This feels like a straightforward question but somehow I am struggling with it.
Here's how I am framing it in my head:
I understand the problem or business case, I align with stakeholders on what their problem areas are and bring forth their perspective to help solve the business case using data. The data is focused around the main drivers to solve the business case. For example: working with sales leadership and product to drive a new rewards construct for an application requires data to substantiate the correct 'inventory.' The data points to the business case, which in this case also involves having sufficient coverage and 'sticky' rewards merchants. The data shows which merchants would be a good fit and are stickiest based on my analysis and hence it speaks for itself. Example KPIs that I analyze are RPU, store sessions, number of offers live, whether there is an affiliate program for the brand, and how many distinct consumers are both engaging with the brand. Nothing fancy.
I summarize the findings starting with the key take-away first. E.g. out of the 30K merchants I analyzed, I found these 15 merchants to be a good fit due to their RPU, distinct users per month, and repeat purchase behavior by users. The data speaks for itself but I also customize the delivery in such a way that it solves the leadership business case. In this case, what merchants should we run a rewards pilot with.
What is my answer missing? How can I make it better? Or am I overthinking it lol
