Measuring What Matters: A Hypothesis-First Approach to Faster, More Confident Decisions

In any customer-facing business, a top priority is a smooth customer experience. To ensure that there are no bumps standing in the way of a satisfied consumer, many retail organizations collect metrics intended to identify process hiccups and address gaps. But what happens when an organization becomes so large that they are drowning in too much data to even identify the source of their process problems, much less develop solutions?

APQC’s Madison Lundquist (Principal Research Lead, PPM) recently spoke to Abhinav Sonker, a senior product manager responsible for improving the customer-facing digital experiences of a large-scale retailer. He shared the company’s approach to untangling an overabundance of data in order to provide clarity in improving the repeat purchase cycle for existing customers. 

This interview provides a paraphrased summary of Sonker’s and Lundquist’s discussion about the retailer’s “hypothesis-first” journey to a smoother buying experience, including:

• Challenges inherent in choosing the right metrics, particularly for a large organization 
• Why the hypothesis-first approach helped solve these challenges, leading to a better customer experience and more internal clarity
• Obstacles Sonker’s team overcame while implementing the new measures
• Advice for organizations looking to improve their own performance measures