Editor’s Note: This post is part of our Big Ideas series, a column highlighting the innovative thinking and thought leadership at IIeX events around the world. Jian Huang will be speaking at IIeX North America 2019 in Austin, TX. If you liked this article, you’ll LOVE IIeX North America. Click here to learn more.
“The squeaky wheel gets the grease” is a common saying and often a driving force when making many business decisions. Everyday, product managers are inundated with information about all kinds of “squeaky wheels” – whether it’s feedback collected from salespeople, input from customer support, new initiatives by engineering, or demands from executives.
To product managers, the interlocking iron triangle of quality, cost, and time limit their ability to silence all “squeaks”. While the best product managers always prioritize innovation opportunities that can create the most value for the customer and company, they must also succeed in making exact, thoughtful, and even artful choices about which squeaky wheels to ignore.
With choice comes risk. Further complicating those risks are organizational cognitive biases and tendencies toward groupthink which, more often than not, turn the negative aspects of the “squeaky wheel” cliche into a sad reality.
Better research can help mitigate this risk. However, many product teams use traditional methods to derive priorities and cannot deliver the kind of data required for success. That is evidenced by as many as 90% of new products failing each year.
Fortunately, over the past 5 years, we have seen exciting new digital feedback technologies that can provide substantive information for product innovation. These advancements are scalable, easily deployable, reduce costs substantially, and shorten decision-making time significantly. This is because they are not only more efficient in collecting feedback, they are also able to better understand customer psychology through capturing behavior data.
Digging into customers’ psychology requires asking the right questions.
Asking customers the right questions is key when using any feedback tool. Through our research, we have found three questions all companies can benefit from asking:
- Question 1: To better understand product opportunities ask: What was on your mind when you felt you needed to buy [our product]?
- Question 2: When beta testing a new product ask: What pain points caused you to even bother to try [our beta product]?
- Question 3: If you are not sure what opportunities exist ask: What work-related issues keep you up at night?
On the surface, these questions ask about “pain points”. Underneath, they go far beyond by seeking to reveal your customers’ psychology—their unvoiced priorities.
Previously, getting this kind of information has been almost exclusively tied to running focus groups or in-person interviews. The cost, speed, and practical limit when using those conventional methods cannot deliver an accurate psychological picture of a large customer base. In addition, the unreliable and messy analytic procedures to process that kind of unstructured data can cause problems much bigger than just cost.
New digital feedback tools can gather insight on people’s psychology, specifically implicit group saliencies, through a seemingly simple online survey interface—Behavior Enabled Surveys (BES). The behavioral patterns discovered by these new platforms are especially powerful when paired with well-executed qualitative research, where you truly situate the consumer nuances that you have discovered in a much richer context.
This combination of BES insight is invaluable when developing a product or service strategy and can turn the “gut feelings” of which squeaky wheels to look at into sophisticated, data-enabled decisions.
“Moving the needle” is easier using the right tools.
As an example, a medical device company needed to gather feedback on a special needle used by surgeons. Historically it has proven difficult to get accurate feedback and derive a consensus from surgeons regarding how to best improve the design. Using a BES tool, the product team determined that out of 15 common sources of surgical error and a half dozen potential patient recovery problems, the top issue on the surgeons’ minds was the same thing—bleeding during the procedure.
There were, of course, “known” squeaky wheels about the current product, such as needle length, the handle, etc. Many surgeons actually spent their own time modifying and adapting the existing product to fit their personal use. However, the one feature that they could not adapt—which also happens to be the most critical—is stiffness. In addition, stiffness was revealed on the mind of surgeons as “control”, and through that, the product managers confirmed the most preferred feature is not an “optimal stiffness”, but instead a selectable range of stiffnesses.
The research supporting this product innovation was a success. Prioritizing the “squeaky wheels” was easy when asking the right questions with a BES and allowed the product team to iterate and improve the questions they ask. Better yet, they initially expected to spend months on research using traditional methods. In the end, they needed only a week: from preparation to operating the campaign to getting results, and informing strategies.
A customer’s explicit “squeaky” feedback will always be noisy and even unintentionally and subjectively biased towards extremes. Hence, from experience, few product managers feel they can trust survey data. In contrast, as the above example shows, Behavior Enabled Surveys do not rely on explicit data alone. They innovate through the additional use of implicit data—the combination of the two yields new insight and greater confidence in the results. Savvy product managers are just starting to take advantage of this new innovative approach for targeting and greasing the right squeaky wheels. In other words, precisely and efficiently discovering reliable product innovations that enhance customer value and drive growth.