Retailers manage pricing through B2B software analytics that uses historical data to suggest new data as well as predictive analytics. The generated content these analytics tools produce is what people in the company need in order to analyze and develop, and execute pricing strategies.
Research, Discovery, User Interviews, UX Design, Mentoring
Retail Pricing | Web Application | B2B
In this case study I have omitted confidential information to comply with my non-disclosure agreement. The information in this project is my own and does not necessarily reflect views or plans of Walmart.
two work streams
I designed, planned and executed a four-week discovery research to help with:
A. Learn about existing pricing software and B. validate design concepts through research finding.
Guidance & Mentorship
I learned, gathered, and analyzed information about company pricing tools, deeply familiarized myself with the daily UX challenges both UXer’s and BO’s owners deal with in order to build a strong foundation for UX recommendation
A four-week discovery research to help with: A. Learn about existing pricing software and B validate design concepts through research finding.
• Interviewing 8 users (Sr. Managers, Planners and Buyers)
• Designing discovery questions to learn about behaviors and attitudes around the existing analytics tools
• Two separate designs to gain better insight through A/B
• Gathering and analyzing discovery finding about participants experience
• Providing UX recommendation based on research finding
The study aimed to answer the following questions:
How do users currently describe their process in the software? What are the biggest pain points?
What are the key business outcomes that you use the software to accomplish?
How much time do you currently spend on an average in creating, evaluating and approving pricing plan?
When shown one wireframe for how new pricing works, what do they like about it? what would they improve?
Do they currently look or expect to see different data than the previous solution?
Accuracy of projections
Participants said overall existing pricing tool is a straightforward system to use and it's the least painful application from an ease of use perspective.
However, they indicated that often the system provides them predictions that seem inaccurate which causes them to run numbers and calculations manually using excel sheets and because of that they prefer not rely on the
Meaningful data and how it’s displayed
1. Participants indicated 3 data points they found are most useful to perform their job, and indicated others as “less important”.
2. Most participants preferred to have data presented side by side
3. Most participants said that 9 out of 10 times they would take action on the pricing plan level information and wouldn't dive in to see more details
4. Few participants thought having status on the pricing plan is helpful