![\"Feature](\"https:\/\/static.wingify.com\/gcp\/uploads\/sites\/3\/2025\/05\/Feature-image-Best-Testing-Teams-Arent-Just-Data-Driven\u2014Theyre-Empathy-Led.jpg\")
<\/figure>\n<\/div>\n\n\nLeader:<\/strong> Sunita Verma<\/p>\n\n\n\n Role:<\/strong> Experimentation Specialist<\/p>\n\n\n\n Location:<\/strong> Singapore<\/p>\n\n\n\n Speaks about: <\/strong>Growth experimentation \u2022 Product testing \u2022 Cross-market insights \u2022 Personalization \u2022 Empathy-driven CRO<\/p>\n\n\n\n With a track record of driving experimentation at major commerce companies like H&M, FairPrice Group, and Zalora, Sunita Verma brings a rare blend of analytical rigor and human-centered thinking. Her work spans product growth, regional testing, and cross-functional collaboration across Asia. She\u2019s helped teams shift mindsets, build experimentation culture from the ground up, and embed empathy into every stage of testing.<\/p>\n\n\n\n If you\u2019re looking to scale CRO across diverse markets or wondering how to build stakeholder trust in a data-driven world, this interview is for you.<\/p>\n\n\n\n Disclaimer: All of the content below reflects Sunita’s personal thoughts, opinions, and beliefs, and does not necessarily reflect those of any companies she is or has been associated with<\/em>.<\/p>\n\n\n\n As per Maslow\u2019s hierarchy of needs, people will only start considering higher forms of thinking and needs once more basic needs have been met. We see young shoppers today are increasingly looking for responsible companies instead of ones that are able to give them the best value-for –money. This contrasts with trends we see in Gen X and Y shoppers who tend to rank price, value-for-money as top considerations for purchase.<\/p>\n\n\n\n This behavior presumably emerges as a result of the rapid rise in standard of living of the last few decades in several parts of Asia. For organizations, it becomes important to assess when the market\u2019s population will start seeking higher-level needs\u2014aligned with the market\u2019s development\u2014while planning to capture a new generation of consumers.<\/p>\n\n\n\n The higher levels of thinking and consideration in the younger generation is impressive. However, the rate at which this is becoming more widespread differs significantly from one Asian country to another (seemingly related to the standard of living within the country).<\/em><\/p>\n<\/blockquote>\n\n\n\n I typically try to evaluate an idea based on the below factors:<\/p>\n\n\n\n How did this idea come about, and what sort of data or knowledge is backing it?<\/p>\n\n\n\n To maximize the existing data and knowledge that we have (without testing) to understand how confident we can be in the idea.<\/p>\n\n\n\n We\u2019re looking to prevent the testing of ideas that are solely based on gut-feel (across my career so far, this request is usually one that is cascaded down from a HiPPO). <\/p>\n\n\n\n Will this idea make a big difference to user behavior or perception?<\/p>\n\n\n\n Once we know that the idea in itself comes from sound-reasoning, we\u2019ll need to understand its chance in making enough of a difference to users such that the test has a good chance of being statistically significant. This is where the testing team would need to do some homework to understand the traffic, conversion, potential impact, and thus the minimum detectable effect (MDE). Stakeholders are not brought into this technical process but conversations with stakeholders will allow the team to understand the possible impact the idea might bring about.<\/p>\n\n\n\n However, if the test idea does not have a good statistical chance, our next step would be to understand if there are reasonable ways to change the test design (e.g. bolder variations, longer test durations, location of test, markets tested)<\/p>\n\n\n\n As you can see, this is a very RICE approach to prioritization and is a fairly popular tool in several prioritization frameworks across organizations.<\/p>\n\n\n\n It is important to engage stakeholders from the start. They need to feel responsible for the purpose of the test, as it should align with their goals and support their objectives. This has to be established right from the start to garner greater trust.<\/p>\n\n\n\n All the technical bits and calculations in the process do not need to be fully walked through to the stakeholders involved but a high-level overview is important for them to understand our outlook on a certain test. This reduces the need to get into lengthy explanations of the different parameters in testing and instead streamlines the conversation to the broad important concept to the layman and thus why we\u2019re suggesting some changes to ideas or suggesting for some ideas to be reviewed\/considered for another time. <\/p>\n\n\n\n First off, be excited and curious about WHY. As excited as when you would see a positive result in a test. To me, it is critical to ensure you\u2019re in that mindset to make sure you\u2019re not bringing any biases when looking further into the results. If you feel nervous or anxious due to the results, then there are bigger issues than the results\u2014there will need to be a mindset correction in the organization of what testing and learning are about.<\/p>\n\n\n\n Now, when we\u2019re in the right mindset, try to dive further into the results to understand what is causing the results. This is highly dependent on what the test was about. Are different segments of users performing differently? Are there specific steps in the journey where users have fumbled?<\/p>\n\n\n\n Once all of the insights have been gathered to paint a fuller picture of why our customers are reacting in this way. It is time to share the results with the key stakeholders. I usually like to set the tone by making sure stakeholders understand that this has been a very valuable test as it has learnings that went against our judgments that could turn into actionable insights. <\/p>\n\n\n\n It is important to ensure that stakeholders view the results in a productive way instead of being discouraged. From there, it would be easier to discuss how we can utilize these learnings to potentially tweak the idea or drop the idea completely or even retarget the test to specific groups of users.<\/em><\/p>\n<\/blockquote>\n\n\n\n We would not have any tailoring or personalizations until we build a knowledge base of what works and what does not. While there are several beliefs and stereotypes about each market and how their population behaves\u2014this might vary significantly from brand to brand within the same market. <\/p>\n\n\n\n As an example, in certain markets like Vietnam, it is no secret that it is relatively more deal-driven than the other Asia markets listed, and we start to understand how ideas tested start showing different results for this market compared to others. This gives us the ability to log this knowledge down in the testing library so that we can better design future tests.<\/p>\n\n\n A unique experience from a competitor in the market does not mean that we should hop on to a similar strategy because it aligns with their (not our) shoppers\u2019 preferences. We\u2019ll have to remind ourselves that our shoppers are unique and while we can borrow the thoughts of general behaviors and preferences of the market, this will need to be tested before it is acted upon. Hence, this might take several rounds of testing.<\/em><\/p>\n<\/blockquote>\n\n\n\n Customer metrics are extremely important\u2014from the bottom of the funnel (e.g., NPS) to top of funnel (brand awareness, brand consideration). These metrics should not be success metrics for experiments, as they are long-term metrics. <\/p>\n\n\n\n However, it is important that organizations pay heavy attention to them (possibly even more than profit) as the customer sentiment will reveal where course correction needs to happen for the business to continue thriving in the next few years.<\/p>\n\n\n\n I\u2019ve not particularly found a specific metric that is a holy grail for experiments\u2014the metrics highly depend on the test idea and parameters. What I do find to be of utmost importance, though, are guardrail metrics. Even just going through the process of thinking of the appropriate guardrail metrics for a test is a great exercise in and of itself to ensure we\u2019re not trying to generate rosy test results but that we\u2019re trying to understand the user behavior.<\/p>\n\n\n\n To pick the right guardrail metrics, it\u2019s important to play the devil\u2019s advocate.<\/p>\n\n\n\n For example, say the team has a great idea: testing a \u2018Similar Product\u2019 recommender on the product page to give users more options. The goal is to increase the likelihood that users come across something they\u2019d like.<\/p>\n\n\n\n Now, it becomes our role to think about how this change might create a negative impact.<\/p>\n\n\n\n A potential guardrail for this test could be the cart-out rate or the number of days between adding to cart and checking out.<\/p>\n\n\n\n This helps us understand if giving users more choice upfront\u2014via the similar product recommender\u2014introduces the paradox of choice. In other words, whether too many options cause delayed decisions or, in some cases, complete abandonment.<\/p>\n\n\n\n The core experimentation team will typically have a checklist of items that needs to be ticked in order for us to green-light the design of a test, and another checklist for test analysis. However, that\u2019s the easy bit\u2014there are many checklists out there shared by several CRO professionals that are very valid and comprehensive.<\/p>\n\n\n\n To ensure that the team is able to follow the checklists, it is vital that the experimentation team is treated as a \u2018center of excellence\u2019 in end-to-end testing (from design to analysis). Laying the groundwork for setting up the above environment is something that usually starts even before the organization\u2019s first CRO team is hired.<\/p>\n\n\n We do typically manage expectations from the get-go with business stakeholders that the analysis period for a test will be 2 weeks, which gives sufficient time for the team to ensure that all checks and deeper dive analysis are completed without the interference of business stakeholders peeking at the results in the process. In this way, we\u2019re able to then prepare a more nuanced results slide that allows us to ensure that the narrative of the final learnings shared closely aligns with our findings.<\/p>\n\n\n\n Learning is a key thing that I try to keep in mind when framing results (especially for tests with exciting results). It is important that the results sharing session re-centers stakeholders on the purpose of the test, what we have learned about our users, and how we can expand on this learning rather than being overly focused on a single metric\u2019s percentage increase.<\/em><\/p>\n<\/blockquote>\n\n\n\n It is definitely a much newer, up-and-coming area in Asia while other markets like Europe are much more mature in the concept. The receptiveness to it is really fully dependent on how the leaders in the organization view it and also what the employees are used to. <\/p>\n\n\n\n I am lucky enough that most folks I have come across are extremely receptive to it as there is already a top-down organizational communication in a continual, consistent manner that this will be the way forward.<\/p>\n\n\n\n However, there are definitely groups of people where much more work is needed on gaining receptiveness\u2014and so far this has been with those who are used to functioning in the same way for the last decade or two. <\/p>\n\n\n This is very understandable as well and I can only imagine the fear for their roles when something like this is introduced. Hence, working with empathy again becomes key. This is not to say that these groups of people only exist in certain markets. They exist in every market as it is not market-dependent but rather organization and department-dependent.<\/p>\n\n\n\n Set a specific goal for any web page, and VWO Copilot will generate relevant testing ideas tailored to it. Then, seamlessly move forward with variation designs\u2014created automatically with just a few prompts, without relying on design bandwidth. <\/p><\/div><\/div><\/div><\/div>\n\n\n\n I have alluded to this in my presentation at the APAC Experimentation Summit last year\u2014empathy and relationship-building is a huge determinant of success in this role. Experimentation in general is treated as a cold topic with the main bulk of it being focused on calculations and designing scientific approaches\u2014at least that was my own mindset when I first ventured into it.<\/p>\n\n\n\n However, over the years, I\u2019ve come to realize that the main portion of my time is spent on people and building trust. Breaking down complex concepts to simpler ones; building relationships and trust that works to ease the acceptance of what I have to say; encouraging teams to think further outside the box without coming off as pushy; being understanding of the limitations that teams are working with and encouraging positive thinking of finding workarounds; recognizing the good work that others are putting in and ideating to help them grow toward their goal\u2014the list goes on.<\/p>\n\n\n\nWhy should you read the interview?<\/strong> <\/h2>\n\n\n\n
What do shoppers value today?<\/strong><\/h2>\n\n\n\n
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How to prioritize which ideas to test<\/strong><\/h2>\n\n\n\n
Confidence: <\/strong><\/h3>\n\n\n\n
Impact and reach:<\/strong><\/h3>\n\n\n\n
![\"Key](\"https:\/\/static.wingify.com\/gcp\/uploads\/sites\/3\/2025\/05\/Key-factors-for-evaluating-test-ideas-1.jpg\")
<\/figure>\n\n\n\nMaking sense of unexpected experiment outcomes<\/strong><\/h2>\n\n\n\n
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Designing experiments for local market behaviors<\/strong><\/h2>\n\n\n\n
![\"What's](\"https:\/\/static.wingify.com\/gcp\/uploads\/sites\/3\/2025\/05\/Whats-your-strategy-pick_-1.jpg\")
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Which metrics matter most in experiments<\/strong><\/h2>\n\n\n\n
Keeping testing rigor in a fast-paced culture<\/strong><\/h2>\n\n\n\n
![\"Building](\"https:\/\/static.wingify.com\/gcp\/uploads\/sites\/3\/2025\/05\/Building-trust-and-securing-stakeholder-buy-in.jpg\")
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How CRO culture varies across Asia<\/strong><\/h2>\n\n\n\n
![\"Cro](\"https:\/\/static.wingify.com\/gcp\/uploads\/sites\/3\/2025\/05\/CRO-Maturity-Timeline-by-Region-1.jpg\")
<\/figure>\n<\/div>\n\n\nWhere AI can help CRO teams most<\/strong><\/h2>\n\n\n\n
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Sunita\u2019s bold beliefs behind big wins<\/strong><\/h2>\n\n\n\n