Case Study: The Cost of Not Listening to Your Customers
A case study on how one company suffered five straight quarters or revenue decline as a result of not listening to customers and data.
written by: Laura Nagy & Ben Sievert
edited by: Ron Dawson
A case study on how one company suffered five straight quarters or revenue decline as a result of not listening to customers and data.
written by: Laura Nagy & Ben Sievert
edited by: Ron Dawson
New Coke, Qwikster, Apple Newton, Microsoft Bob, and Mircrosoft Bob—what do these all have in common? They're all epic product failures that remind us why you should never cover your ears when your customers are talking or stop paying attention to who your customers are.
Most companies strive to strike the perfect balance of monetizing their products and services while also giving customers a stand-out, high-quality user experience thereby creating brand loyalty. Achieving that “perfect balance” however, is not an easy feat, and far too often when a grand idea grips hold of the CEO or senior leaders, it is difficult to change hearts and minds to course correct. In this article we examine how one business was unable to strike this equilibrium because they didn’t 1) put the customer first and 2) started listening too late when the train had already left the station.
We partnered with a company, let’s call it “PantryEssentials” (the real name of the company has been hidden for privacy purposes) that catered to the home cook and specialized in sending customers subscription boxes of the latest kitchen gadgets, spices from across the globe, recipe/cook books, canned goods, small batch/boutique products, etc. Customers paid a flat monthly fee and were able to select products of their choice online up to a certain dollar amount. Although this subscription model was generally profitable, PantryEssentials wanted to make more revenue and build something even easier for their customers to use. PantryEssentials made two fundamental shifts:
What actually ended up happening was an increase in confusion, more questions from customers, and a perceived decline in value of the subscription box, driven by:
PantryEssentials assumed that customers’ number one pain point was “decision fatigue” as there are so many food brands and product options to choose from on a day-to-day basis. Because of the matching algorithm PantryEssentials rolled out, dissatisfaction increased. The top complaints about the boxes became, “This isn’t what I want or would have selected” and, “Your selections don’t align with my cooking values, needs, or desires.” Sure, decision fatigue is a pain point customers have, but customers were coming to PantryEssentials because of the variety of unique, global products and the ability to select products for themselves based on their own preferences and lifestyles.
PantryEssentials conducted tests where a beta version of this new model was exposed to a few top customers who were asked what they liked or didn’t like about the user experience and the perceived value of the new pricing model. This is best practice and a step we would recommend to all customers designing a new product or iterating on an existing version. However in the case of PantryEssentials, while customers conceptually liked the product matching algorithm, they were confused by the complicated credit system and didn’t think the user experience design was compelling or practical enough to shift away from a process that had already been working.
PantryEssentials however, chose to listen to what they wanted to hear, and it became the classic case of “we know what the customers want better than they do” and as the age-old saying goes, don’t fit a square peg into a round hole - if the data isn’t telling you the story you want, don’t enhance or force the lesser storyline to fit an agenda that could be costly.
One of the most problematic issues with PantryEssentials rolling this new structure out was that the complicated algorithm on the back-end didn’t fully work. The haste to move to the new pricing model and the hype of being in the game of “AI” overrode the quality of the actual user experience. PantryEssentials did not ensure that the algorithm was properly trained and failed to do extensive testing in order to see if the algorithm recommendations were matching customers' basic, practical needs before they went live. While a product doesn’t need to be 100% perfect when it’s rolled out, it should achieve the basic goals you attend to.
PantryEssentials did not come up with a powerful enough marketing and branding campaign that would excite and delight customers to adopt and want to invest in these changes. Instead messaging was opaque and created confusion, skepticism, and a feeling of “you’re ripping me off.”
The cost of churn or losing customers and winning new ones is high, and PantryEssentials found this out the hard way. The implementation of the confusing new pricing model and faulty matching algorithm, resulted in five consecutive quarters of revenue decline, costing PantryEssentials dearly. While there are always negative signals in launching a new product, it is imperative to investigate the drivers of these signals deeper and to genuinely listen, internalize, and operationalize customer feedback within major product changes. PantryEssentials leadership became singularly focused on increasing revenue along with the perception of needing to get into the AI race, and ignored the canary in the coal mine during initial beta testing shifting away from customer centric design and strategic thinking.
Laura NagyLaura is passionate about bringing the voice of the customer to the design process of products and services through building listening strategies from the ground up and engaging with customers face-to-face through qualitative research methods. With over seven years of experience, Laura has worked as an internal consultant in tech, partnering with product, marketing and UX teams to ensure customer-centric best practices and empathy are at the heart of design.
Ben is passionate about driving and incorporating actionable insights into the design of products and services. With over seven years of experience in internal and external consulting, Ben has a background in survey development and advanced analytical methods, which help him uncover deep-rooted insights into customer behavior that impact the long-term future success of products and services.
AuraB Solutions specializes in crafting tailored market and product research by putting the customer first to deliver thoughtful and impactful insights on a boutique scale. They help investigate your competitive landscape by getting to know your customers and uncovering customer perceptions around your products and services to help give your product a voice in an increasingly saturated market.
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