E-commerce feedback widget. Case Study

  1. Most eCommerce stores aim at rapid growth. They can reach the goal either by growing their market share, or expanding their store size, or just gaining larger profit margins. But what if an e-commerce business would have a personalized approach that can be applied to all commerce user segments?
  2. We designed the critical approach on how to reach the e-commerce clients’ needs through base marketing channels and shifting our value proposition to them. The main idea was to create an online store widget that allows users to get feedback from market influences, bloggers, opinion leaders, and design the managing sales dashboard.
  3. Moving on to our essential design process, we have done the base steps which can resolve the main e-commerce issues.
  4. Initially, we designed the Lean business model canvas, which allowed to understand the core business needs and define the main business marketing activities:

Job-To-Be-Done canvas

After defining the core of user hypotheses we did a couple of quantity user researchers. It helps us to obtain plenty of jobs that we packed on “Jobs to be done” canvases. These canvases are intended to be a starting point to develop a hypothesis about a market of interest that can later be refined and validated through a more rigorous execution of the ODI process.

  1. What group of customers to target for growth?
  2. What job the customer is trying to get done?
  3. Associated consumption, related and emotional jobs.
  4. What are the customer’s desired outcomes (needs) associated with getting the core and consumption jobs done?

Customer journey mapping

After successively analyzing and validating Jobs To Be Done approaches we go to customer journey mapping that helps us to define a kind of high-level overview you need to target customers with the content and touchpoints that will move them down your sales funnel.

  1. No shopping activity — 56%. It showed that there are problems with Product cards that must be resolved.
  2. Cart abandonment rate — 89.8%. It is a critical issue that might be caused by payment problems or broken user flow.
  3. Check-Out abandonment — 93%. This issue appeared when users were on the credit card adding process. This problem also needs to be evaluated and fixed by improved user flow and a series of customer journey mapping.

Implement Improvements

Once our map is complete, and we take all the insights and ideas, we start fixing all the weak spots you discovered and start drawing the first low fidelity prototypes. Sometimes it seemed quite vague and we were afraid that our crucial improvements would not reach a practical realization. But we continued to make efforts until we got an affordable result:



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