depending on application traffic and consumes resources only when the code is running, developers do not have to worry about over or under-provisioning. Now developers can efficiently manage resources from the command line, debug source code in their production environment, easily run API backends using industry-leading tools, and streamline the application development process.

The Return of the Private Cloud

With cost savings being a key driver for cloud adoption, many organizations choose the public cloud to achieve economies of scale. Although the public cloud sector continues to attract enterprise customers looking for a combination of price economy and cloud productivity, many customers also look to run several workloads privately within a private cloud. Contrary to popular belief that public cloud platforms are the most economical, recent research suggests that private cloud solutions can be more cost-effective than public cloud infrastructures.

The Return of the Private Cloud

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Why Private Clouds are Becoming Popular Again:

The continuous need for speed and efficiency of operations is making cloud adoption a priority for many businesses today. Cloud services enable modern organizations to break the barriers of traditional business operations and drive innovation at a rapid pace and in affordable ways. According to a study, public cloud adoption increased to 92% and private cloud to 75% in 2018.

Private clouds work better for large enterprises, especially if they operate in regulated industries or have workloads with sensitive data. With private clouds, organizations have more control over their data and enjoy additional security, compliance, and delivery options. Also, with the generational shift in IT management processes and practices, private clouds enable the millennial generation to adopt simplified tools and intuitive graphical user interfaces.

Why Public Clouds Aren’t as Economical as they Seem:

Containing costs is one of the main reasons for public cloud adoption. Other reasons are the access to on-demand resources, quicker time to market, easier product development, and the ability to scale to meet varying needs. However, many organizations do not realize that public clouds are not always the bargain they expect and that they may not deliver the promised cost savings. Although public clouds help organizations grow revenue and increase productivity, with scale, the costs can mount rapidly, without the expected savings accruing to the business.

Also, in order to move workloads to the public cloud, organizations must consider the potentially high cost of re-architecting and re-coding applications. This is significant when compared to the relatively minor premium incurred in maintaining a private cloud. This certainly busts the myth that public clouds are always the cheapest option.

Making Private Clouds Economical:

Although the private cloud has often been touted as the right choice for organizations with mission-critical requirements at a premium price, this is not the full story. There are several ways in which private clouds are more economical than public clouds. 41% of organizations claim to be saving money using a private cloud instead of a public cloud – in addition to the perceived benefits of ownership, control, and security.

  • For organizations that have the expertise to manage a large number of servers at a high level of utilization, private clouds can offer a total cost of ownership (TCO) advantage.
  • Organizations that use capacity-planning and budget-management tools can achieve substantial economies of scale. Capacity-planning reduces costs by ensuring the hardware is being utilized with as little waste as possible. And budget-management enables consumption and expenditures to be tracked with the goal of reducing waste and optimizing spending.
  • High levels of automation an also reduce manual tasks, allowing administrators to devote more time to other critical tasks. Organizations can increase labor efficiency by having access to qualified, experienced engineers. They can reduce operational burdens with the outsourcing and automation of day-to-day operations – high levels of automation drive down management costs significantly.
  • Another key consideration is how organizations utilize cloud resources. Since TCO of a private cloud is directly proportional to its labor efficiency and utilization, for self-managed private clouds to be cheaper, utilization and labor efficiency must be relatively high. If the infrastructure is only used to about 50% of its capacity, the cloud administrator will need to manage a large portion of the infrastructure to achieve a TCO advantage.
  • Lower costs can also be achieved by maximizing software license use. If licenses are based on CPUs, organizations can achieve improved license utilization by hosting a large number of virtual machines per CPU in a private cloud as compared to a public cloud where each virtual machine needs to be licensed separately at increased costs.

Choosing What Works Best:

In order to get the most out of their cloud investment, organizations must have a clear understanding of what works best in various cloud scenarios and what does not. They need to get past common myths and public hype around the “public vs. private cloud” debate. Enterprises looking to adopt the private clouds need to deploy it for large projects with high utilization and labor efficiency, using the right license model and the right combination of tools and partnerships to achieve economies of scale.

According to a study, even if the public cloud were to cost half as much as the private cloud, enterprises would migrate only 50% of workloads. This suggests that no matter how economical the public cloud may seem, organizations will still have other compelling reasons to use the private cloud. Organizations can also opt for a multi-cloud strategy to avoid vendor lock-in and leverage the best attributes of each platform. According to a report, 81% of enterprises today have a multi-cloud strategy. We have written previously about the multi-cloud and when it may be right for you. Go ahead, hop across there is that’s the next set of questions in your mind.

The Big Deal About Interactive emails, and How They Could Rule This Online Shopping Season

Email marketing is not dead. In fact, it’s among the most effective ways for online retailers to build relationships with customers. For substantial conversions, you should be emailing your customers regularly. However, if your email campaigns aren’t working, it’s time for you to examine what you’re doing.

Your emails should create user engagement, and among the best ways to do that is to increase interactivity. Interactive emails are a great way to bring more functionality into your customers’ inbox; this could range from showing a hidden message when the user clicks a button to creatively using scrolling to tell a story – there’s a lot of untapped potentials.

interactive emails for shopping seasons

The big deal about Interactive Emails:

Do you know? 54% of marketers say increasing engagement rate is their top email marketing priority. A remarkable alternative to traditional emails, interactive emails are set to be the next big thing in the e-commerce industry. Interactive emails are a great way to surprise and delight customers with new offers, discounts, and more. They are making interactions between retailers and customers more engaging. With innovative ideas, creative designs, interactive features, and visually attractive content and videos, interactive emails are driving substantial increases in the click-through rates as they enable customers to act from within the email body.

  • You can offer menus in emails (like on the website). Users can easily surf products or service categories right within their inbox. Menus are great for new product launches, recommendations, and cross-selling and can help you improve your click-through rates and generate traffic.
  • Delivering engaging content through photos, GIFs, and videos is an excellent way to capture the attention of your customers. From the latest news to the latest product on your website, how-to messages to interactive pics –embedding such features in emails is better than sending a link to your website or social handles.
  • Since e-commerce sites have an extensive array of products, counters work great to create a sense of urgency in an email.  Countdowns to promote a sale or event promote quick action. They allow you to offer limited period discounts and motivate customers to make a purchase directly from the email body.
  • If you want to showcase the latest products or trends or offers, rotational banners are perfect to drive customer interactions. Not only do they make email aesthetics attractive and catchy, but also help in keeping content precise and to-the-point.  
  • Another great way of driving interaction is through the use of sliders. By displaying multiple products in a limited space, you can encourage users to click to view the next or previous slide – with a different CTA for each. You can use sliders to showcase new products, recommended products, product reviews, and more.

What makes them so Effective?  

Although interactive emails are becoming popular across industries, it is the e-commerce space where they really shine. Here are 5 features that make interactive emails so effective in online shopping:

  1. Fill cart: Imagine if customers could shop for their products directly from the email body, without opening the app or logging into the website? Through interactive emails, you can allow customers to easily navigate through products, fill their cart, and check out right from the email. By updating the cart and associated prices, taxes, and discounts in real-time, you can increase customer satisfaction and revenue.
  2. Surveys and product reviews: Very often, customers want to provide feedback and product reviews but do not have the time or patience to log into the website. With interactive emails, customers can directly provide feedback and review products from the email body, and save substantial time and effort. You can gain valuable information about customers, get feedback about your products and services, increase the click-through rate on your emails, and show them that their opinions matter.
  3. Story-telling: Not everything in email marketing has to be about increasing revenue. It can also be about engaging and delighting customers and building relationships through interesting story-telling. Story-telling is a great way to captivate your audience. First, listen to your customers and discover their motivations, concerns, and aspirations. Then, align your story with what drives them, and link your products with their lives to tap the right emotions.
  4. Real-time marketing: If you’re looking to pursue additional sales opportunities, interactive emails are a great way to enable real-time marketing. By enticing customers to make quick decisions based on a certain interaction, you can not only help them make a purchase but also ensure it exactly fits their needs. For example, if a customer leaves your website with an abandoned cart, you can instantly send him/her an email and offer an incentive to buy immediately or check if they have a query. Price is often the main reason for abandonment, a discount may act as a great motivation to finalize the sale.
  5. Add to calendar: Since sale days are a great way to cash in on increased footfall, an add-to-calendar option can enable you to promote your event. Although it is a simple way to increase interactivity, it is highly effective as it will ensure your customer is reminded of the event, and in all probability, drop by as appointed.

Gear up for the Shopping Season:

Interactive emails are a great way to make customers aware of new and attractive offers. By utilizing interactive elements, you can urge customers to make decisions. If you want to build relationships with your customers, it is time to add value to the emails you send and ensure they don’t unsubscribe from your mailers. Make your customers scratch, pull or slide content, spark their curiosity, and enhance their experience with interactivity this shopping season.

Several online retailers are competing to own the 2018 shopping season. Through innovative and interactive tactics, you can truly drive customer engagement and stand out.

Effective Strategies for Cross Browser Testing

With the latest technologies and trends coming up in the online world, the major thing that is being added is the number of mobile devices and the latest updates in browsers.

Every other day, a new mobile device is launched in the market. With the buzz of new iPhones coming around the excitement gets doubled. However, this is not just limited to mobile devices, we see frequent updates in browsers as well.

Some people love chrome, others are fond of Firefox. Don’t forget Safari too. Some unfortunate souls even have to use Internet Explorer because of company restrictions.

cross-browser testing strategies

So, billions of people, thousands of choices for browsers, devices, operating systems. But one thing remains the constant, USER EXPERIENCE. The user experience or you can say the experience that you provide to your users irrespective of the browser, operating system, or device. So, you need to perform cross-browser testing for your website across hundreds and thousands of possible combinations to test that the website or the Web application should work perfectly.

Testing on all the thousands of combinations is not a wise thing to do, you will spend all the time testing your website even on some combinations that your audience might not be using or you might be missing out on some common errors because of that. So, you need to have an effective and a time-saving cross-browser testing strategy.

So, let’s get started.

Target the Browsers to Add in The Testing Matrix:

You need to prepare a matrix of browsers that your audience might be using.

It will require a lot of research on the data before you can choose the few among the hundreds of browsers available on which your website is meant to be rendered by your audience.

Let’s discuss the tools that will help you in gathering relevant information regarding the browsers used most by the users you are meant to target.

  1. Google Analytics – Google analytics can help you track important data like the device used by the users to browse your website, the platform and operating system mostly used, along with the browsers used by them. Using it, you can prioritize the most used browsers and sort them accordingly in the matrix.
  2. Data from Other Sites – If your website is new, Google Analytics won’t help you much. In that case, you can research on other sites that are similar to yours and gather analytics on them.
  3. Stats Counter – Stats Counter is the perfect tool that lets you gather data specifically based on your requirements. You can keep filters like location, time, operating system, browser, and sort accordingly.

Once the data source is figured out for your browser matrix, it’s time to decide the key factors you will need to cover.

Data Points Required for Your Browser Compatibility Matrix:

Let’s discuss the important data points to collect from the analytic tools based on which you can plan your cross-browser compatibility strategy.

  1. Platform – The users can access your website from a desktop, mobile or tablet. Find out the most preferred platform of your users and make sure that the website is rendered properly on them.
  2. Browser Usage – After you have selected the platforms, find out the browsers that are mostly used to access websites on those platforms. The results will vary location wise and also according to operating systems.
  3. Compare the Platforms – Do the research over and over again and find out a combination of the most used platform, browser and operating system in a specific zone. Know the best combination preferred by users before you start testing.

Once your analysis is done, sort the browsers according to the following points that will help you to find out the best-supported browser for your website.

  • A- The browser that is most loved and fully supports your website.
  • B- Browsers that are not so preferred yet supports your website.
  • C- Browsers that are partially supported and most preferred.
  • D- Browsers that are partially supported and least preferred.
  • E- Preferred browsers that do not support your website at all.
  • F- Least preferred browsers that do not support your website.

Analytic results will help you rate the browsers accordingly based on traffic and conversion.

browser rating based on traffic and conversion

So that you can prioritize which browser to test first and which one the last.

Prerequisites For Cross Browser Testing:

Now that your browser matrix is ready, and you have targeted the browsers on which your website should render properly, let’s discuss the perquisites that are mandatory to have before you perform cross-browser testing.

  • First, make sure that you know how to perform cross-browser compatibility testing or at least have a testing team in your project.
  • Formulate a testing strategy by getting all the devices ready with you. In case any device is unavailable, use an emulator. Install all the required browsers in the system on which testing is to be performed.
  • You can also use a cloud-based cross-browser testing platform like Lambdatest that will provide you with thousands of browsers and devices on which testing can be performed.
  • The Three Basic Steps In Cross Browser Testing:

    You’re now all set with the browsers to test upon, the tool and all the prerequisites, now it’s time to know how to go ahead with performing cross-browser testing. You can execute your website’s cross-browser compatibility tests in three phases.

    • Testing for Bugs – This is the first step where you will execute all the test case scenarios and note down any bugs that you notice. While fixing those bugs you should make sure that any new bug is not created. Perform proper unit testing after each defect is fixed.
    • Create Plans and Strategies – This is the second phase where you repeat the test case scenarios performed in stage 1 at all the browsers. Classify the browsers according to priority into 3 types – High Risk, Medium Risk, and Low Risk. Your aim should be to cover all the test case scenarios in a very few iterations of testing rounds.
    • Sanity Testing – After all the defects, misalignments and other compatibility issues are fixed, its time to move on to Sanity Testing. Here, prioritize the browsers and start testing, starting from the least preferred ones. Go back to level 2 and perform the same test until you are sure that your website is rendered properly in all the targeted browsers.

    What Can be the Possible Elements to Test for Cross Browser Compatibility?

    Once you have set your system for testing, procedure, tool, the strategy now let’s see the elements that you need to check or that might be the victims of cross-browser issues.

    • Alignment of elements – Ensure that all the elements in your website are properly aligned in all the browsers.
    • SSL Verification – Some browsers may not support your SSL certificate. To avoid unforeseen situations when a user is unable to access your website because your SSL certificate is not supported by the browser, check your SSL certificate’s browser support.
    • Rendering of Fonts – Nowadays, most websites use cool new web fonts. However, some new fonts are not supported by many browsers. You will need to make sure that the fonts you are using in your website are supported by all the browsers that you selected in the matrix.
    • Media Elements – You should ensure that the audio or video elements used in your website are rendered properly in all the browsers.
    • Validate HTML and CSS – An HTML tag when left open will easily cause disruption in the display when a website is rendered in the browser. Use W3C Markup or other validation services to ensure that your code is properly written without any syntax error.
    • Check the API Requests– It is often observed that in a website when an external API is called, it throws some errors because the API request is not supported by the browser. You will need to make sure that the browsers on which you are running tests accept all API requests which are made by your website.
    • Pop-Ups– Many times pop-ups don’t occur in some browsers so check if all the pop-ups are being displayed properly and are opening in all browsers. Also, see if they are correctly aligned as per the design.
    • Alignment of checkboxes– Checkboxes can cause problems in some browsers while they may render properly in the others. Make sure that all your checkboxes are properly aligned and in working condition in all browsers.
    • Test the buttons– Not all buttons work the same in all browsers. Test by clicking on them, check if they are redirecting to the correct URL.
    • Drop Down Menus– IE and Safari are the favorite victims of drop-down menus. Check if the drop downs work as expected in all the browsers.
    • Grids/Tables– Broken grids and tables affect the user experience badly. Check the alignment and location of tables and grids( if any) across every browser.
    • Test for sessions and cookies, zoom in and zoom out functionality, the appearance of scroll, dates, rendering of HTML animations, flash media elements, mouse hovering across all the browsers.

    Once you make sure that all your elements are rendered on all browsers, devices, and operating systems and you get a seamless experience all the platforms. You are all set with the perfect cross-browser testing strategy.

    With the software industry evolving daily and new devices and browsers arriving in the market, cross-browser testing can be a little scary at first in case of a large application since it involves hundreds of combinations and maybe thousands of scenarios. However, once a proper testing strategy and planning is devised section wise, the job becomes much easier and you ensure a seamless experience for all your users no matter what device or browser they are using.

    Author Bio:

    Deeksha Agarwal is a growth specialist at LambdaTest and is a passionate tech blogger. She loves to write on latest trending technologies.

5 Reasons Startups Should Care About Blockchain

Blockchain – the shiny new object in the technology toolkit has taken over the headlines. The market is buzzing over the long-term implications of Blockchain, decentralized systems, and cryptocurrencies. The promise is to disrupt industries such as banking and finance, retail, real estate, and healthcare. The global spending on Blockchain technology according to an IDC report, in 2018 alone, is expected to be cross $2.1 billion.

The report also says, “The year 2018 will be a crucial stage for enterprises as they make a huge leap from proof-of-concept projects to full Blockchain deployments. As a leader in Blockchain innovation and integration, the US will continue to invest in Blockchain throughout the forecast, spending heavily in financial services, manufacturing, and other industries.”

5 reasons startups should care about Blockchain

While all this is very exciting, is this only a “big enterprise” story? To my mind, NO. I feel startups should take a close look at evaluating this technology and the benefits that it brings to the table. Given that the world of Blockchain is yet to mature completely, startups have the opportunity to become early adopters and proponents of this technology. With a first-mover advantage, startups can create a strong Blockchain ecosystem and build a competitive advantage before this space becomes saturated. Here’s my take on why startups should care about Blockchain

  1. Security:

    Blockchain is, as most know, a Peer to Peer (P2P) network. The power to manage and manipulate the network rests with multiple stakeholders. This means that no one person can hack, close chains, manipulate or shut down the blocks, making the Blockchain network guaranteed free from any frauds or hacks.

    Blockchain systems are poised to become the defacto method of storing enterprise data owing to the incorruptible digital ledger of transactions (DLT). The DLT stores all data in an automatic ledger and is encrypted automatically using the latest cryptographic methods. Blockchain systems are also decentralized. This distributed nature of the systems reduces security risks greatly.

    Data is the most valuable currency today. And with that comes the concerns over data security. With the spending on information security standing at $86.4 billion in 2017 and expected to exceed $1 trillion cumulatively from 2017 to 2021, startups with innovative solutions in the space stand to gain.

  2. Transaction and Record Transparency:

    Transparency is ingrained in the DNA of Blockchain. It also provides a high level of privacy since the transaction details are only shared with the defined set of participants involved in the transaction. This technology eliminates third-party interventions. Irrespective of what is the use-case, be it personal details storage, storage of enterprise data, transactions, currency exchange etc., every transaction detail can be clearly tracked.
    How? Well, Blockchain systems employ completely audit-able, unforgeable, indelible, and trackable ledger of transactions. An entry can only be made in the ledger if it is validated by the system using an algorithm. In these GDPR days, startups could benefit from incorporating Blockchain into their products and solutions to assure security and privacy.

  3. Easier Global Partnerships and Low Transaction Costs:

    Blockchain is a technology built with collaboration in mind. Now using Blockchain, startups can propel their growth story by collaborating with offshore partners, and even employing foreign workers. As Blockchain utilizes a global network that is distributed across the world, organizations are no longer restricted by borders to fuel their growth story. Transactions using Blockchain technology also becomes much simpler. There is already the use of smart contracts using Blockchain.  
    Here, a 3rd party, also interacting with the registry, validates the transactions. This means startups and SMEs can transact with contractors, employees, and even customers without turning to (or having to pay fees to) the PayPal types. This means that Blockchain transaction costs are negligible.

  4. Disrupting Storage:

    Decentralized storage also drives constant availability creating a new Cloud paradigm that may be cheaper and easier for startups to access and use. Since this type of decentralized cloud storage is supported by computers and require no manual interventions, there is 24X7 data access and almost zero downtime, without compromising on security.

    PR Newswire estimates the cloud storage market to $88.91 billion by 2022. As the decentralized storage industry is growing rapidly, Blockchain has the potential to completely disrupt both Storage Marketplaces and Storage Infrastructure. While cloud has become central to optimized data storage, 2017 was full of stories of data breaches bringing the issue of third-party dependencies into the light. Blockchain technology gives the cloud the extra edge by giving organizations the capability to centrally manage workloads while the data remains distributed. A number of new startups are utilizing the Blockchain storage marketplace where the “hosts sell their surplus storage capacity and renters purchase this surplus capacity and upload files.”

    Also, as the cost of computing increases incrementally, Blockchain emerges as the leveler for startups. As Blockchain employs pre-existing servers, the decentralized platforms do not need a large investment and thus take the ambiguity out of storage capacities and the associated costs. This cost saving can’t hurt!

  5. Reduce the Cost of Doing Business:

    Blockchain technology and DLT brings improved efficiencies, business flexibility, and the capability to respond to market changes with speed. Startups can implement automated Blockchain networks to address issues like antiquated infrastructures, manual processes, and pen-and-paper systems, and implement digital systems with ease. I mentioned smart contracts.

    These programmable smart contracts can eliminate bureaucracy and lawyers. Here codes are stored on the Blockchain network and can be executed automatically on meeting certain specific conditions. This eliminates the need for third-party interventions like those in banking transactions or legal agreements. By relying on these algorithms, startups can reduce their cost of doing business by streamlining their end-to-end funnel, the supply chain etc.

Clearly, Blockchain is more than Bitcoin and cryptocurrencies. Blockchain technology is accelerating us to a future that is more secure, transparent and fair. It will be interesting to see how the startups leverage this.

Complete Guide to Usability Testing

Whether it is a myth about usability testing or its process, we offer you details that matter.

Let us now begin our today’s discussion on how to perform usability testing for your website and discuss various methods to do so.

When you visit a website, like Amazon, eBay, etc., what is the one thing that makes you stay there? Is it the design, offers, or the fact that you can use it easily and find relevant information or product effortlessly? Though all these factors are crucial for retaining a visitor, it is the ease of usability and satisfied user experience that guarantees your happiness and encourages you to stay on a website longer.

complete guide to usability testing

So, what is this usability and why is it so critical for your websites?

Nowadays, when the number of the competitors is increasing rapidly, design and content are not enough to retain users, it also requires engaging, intuitive, and responsive user experience, which should be considered by the designers and development teams during the development phase.

Usability, which is defined by ISO as “the extent to which a product can be used by specified users to achieve specified goals with effectiveness, efficiency, and satisfaction in the specified context of use” is, therefore, an integral part of a website and is ensured with the assistance of usability testing.

The question then arises:

What is usability testing and how it helps ensure the usability of a website?

Asking people to review your work, might be a time-consuming task, but it always works in your favor. This process can be applied to any discipline, especially to improve the user experience.

Usability testing is one such method of user research or review, which is used to validate the design decisions for an interface as well as to verify its quality, accessibility, and usability by testing it with representative users. It helps create a website/product that connects with users and establishes credibility, builds trust, and ensures customer satisfaction.

Usually conducted by the UX Designer or user researcher during each iteration of the product, it enables them to uncover various issues with the website’s user experience and resolve them to ensure it is usable enough.

Hence, usability testing ensures that the interface of a website is built in a way that it accurately fits the user’s expectations and requirements. Moreover, it determines whether it is user-friendly and if users will come back to it or not.

Methods used to test your website:

An area of expertise of UX/UI designers and developers, usability testing, is performed with the assistance of various methods, which help the team accumulate necessary details about the website’s usability.

Popular testing methods are:

  1. A/B Testing:

    A/B testing or split testing is used for an experimental analysis, wherein two versions are compared by the team to choose the best version of the website or its component and to determine the one that performs best.

  2. Adv:

    It uses a qualitative and quantitative analysis that validates the intended goal.

  3. Remote Usability Testing:
    Another important method of usability or user testing, remote usability testing is used when the user and researcher are in different geographical locations. This test is moderated by an evaluator interacting with the participants using various screen sharing tools.

    Adv:

    It offers developers more realistic insight than lab research and allows them to conduct more research in the shorter period of time.

  4. Co-discovering Learning:

    In co-discovering learning, users are grouped together to test the product, while being observed. Test users talk naturally with one another and are encouraged to define what they are thinking about while performing the allocated task.

  5. Adv:

    This helps measure the time taken to complete different tasks as well as the instances where the users asked for assistance, among other things.

  6. Expert Reviews:
    Expert reviews involve UX experts who review the product for any potential issues or defects, which are evaluated by them with the assistance of the following techniques:
  7. Eye-Tracking:
    This method of usability testing is used to capture physiological data of users conscious and unconscious experiences of using the website. During this testing, the motion of the eye, its movement and position are tracked, to analyze user interactions and time between clicks.
  8. Adv:
    It helps to identify the most eye-catching, confusing and ignored features on the website.

    Read more about eye-tracking.

    But wait, there’s more:

    Apart from these testing methods, there are other effective methods that do not require any test lab and can be executed without investing any technical efforts.

  9. Questionnaires, Surveys, & Interviews:
    An effective method of usability testing, questionnaires, surveys, & interviews involves asking several questions from the users, which helps the researches get informative feedbacks in real time.
  10. Adv:

    Performed when there is a requirement for a large number of opinions, these methods help avoid ambiguity and deliver structured information.

  11. Realistic Scripts & Scenarios:
    This method of usability testing involves both developers and tester, who work together on a preplanned test scenario and imitate the steps that a user while accessing the website.
  12. Adv:
    They act as a user and replicate the anticipated steps a user takes, which are then assessed by the developers to improve the website’s usability.

  13. Drawing on Paper:
    Drawing on paper is a popular & cost effective method of usability testing used by designers and developers, wherein they create a website prototypes on a paper and let users test it and its various components, like controls, bars, sliders, etc.
  14. Adv:

    This is an effective testing technique as it allows the developers to gain relevant feedback on the paper prototypes easily.

  15. Think Aloud Protocol:
    Also known as lab usability testing, think aloud protocol, is a qualitative data collection technique, used to understand the user’s own reasons for their website usability behavior.
    During this process, test sessions are either audio or video recorded for developers future reference.

Whether a website or an app, these methods of usability evaluators can be used by the team to get real users data, which can be utilized to make the product suitable for the target audience.

Now, let’s move on to understanding the process of usability testing.

Process of Website Usability Testing:

The process of usability testing is a simple one and can be executed either by the developers, testers or appointed users. It follows a set of five steps which are:

  1. Planning:
    The test begins with the team identifying the goals and defining the scope of testing. Furthermore, they agree on the metrics, determine the cost of the usability study and create the test plan and test strategy.
  2. Recruiting:
    Once the necessary plan is prepared, the team and the resources are assembled and the tasks are assigned accordingly. Finally, the team lead or manager decides the reporting tools and templates, which will be used for test execution.
  3. Test Execution:
    It is in this stage of the process that the team performs the usability test, during which they communicate the scope of testing and capture unbiased results.
  4. Analysis:
    After test execution, the team categorizes the results and identifies the patterns among them, which are then used to generate inferences.
  5. Reporting:
    Finally, once the analysis of the results is completed, the team offers actionable recommendations as well as stakeholder briefing, to help rectify issues and to remove any issues regarding the testing.
  6. Advantages Offered by Usability Testing:

    By investing in usability testing, you will not only make your users and potential clients happy but also reap various other benefits, which might help you increase your ROI and create a renowned reputation in the market.

    We’re not through yet:

    You will also enjoy various other benefits, like:

    • Improve Retention Rate:
      Retaining customers is an important source of income for the organization in the retail world. By conducting usability testing organizations can improve the retention rate, as it allows them to understand why users are leaving their site and take necessary preventive measures.
    • Reduced Costs:
      It is comparatively cheaper to conduct usability testing, rather than creating a new website or redesigning a one that does not meet the requirements of the user and offers them an unsatisfactory user experience.
    • Understand User Behavior:
      From determining the most engaging elements on the website to identifying the pattern of user behavior, usability testing helps the team immensely and offers them data which can be used to create a better website.
    • Detect Bugs & Defects:
      Usability testing is immensely helpful in detecting defects and bugs that were not visible to the developers.
    • Reduce Support Calls:
      By conducting usability testing, the team can minimize the number of support calls or inquiries users will have to make to the help desk, as they’ll come across fewer usability problems and queries.

    Conclusion:

    So, these are the various ways to perform usability testing for your website.

    Now I’d like to turn it over to you:

    Which of these methods do you like the most and which one do you find to be the most effective and useful?

    Also, if you have any suggestions, let me know in the comments section below.

    If you are still unsure about usability testing, you can contact our experts and get usability testing as per your requirement.

How Cloud Makes Big Data Better?

Information technology at one time was that exclusive club that allowed only the elite few such as very large organizations and government bodies etc. through its doors. The story is quite different today. The rise and adoption of technologies such as the cloud have led to the democratization of IT, increasing the reach of technology, enabling cost reductions, and providing a plethora of applications to choose from without making any heavy investment. The cloud has given the much-needed horsepower to make the world more software defined. It hardly comes as a surprise that the cloud ranks high up in the priority for organizations across the globe.

Along with the cloud, we have also witnessed the rising importance of Big Data. Big Data has moved from the ‘nice to have’ to a ‘must have’ initiative as we move deeper into the data economy. The promise of valuable insights to create competitive advantage, drive revenues and spark new innovations are reason enough to bring it on the agenda of all kinds of businesses. As the adoption of Big Data and Cloud continue to increase, we are witnessing a growing interdependence between these two technologies with the promise of phenomenal gains.

How cloud makes big data better?

  1. Convergence – is the name of the game:
    While big data and cloud evolved independently over time, today these two technologies are becoming increasingly intertwined. The growing volumes of data and the need for faster analytics have driven big data to the cloud. Organizations today are looking at new data models derived from structured and unstructured data sources, they need complex event processing applications, they need usage-based compute resources, and they demand greater computing power. With an on-premise data store, processing and analyzing these high volumes of data becomes hard to execute. And given the operational and management costs associated with these on-premise solutions, it does not present itself as an agile and cost-effective solution.
    The cloud, on the other hand, helps in alleviating the enterprise data load and offers not only greater computing power, increased storage, and data agility, it also makes it infinitely easier to analyze and derive faster data insights.
  2. A conversation shift:
    With the conversation moving from ‘where can we store all this data’ to ‘what can we do with all this data’, organizations are moving towards an orientation that is more outcome-based. Clearly, cloud computing and big data are better together. With a growing dependence on data, enterprises are looking at greater effectiveness from big data platforms. With the greater integration of data from both structured and unstructured resources, the big data platform that we need must be highly scalable, elastic, and performance driven. And this can be achieved by leveraging the computing capabilities of the cloud.
  3. The need for greater scalability:
    Performance issues such as latency have no place in the enterprise today. When it comes to analytics, latency can play havoc with performance. The lack of efficient data warehousing and an inability to access real-time BI to answer business queries is a challenge that can be navigated using the cloud. Latency can be brought down efficiently to almost single digit milliseconds using the cloud to create direct interconnections between the data and the analytics. The need for additional processing power can also be addressed with the cloud as it is always there for the taking.
  4. The financial advantage:
    Cost is an obvious advantage of the cloud. On-premise big data storage and analytics can cause a huge drain on the IT budgets as the organization then becomes responsible towards maintaining the big data centers. The cloud, on the other hand, makes no such demand and gives the organizations the flexibility to maintain small and efficient data centers that can be scaled on-demand. The cloud also makes it much easier to gather external data, something that is growing exponentially today. It also enables data access anytime, anywhere without any additional infrastructure demands, thus making it more cost-effective.
  5. Increased collaboration:
    Analytics is collaborative. Collaboration is also a driver of cloud adoption.
    BI and big data analytics work better in the cloud as the cloud provides ready access to data, BI, and processing applications. The cloud makes it possible to share visualizations, share data, and perform cross-organizational analysis. This makes the data analysis available to a distributed user base as well and makes information more accessible to a broader demographic.
  6. Better maintenance and lesser complexity:
    Analytics platforms, like software products, need maintenance. They need frequent upgrades, redesigns, migrations…the list goes on. By moving the analytics platform to the cloud, organizations can ensure that everything remains up-to-date at all times. The cloud also takes away the cost burden of over-provisioning for peak consumption as organizations can access on-demand scalable resources. With the convergence of cloud and big data, today we have cloud-based analytics applications that move the analytics closer to the data. Cloud analytics platforms also take away the effort that goes into putting together a functioning analytics platform. With a ready-to-use data processing and analytics setups, organizations become capable of accessing real-time data-driven insights faster. The can hit the ground running, as it were.

Big Data is only useful when it is used for analytics. It is also clear that the data deluge is only going to increase. And organizations will be hungry to use this rising deluge to their advantage. The key insight from this post is that this will only be possible by multiplying the power of big data with the advantages of the cloud.

The 3 Indispensable Elements of an IoT Solution

IoT (and the things it can do) is one of the most widely discussed technology topics today: from precision farming to remote health monitoring, smart TVs to energy management systems. IoT is bringing a transformation across industries; it is predicted that by 2019, the IoT market will reach $1 billion. However, it is still a distant dream for most organizations do not yet know how to build a successful IoT solution. Although the use of smart, modern, innovative devices is commonplace, these tend to operate in isolation and not in a dynamic, interconnected world as the best Internet of Things solutions should.

3 Indispensable Elements of an IoT Solution

Elements of an IoT Solution:

For organizations looking to move from a disconnected world to a new, connected one where boundaries between hardware and software systems are constantly blurred, there are challenges at every level. These range from overall architecture to device connectivity, and data security to user interaction. Also, it’s easy to get lost in the maze of standards, technology options, and product capabilities. If you’re looking to build a successful IoT solution, there are the 3 indispensable elements:

  1. Hardware: The hardware you choose impacts your IoT solution in a variety of ways: device cost, capabilities, user experience, and more. Hence, choosing the right hardware is imperative to the success of your IoT solution. Start by identifying the kind of problem you are trying to solve. Next, make a list of likely solutions and use cases. And lastly, determine where and what degree of personalization you would require. Platforms like Raspberry Pi offer an entire Linux computing platform with USB, HDMI, and Ethernet port connectivity for building a top-notch IoT solution. Hardware platforms like these enable you to:
    1. Build custom chip designs and directly integrate sensors within the chip.
    2. Drive sufficient power efficiency, with an appropriate form-factor, and ruggedness.
    3. Integrate complex onboard analytics to run complex algorithms.
    4. Wire the chip such that only relevant information is sent to the cloud.
    5. Enable design modularity to accommodate future hardware upgrades and ensure maximum scalability and ROI.
  2. Software: Although the hardware is an important element of any IoT solution, it cannot by itself deliver results. For that, the device must be loaded with APIs and software development kits that let you build cutting-edge IoT solutions. It can be said that any IoT solution is only as good as the software that binds it. AWS IoT for instance, allows you to connect devices, secure data and interactions, process and act upon device data, and enable offline device interaction. Robust IoT software platforms like these allow you to:
    1. Integrate several capabilities and features into one solution.
    2. Build a high level of security and ensure strict software quality measures.
    3. Continuously monitor and review the code to avoid any failure.
    4. Build scalability and flexibility as per the need.
    5. Collect and manage data and enable analytics and visualization.
    6. Enable remote connections to all devices in the ecosystem.
  3. Cloud: The main aim of any IoT solution is to connect and allow communication between devices, people, and business and operational processes. Since IoT devices generate massive amounts of data, and the analysis and processing of that data need to be completed quickly and easily, managing the flow and storage of this data is a herculean task. Cloud computing with its different models and implementation platforms plays a very important role in enabling seamless communication. Google Cloud IoT offers a fully managed and integrated set of services for easy capture, management, and analysis of IoT data from globally dispersed devices on a large scale. Cloud computing platforms like these enable you to:
    1. Optimize investments in extensive hardware and management of physical network and infrastructure.
    2. Speed up the development process and cut down on costs.
    3. Manage and analyze data instantly and enhance the overall efficiency and functioning of your IoT solution.
    4. Enable application development portability and interoperability across the ecosystem.
    5. Gather data from the IoT device, transmit to the cloud, analyze it, and provide it back to the end-user in the form of actionable information.
    6. Scale up the infrastructure, depending on your needs, without setting up any additional hardware.
    7. Enable remote device life-cycle management including device registration, updates, and diagnosis.

Establish the Right Strategy:

IoT presents enormous opportunities for virtually every business; according to IDC, three industries that are expected to spend the most on IoT in 2018 are manufacturing ($189 billion), transportation ($85 billion), and utilities ($73billion). It’s fair to assume that a variety of other industries will follow suit in short order. The onus of a successful IoT solution lies entirely on the ecosystem it is built upon. This is a complex undertaking and requires careful consideration of each of the 3 main factors to provide a great experience for the end-user. With the right strategy in place, you can open the door to smart analytics, application management, and data security, to successfully ride the IoT wave.

Watch Out for these DevOps Mistakes

The past few years have witnessed the meteoric rise of DevOps in the software development landscape. The conversation is now shifting from “What is DevOps” to “How can I adopt DevOps”. That said, the Puppet’s State of DevOps Report stated that high performing DevOps teams could deploy code 100 times faster, fail three times less and recover 24 times faster than the low performing teams. This suggests that DevOps, like with every other change in the organization, can be beneficial only when done right. In the haste to jump on the DevOps bandwagon, organizations can forget that DevOps is not merely a practice but is a culture change – a culture that breeds success based on collaboration. While DevOps is about collaboration between teams, continuous development, testing and deployment, key mistakes can lead to DevOps failure. Here’s a look at some common DevOps mistakes and how to avoid them.
Watch Out for these 8 DevOps mistakes

  1. Oversimplification:
    DevOps is a complex methodology. In order to implement DevOps, organizations often go on a DevOps Engineer hiring spree or create a new, often isolated, DevOps department to manage the DevOps framework and strategy. This unnecessarily adds new processes, often lengthy and complicated. Instead of creating a separate DevOps department, organizations must focus on optimizing their processes to create operational products leveraging the right set of resources. For successful DevOps implementation, organizations must manage the DevOps frameworks, leveraging operational experts and other resources that will manage DevOps related tasks such as resource management, budgeting, goals and progress tracking.
    DevOps demands a cultural overhaul and organizations should consider a phased and measured transition to DevOps implementation by training and educating employees on these new processes and have the right frameworks in place to enable careful collaboration.
  2. Rigid DevOps processes:
    While compliance with core DevOps tenets is essential for DevOps success, organizations have to proactively make intelligent adjustments in response to enterprise demands. Organizations thus have to ensure that while the main DevOps pillars remain stable during DevOps implementation, they make the internal adjustments that are needed in internal benchmarking of the expected outcomes. Instrumenting codebases in a granular manner and making them more partitioned gives more flexibility and gives DevOps teams the power to backtrack and identify the root cause of diversion in the event of failed outcomes. However, all adjustments have to be made while remaining within the boundaries defined by DevOps.
  3. Not using purposeful automation:
    DevOps needs organizations to adopt purposeful automation – automation that is not done in silos like change management or incident management. For DevOps, you must adopt automation across the complete development lifecycle. This includes continuous delivery, continuous integration, and deployment for velocity and quality outcomes. Purposeful end-to-end automation is essential for DevOps success. Hence organizations must look at complete automation of the CI and CD pipeline. At the same time, organizations need to keep their eyes open to identify opportunities for automation across processes and functions. This helps to reduce the need for manual handoffs for difficult integrations that need additional management and also in multiple format deployments.
  4. Favoring feature-based development over trunk-based development:
    Both feature-based development and trunk-based development are collaborative workflows. However, feature-based development, a development style that provides individual features their isolated sandboxes, adds to DevOps complexity. As DevOps automates many aspects of the code between development and production environments, keeping different conceptual flavors around the codebase makes DevOps more complex. Trunk-based development, on the other hand, allows developers to work in a coherent and single version of the codebase and alleviates this problem by giving developers the capability to manage features through selective deployments instead of through version control.
  5. Poor test environments:
    For DevOps success, organizations have to keep the test and production environments separate from one another. However, test environments must resemble the production infrastructure as close as possible. DevOps means that testing starts early in the development process. This means ensuring that test environments are set up in different hosting and provider accounts than what you use in production. Testing teams also have to simulate the production environment as closely as possible as applications perform differently on local machines and during production.
  6. Incorrect architecture evaluation:
    DevOps needs the right architectural support. The idea of DevOps is to reduce the time spent on deploying applications. Even when automated, if deployment takes longer than usual there is no value in the automation. Thus, DevOps teams have to pay close attention to the architecture. Ensure that the architecture is loosely coupled to give developers the freedom and flexibility to deploy parts of the system independently so that the system does not break.
  7. Incorrect incident management:
    Even in the event of an imperfect process, DevOps teams must have robust incident management processes in place. Incident management has to be a proactive and ongoing process. This means that having a documented incident management process is imperative to define incident responses. For example, a total downtime event will have a different response workflow in comparison to a minor latency blip. The failure to do so can lead to missed timelines and avoidable project delays.
  8. Incorrect metrics to measure project success:
    DevOps brings the promise of faster delivery. However, if that acceleration comes at the cost of quality then the DevOps program is a failure. Organizations looking at deploying DevOps thus must use the right metrics to understand progress and project success. Therefore, it is essential to consider metrics that align velocity with throughput success. Focusing on the right metrics is also important to drive intelligent automation decisions.

To drive, develop, and sustain DevOps success, organizations must focus on not just driving collaboration across teams but also on shifting the teams’ mindset culturally. With a learning mindset, failure is leveraged as an opportunity to learn and further evolve the processes to ensure DevOps success.

All you need to know about the AngularJS – ReactJS choice

With a variety of frameworks available in the market, deciding which web application framework to use can become overwhelming. There are a host of factors to consider including the libraries they offer, the database access options, templates, and code reuse. JavaScript frameworks are developing fast, and frameworks like AngularJS and ReactJS have become extremely popular. With over 318,754 unique AngularJS domains and 214,467 ReactJS domains, the choice is not easy. Let’s look at both these frameworks to see what may best suit your needs.
reactjs-vs-angularjs-framework

AngularJS

AngularJS, an open-source JavaScript-based front-end web application framework primarily maintained by Google. It provides a structure for building an application end-to-end: from writing the code and designing the UI to testing. It addresses many of the challenges encountered in developing single-page applications. It simplifies the development and the testing phases and allows for automatic synchronization of models and views for improved testability and performance. Like similar frameworks, AngularJS offers multiple solutions and designs and is used by several organizations such as AWS, YouTube, Google, Nike, PayPal, Upwork etc.
Key Features:

  • AngularJS offers an out-of-the-box MVC framework that automatically combines all the elements, making it easier to build client-side applications.
  • It uses HTML to build the user interface. This is easy to understand and simple to organize and maintain.
  • Being an end-to-end, full-fledged framework, it requires minimal coding and can run on any browser or platform.
  • AngularJS drives context-aware communications. This ensures the right messages are sent to the right nodes at the right time.
  • The dependency injection feature enables one object to supply dependencies to another object. This allows greater flexibility and cleaner code.
  • Custom directives enable assignment of the right attribute to the appropriate elements.

Advantages:

  • The MVVM (Model-view-view-model) allows different developers to work simultaneously on the same sections using the same set of data.
  • Since AngularJS relies on TypeScript, it offers more consistency and enables faster compilation.
  • Detailed documentation enables developers to easily get the information they need.
  • The two-way data binding reduces the impact of minor changes, minimizing the possibility of errors and eliminating the need for additional effort for data sync.
  • Being open-source, AngularJS is constantly updated and improved through contributions from developers everywhere.
  • AngularJS developers and designers constantly collaborate and contribute to the community. The global community support is excellent. This enables quick familiarization with concepts.

Disadvantages:

  • The earlier versions of AngularJS bring with them complex Angular-specific syntax that drives a steep learning curve.
  • The physical DOM is hard to manage and update.
  • Migration issues make it tough to move from an older AngularJS version to a newer one.

What is ReactJS?

ReactJS, an open-source JavaScript-based library primarily maintained by Facebook, offers a robust base for developing single-page web or mobile applications. Being declarative in nature, ReactJS makes the process of creating rich UIs seamless. It ensures the code is predictable and easier to debug. Since it is component-based, it ensures seamless integration of different components written by different people without causing major ripples through the codebase. The ReactJS ecosystem comprises many building blocks and online tools and is used by several organizations such as Instagram, Netflix, WhatsApp, Airbnb, Microsoft, Facebook etc.

Key Features:

  • The Virtual DOM enables developers to focus on writing the JavaScript code without worrying about updating React components or the DOM; when any data changes, the virtual DOM automatically updates the user interface.
  • The component-based architecture makes components easily reusable, enhancing their testability and maintainability.
  • By using JSX to write views, ReactJS enables JavaScript and HTML to operate in a single file.
  • External plugins enable developers to interface ReactJS with other libraries and frameworks.
  • In order to design an app interface, developers can either use nested elements (by including a reference to the child class within the render method of the parent class) or loops (by combining numerous HTML elements into an array).
  • Server-side scripting can be enabled with Node.js. Developers can create dynamic web page content before the page goes to the web browser.

Advantages:

  • The simplicity of syntax makes ReactJS easy to learn.
  • Since ReactJS is universally flexible, the libraries can be paired with all kinds of packages.
  • ReactJS gives developers more control to size an application by selecting only those things that are really necessary offering extreme flexibility and responsiveness.
  • The Virtual DOM makes arranging documents in HTML or XML formats much easier while developing different elements of the web app.
  • Since data flows only in one direction, the result is better data overview and easier debugging.
  • Downward data binding ensures child elements do not affect parent data.
  • Being open-source, ReactJS is constantly updated and improved by contributions from developers everywhere.
  • The presence of codemods ensures a seamless migration from earlier versions to newer versions.

Disadvantages:

  • The absence of systematic documentation and limited guidance makes development tricky and, sometimes, risky.
  • Since ReactJS is not a full-fledged framework, developers require deeper programming knowledge for integrating the UI library into the MVC framework.
  • Developers may take more time to get familiar with ReactJS as each project architecture varies.

Choose the Right Framework:

Clearly, choosing the right framework for your web application has to be a top priority. Since the framework you choose can have a direct bearing on your ability to meet your current requirements and as well as future needs, choosing between AngularJS or ReactJS is an important decision. While AngularJS offers more consistency, is easier to develop and compile, the complex Syntax and physical DOM make development a little tricky. On the other hand, ReactJS offers a shorter learning curve, is flexible, and easier to debug, but, the absence of documentation and the requirement of deeper programming knowledge make it more suited for professional developers. For the experienced developer, there is no substantial difference in the frameworks; but your choice will have to be driven by your business requirement, your web application goals, and your system constraints.

Check back with us if you need any help in picking what’s right!

Are you missing on these latest eCommerce web trends?

Ecommerce has come a long way from the time when a tiny company called Amazon started selling books online. Today predicted sales in the eCommerce industry are expected to cross $27 trillion by the year 2020. The mobile revolution further fueled the eCommerce revolution and today, you always have your favorite store in the palm of your hand. Almost 11% of online shoppers shop online using their smartphones. 35% believe that the mobile will become their preferred purchasing tool. 39% of the shoppers look towards social networks for purchasing inspiration. Clearly, eCommerce is evolving at a rapid pace. With every product imaginable available online and the increasingly mobile nature of the eCommerce customer, just having a good eCommerce website is not good enough anymore. Consumers today expect that online transactions will mimic the engaging and immersive in-store experience, eCommerce companies must make sure that they follow the latest trends to stay their customer’s preferred online shopping destination. Here’s a look at some of the latest eCommerce web trends you cannot afford to ignore.
latest ecommerce web trends

  1. The ‘motion’ experience:
    Motion is making big noise in eCommerce design this year. Subtle animation, some form of movement on the website, to engage the customer will be a UX imperative this year. The idea of introducing motion is to attract the consumer, keep them engaged, and make the online shopping experience more alive. You could, for example, use animated iconography like Etsy uses to notify people when a product is almost sold out. However, as with everything else, minimalism rules here as well. Don’t overdo the motion experience. This could annoy more than improve.
  2. The Social Connect:
    Today, 9 out of 10 people turn to Social Media before they make a buying decision and almost 75% of people purchase something after seeing it on social media. The Shopper Experience Index reveals that shoppers lean heavily on visual content to absorb the experiences and behaviors of others and to discover the products people are using on social channels.
    Social shopping is expected to be one of the biggest eCommerce trends for 2018. This provides retailers with the opportunity to showcase their products on the social applications their consumers spend the most time with. Levis, for example, added the social connect to their eStore and found that almost 30% of the website traffic started coming from Facebook. Adding the social connect to your eCommerce website will become imperative to give today’s shoppers the opportunity to purchase a product without switching between websites or applications.
  3. Shoppable videos:
    We all know that videos are a mainstay in the eCommerce landscape. They play a big role in drawing the crowds to your website. However, 2018 is all geared to be the year of shoppable videos, where the consumer will be able to shop for a product or service directly from the video itself. Shoppable videos reduce the catalog browsing time for the consumers while providing them with the best visual shopping experience. Global retailers, Marks and Spencer’s have given this trend a try already by selling their new denim collection via such videos wherein the customer could pause and purchase the denim at any point directly from the video itself.
  4. The omnichannel transition:
    The customers of today demand a fully integrated and unified shopping experience. The Shoppers Experience Index 2018, thus unsurprisingly shows an accelerating transition among online retailers towards providing customers with an omnichannel experience. Retailers thus need to focus heavily on delivering a high-quality customer experience that is consistent across online and offline channels irrespective of device. This omnichannel approach allows the customer to view the product on any device, ship purchases to stores, have in-store purchases shipped to them, and process returns and exchanges in any store location. With this approach, Online retailers can truly increase their market reach and develop the capability to sell online as well as offline. They can effectively ‘be everywhere’.
  5. Artificial Intelligence is on the rise:
    AI is going to take eCommerce to the next level. eCommerce companies such as Amazon and eBay are already leveraging AI to improve the online shopping experience. Did you know that Amazon’s recommendation engine drives 35% of the company’s sales? In 2018, Use of AI in eCommerce in the form of chatbots and AI assistants, smart logistics for automated warehouse operations, recommendation engines to analyze customer behavior, and in making hyper-personalized product suggestions will see significant growth.
  6. Voice search to become more commonplace:
    Voice search is geared to take off this year as voice assistants such as Google Assistant and Alexa become more commonplace. Research suggests that more than 40% of millennials use a voice search before making a purchase online. Almost 20% of Google searches on mobile are voice-based. With mobile commerce gaining an even stronger foothold (it is estimated that mobile commerce will cross $600 million in 2018), optimizing the online store for voice search becomes imperative this year.

Finally, eCommerce websites have to become more performance-focused this year (like the years that went by!). Jem Young, of Netflix, said, “Beyond frameworks, beyond libraries, beyond the latest design trends, it’s performance that ultimately matters the most…For eCommerce businesses especially, where the difference of 200 milliseconds can mean the difference between gaining a customer or losing them to a competitor, keeping your site performance is crucial in order to stay competitive in 2018.”
How many of these eCommerce trends is your company following? How have they worked out for you?
Do share your experiences with us.

5 Technologies that are the Building Blocks of Digital Transformation

Organizations are in the quest to accelerate business activities and offer an exceptional product and customer experiences by driving digital transformation. With 57% of organizations believing that digital transformation is a competitive opportunity, it is without the doubt that technology is enabling organizations to become more agile, responsive, innovative, and efficient in addressing their needs.

The Building Blocks of Digital Transformation

In a highly dynamic and competitive world, having an amorphous digital transformation goal is not enough; what is required is an understanding of the tools and technologies that can enable you to get there. Digital transformation spending is expected to reach $1.7 trillion by the end of 2019. Clearly, leveraging modern technology to significantly drive transformation has become a mandate for organizations around the world. However, only 10 percent of companies around the world describe themselves as fully digital – a significant gap. One of the challenges is the vastness of the scope. Where to start? What technologies will play a role? The questions are many.

Since markets, customer demands, and technology is changing rapidly, leading digital change requires you to embrace modern technologies. This will allow you to evolve with the rapid pace of digital change. Here are 5 technologies that are the building blocks of digital transformation:

  1. Cloud:
    For digital transformation to have a profound impact on business activities, the cloud must play an important role. The cloud offers digital organizations the flexibility to do business from anywhere, freeing them from the hassle of investing in and managing physical IT resources. It offers businesses the scale and speed needed to become agile and focus on continuous transformation. The cloud enables organizations to fuel better collaboration and constantly develop, deploy, deliver, innovate, and implement modern solutions. By offering flexible, on-demand access to resources, the cloud enables organizations to execute plans faster and address the changing needs of the market. With the cloud computing market projected to reach $162 billion in 2020, it is past the time for businesses everywhere to embrace cloud solutions to drive digital transformation.
  2. Mobility:
    A key pillar of digital transformation in today’s fast-paced world is mobility. Digital transformation involves radical reconsideration of how organizations use technology to build new revenue streams or business models. Mobility enables them to do that and achieve a host of benefits: anytime anywhere access to information, improved productivity, better process efficiency, lower operational cost, and an enhanced customer experience. Since mobile technology bridges the gap between the physical and digital world, it helps organizations make use of the right data in the right context at the right time and at the right place. It also fuels better communication and collaboration within the organization – helping organizations make more informed decisions, be more proactive, and engage with their customers and employees better. With 82% of organizations believing mobile is the face of digital transformation, the role that it plays is now self-evident.
  3. Big Data and Analytics:
    In today’s digital economy, organizations need to embrace technology not just to support existing business processes, but also to drive new avenues of competitive differentiation. Big data and analytics are driving organizations to analyze humongous amounts of data and unearth critical insights. They are examining business processes, customer behavior, market trends, and competition data and creating value. Since today’s digital customers are a major catalyst for digital transformation, harnessing the right data helps organizations to understand customer needs, make data-driven decisions, build products and processes to meet those needs, and shape the right experiences for them. As big data and analytics enable organizations to get answers to critical questions in near real-time, it allows businesses to react quickly to change, improve performance, and build competitive advantage.
  4. IoT:
    The Internet of Things is driving substantial transformation across industries by linking critical assets in a connected ecosystem. The data generated from these systems can be used to drive sufficient business value, potentially transforming operations and improving business efficiency. Gartner predicts that 1 million new IoT devices will be sold every hour and that IoT spending will reach $2.5 million per minute by 2021. Using IoT, organizations can extend their enterprise and make the most of the exciting business opportunities for transformative business growth. IoT can help drive industrial automation, derive insights into equipment data, enable predictive maintenance, and improve the safety of the workforce. What’s more, IoT data can also be used to boost efficiency, improve customer experiences, and increase overall business agility.
  5. AI:
    In a bid to drive transformation, organizations across the world are looking at ways of applying Artificial Intelligence to boost their business outcomes. AI is already a key driver of digital transformation across a wide range of sectors. Nearly 9 in 10 businesses believe that AI will serve as a key competitive advantage, and help them explore new opportunities and revenue streams. AI can drive significant automation in the enterprise. It enables organizations to apply a more agile framework for digital transformation and create repeatable, reliable functions that can be used widely. By understanding customer journeys and the outcome of future interactions with customers, AI can also be used to drive personalization in customer engagement – a key expectation of the modern digital customer.

Technology at the Core

The pace at which the world is moving is compelling organizations to embrace modern and innovative technologies. The aim is to become extremely agile, to quickly respond to market changes, and to address customer needs. Digital transformation requires you to leverage the available technology to enhance your business process efficiency and become more competitive. Modern technology advancements such as cloud, mobility, big data and analytics, IoT, and AI, offer a variety of potential business benefits. Picking an area of impact to your business and applying the right technology mix will help you take the first successful step towards digital transformation.

5 Changes Your Startup Must Make To Succeed With Offshore Product Development

Offshore product development is now quite common in the technology world. Some of the most successful startups such as Basecamp, GitHub, and MySQL are good examples of startups that successfully outsourced their product development and yet were massively successful.

It’s fair to say that outsourcing is only going to increase because of the cost and business benefits it brings to organizations and especially to startups. Highlighting this trend, the IT Outsourcing Report stated that nearly 40% of companies that outsourced application development planned to increase the volume of work they outsourced. The report also stated that 53% of companies with a mobile app outsourced their development initiatives. When it comes to startups, outsourcing had its own set of advantages other than just cost. Since startups are usually resource and time constrained, outsourcing product development makes abundant sense. Outsourcing gives startups the bandwidth to focus on the business aspect without having to worry about the many complexities of product development.

That said, outsourcing product development is anything but a simple process. Both the startup and the offshore product development team need to iron out certain processes to ensure that product development happens effortlessly, and the end result is superlative. Here are some suggestions on how to make this work.

  1. Treat the Offshoring Team As Your Extended Team:
    Your offshore product development team is an extension of your internal team. They thus should be treated with the same amount of trust that you would show your local team. Startups must trust that the outsourcing vendor will work with a commitment to ensure that they develop a product that is successful.
    In our experience when a startup treats their outsourcing vendor and the team as their partner they work harder for you and empathize more. The fact is, you hire an outsourcing team for the experience and expertise they bring to the table. So, treat them as a part of your internal team to get the most out of that portfolio. Trust their insights and get them more involved by embedding them into your development process.
  2. Leverage Them As Your Technology Partners:
    Your offshore team gives you open access to strong technology experts. Sometimes this might lead to a clash of views. Such clashes often happen when the technology expert feels that a particular technology is more suitable for a project and the startup feels otherwise. In such a situation, it is advisable to have an open discussion like you would have with your internal team member.
    Let us speak on behalf of the offshore product development vendor for a minute. Given that these experts have their finger on the pulse of the tech ecosystem beyond just your product, their opinion will usually not be driven by technology bias. It will generally stem more from a desire to leverage the technology that will help in developing a better, feature-rich and more robust product.
  3. Integrate – Make Them a Part of the Big Picture:
    Would your internal team be able to function if you don’t give them an idea of the big picture…of where your startup is heading? It’s no longer the case that offshore product development teams work best only when managing certain non-core activities in isolation. If you want your startup to succeed, you must ensure that all invested stakeholders have a clear idea of your company vision and mission -and this includes the offshore team.
    Help the offshore team understand not only the problems the product is trying to solve but also where the company wants to go in the long run. When you share your vision with the offshore team you give them the context in which they can innovate on your behalf. They can then help you come up with ideas to make the product better, how to extend the product, how to plan for an accelerated product development roadmap and come up with a product evolution plan.
  4. Establish Clear Criteria For Success:
    You can only manage what you can measure. The same is true for startups working with offshore product development teams as well. Adopting an agile approach even in communication is key. Clear expectation setting helps in establishing clear criteria for success.
    To establish measurable and clearly accountable goals, have reasonable delivery timelines, have regular check-ins at a mutually convenient time, have a defined process of engagement that ensures that all deliverables are transferred in the appropriate format. It is most important to agree upfront on the parameters that define success to establish the performance of the offshore team.
  5. Great Communication is Critical For Success:
    Great communication leads to successful partnerships. When it comes to an offshore product development team, communication can sometimes prove to be the Achilles heel. Startups, thus need to ensure that there is an environment that fosters effective communication between the offshore and local teams. This means leveraging all available tools like emails, messenger, and chat for communication and clarifications. This will involve the use of appropriate productivity tools for proper project management.

    This is essential to eliminate misunderstandings based on assumptions. Ensure that your outsourcing partner offers a model for business engagement that helps you get clarifications in case the outsourced team is in a different time zone. Regular check-ins also play an important role in establishing clear communication channels. This approach is more structured and ensures that everyone’s time is used optimally and that no information falls through communication gaps.

A change in mindset is essential to succeed while outsourcing product development to offshore teams for a startup. Once you see this team as an extension of your own company then ironing out issues that emerge during any product development lifecycle become easy. Remember that at the end of the day, “Individually we are a drop but together we are an ocean”. It’s time to dive in!