The current pandemic has finally given the push to make the whole world go online. The businesses and individuals who were resistant to change over the past years also have no other choice but to go digital due to erratic lockdowns and social distancing requirements. Either reluctantly, or with open arms, people from all stages of life are coming online from various devices for not only performing office-related work, but everyday tasks like ordering products or services, payments and banking, education, collaboration, entertainment, and a lot more. In fact, the digital transformation that has happened in the past few months due to the impact of COVID-19 is more than what we have seen in the past decade. According to a study by Mojo Vision, “50% respondents said the onset of COVID-19 caused them to use or depend more on devices, apps and services. Moreover, they feel that they would continue to do so in future too.” At a time when digitization is growing by leaps and bounds, there is a demand for applications that perform well and meet the specific needs of the users.
The role of performance engineering to ensure the best customer experience in the digital era
Continuous Quality Engineering is a vital part of the product development lifecycle and IT businesses are leaving no stone unturned to excel in the field of performance engineering. Quality engineers and application developers are working hard to ensure that their solutions perform perfectly under all kinds of loads, usage scenarios, platforms, browsers, bandwidths, and much more. They have to make sure that the source code is optimized, the integrations with third-party apps and back-end connections with data centers work seamlessly, hosting and servers are load-balanced, security is maintained without compromising the speed, and the overall application is managed in the best possible way throughout its lifecycle. All these efforts lead to a superior quality application that works well under all situations and satisfies the customers. But guess what? That is not enough.
What comes next when all the systems are already optimized?
All the good software application development companies have already reached a stage where they use the best practices and standards for development and deploy all quality engineering essentials to take the performance to the highest level with the resources they have. But how to further enhance the performance when all the systems are running at their best? How to create a distinctive competitive advantage by offering users even more. This can be done by leveraging predictive analytics with performance engineering to enhance user experience and perception.
The next level: Leveraging predictive user behavior analysis for dynamic and personalized applications
As humans, we are always inclined to visit places or people who bring us a feeling of safety and comfort. We like the company of friends who have taken the time to understand us or family members who know our little quirky likes and dislikes and go the extra mile to delight us. Don’t we want to go to such friends and places again and again? Performance engineering now has to tread the path of creating such personalized user experiences that can entice similar feelings of comfort so that it becomes a habit for the user to choose your application over the others.
This can be done through personalization of the user interface based on behavior, prioritization of the valuable information that the user might need, and ensuring context sensitivity. Google, Spotify, and Netflix have used these techniques to create that sense of personalized comfort and reliability that users do not want to switch to other providers.
Performance engineers are creating a better perception of performance through:
- Enhanced perception of speed so that users can reach the right information faster: There are times when the application code, backend, and integrations are completely optimized and not much can be done to improve the speed further. But we can still create an enhanced perception of speed by enabling users to reach the desired information faster. By analyzing past behavior data like devices used, location, pages visited, bounces, categories liked/purchased/viewed, session time and length, exits, and user flow, we can predict what the future interaction of the user might be like. This can help in creating a dynamic and personalized interface that gives users what they might be looking for in a fewer number of clicks and consequently a lesser amount of time.
For instance, you go to your favorite food ordering site and you get the right options and buttons based on what you like to eat at that particular time and day, your dietary needs, caloric requirements, and the matching coupon codes for discounts from your favorite restaurants. You would not need to do the extra searching for the right outlets and discounts and would order faster. It will minimize the cognitive load on the users, as they will have to make fewer decisions and hence there would be a lesser chance of them exiting too soon.
- Seamless interconnections across platforms:
Today users are not restricted to one common device shared with others. They move from mobile to computer to a tablet. Or they might go to different locations, for instance, office or home or to a friend’s place and login to the same account from different devices. They might visit your desktop website and then shift to the mobile website or the app, or an in-store POS. As we can see, there are ample choices for the users to interact with your business and they demand a frictionless experience at all the touchpoints. The performance engineers have to ensure that the experience should remain smooth, consistent, and seamless, without any loss of quality.
According to Forrester, “A well-designed user interface could raise the website’s conversion rate by up to a 200%, and a better UX design could yield conversion rates up to 400%.”
- Intuitive applications that respond to customer behavior with predictive recommendations:
Today, in the cut-throat competitive environment, companies must leverage their data banks for predicting user behavior and creating more opportunities. Predictive modeling can be used to analyze this data and recommend items.
Predictive and intuitive designs can be used in many ways. For instance, e-commerce giants always give recommendations to you for the products you might like based on past purchases. The banking sector uses predictive analysis to detect frauds. Netflix uses analytics to give the users the perfect recommendations based on their engagement data so that they can find the right content faster from an endless pool of entertainment. An education and learning website gives out tests based on the skill level of the learner and slowly increases or reduces the difficultly to enhance the experience and learning during each visit. All these are examples of predictive analytics to improve performance and take the user experience to the next level.
Conclusion: Extreme performance engineering will define the next generation applications
Personalization is the key that will unlock the way to an enhanced user experience and technologies like predictive analytics will take them to another level. Application developers will leverage the power of extreme performance engineering to create dynamic apps that sense, respond, learn, and forecast what choices would the users make in the future and transform according to those predictions in the next interaction. The application would prescribe the next steps to the users and in doing so, will reduce their time to information and delight them with completely personalized experiences.