Enough Is Enough: Feature Optimization Pays Off

Never too much of a good thing? Wrong. There is such a thing as too much. You can overdo exercise and overindulge on health foods, and even oversleeping can be a sign of a serious medical condition. You can over-engineer your products to meet perceived customer needs that are not actually there (i.e., are only important to a minuscule subset of the population). Just take a look at USA Today’s list of the “50 worst product flops of all time” for examples of products trying too hard.

The financial services space is not immune to overdoing it. Firms can overinvest in a particular asset class that eradicates a portfolio’s diversity. They can also over-engineer new financial services products. Robinhood’s foray into checking accounts is just one example.

Reasons You Over-Engineer

There are many reasons that products and services get over-engineered, including:

• The brand team is being evaluated on innovation metrics and motivated to keep adding incrementally to show progress.
• Someone in upper management had a “good idea” or pet project that everyone feels the need to pursue.
• You may feel compelled to “keep up with the Joneses” in our consumer market that seems features-crazed given the media’s constant announcements about the latest tech products and all things new.
• The “sunk cost fallacy” where money has been spent investigating features to the extent that you are no longer willing to let it go. The more time and money you spend on something, the more likely you are to want to stick with it.

Enough Is Enough (Kano)

We regularly see companies testing new concepts that layer on bells and whistles they have decided people should want, often without asking those people how much value those new features would add. All too often, the answer would have actually been “neutral”—or worse, “detractors”—and it will not move the needle for the company in a positive direction. Examples include:

• Services from health insurers to help customers find the lowest-cost doctors. This is an area insurers would benefit from immensely but could spell lower-quality care for customers (detractor).
• Ways to increase touchpoints with investment advisors. But, to advisors, quality matters more than quantity of touchpoints (neutral at best). And, this ignores what we encounter in our research that many advisors define “good service” as being left alone except for very specific, infrequent touchpoints (detractor).
• Extreme experiential credit card rewards—bungee jumping, paragliding, disc-jockey lessons. The target market is extremely narrow, and no one else cares (neutral).

When developing a product or service, the main focus should always be on the value it will bring customers. More specifically, the focus should be on the value as defined by the customers themselves.

Developed by Professor Noriaki Kano in the 1980s, Kano analysis accomplishes just that—it classifies features based on the value they provide to customers. It makes the assumption that maximization of all attributes is not necessarily the best solution. Instead, Kano analysis assumes that “good” is good enough for some attributes. That’s right—enough is enough in some cases—let it go!

More specifically, Kano analysis classifies attributes and features into five categories (our naming convention differs slightly, but the theory remains the same):

1. Delighter: the attribute/feature is truly exciting and adds an unexpected “wow”
2. Nice-to-have: the basis for competition in the absence of delighters, people are happier when the attribute/feature is present
3. Must have: the feature/attribute must be included for customers to be interested and is a cost of entry; customers expect the feature/attribute to be present and fully functional
4. Neutral: customers are indifferent; the feature/attribute will neither increase nor decrease customer satisfaction
5. Detractor: the feature/attribute has a negative impact on customer satisfaction; customers would rather not have these features

We believe that Kano analysis is a better approach for determining which features should be included in your next product or service because it gives greater insight into customer desires than a traditional choice-based conjoint system. In turn, this allows you to focus on optimizing the key features of a given product while recognizing unnecessary or superfluous wastes of your valuable time and money.

It is easy to see the immediate strategic impact on planning that this deeper level of customer desires reveals. Aim for at least one “delighter.” In the meantime, optimize your “nice-to-haves” and ensure that your “must haves” are all present and functioning well. Do not overinvest in “neutrals,” and finally, watch out for any “detractors” that would hurt your brand.

Feature Optimization Pays Off (Shapley Value)

Kano analysis is a perfect first step in prioritizing feature development. Yes, I said first step. But, how could it get better than that? Let me next introduce a cutting-edge modification of Shapley Value analysis.

Developed by Lloyd Shapley in the 1950s, Shapley Value was originally an economic game theory tool. Its powerful adaptation for use in market research line optimization problems helps us evaluate the interactions between attributes to best imitate the reality of how your customer evaluates your product/service. Because when was the last time you opened a credit card just for the sake of having a line of credit without simultaneously considering the lower interest rate, various rewards, and many other attributes? Customers do not make decisions in silos, and so it falls short to evaluate attributes in silos.

Marrying Kano and Shapley Value is more efficient and more powerful than the traditional paired-comparison approach to Kano.

You can clearly plot the incremental gain in customer satisfaction associated with each feature to the point that adding more features gets you very little, if any, more—and again, enough is enough! Seeing the multidimensional influence each attribute has on customer satisfaction lets us look at optimum bundles and understand trade-offs between the various attribute combinations to make even smarter, more informed decisions.

Propelling Products Forward: Catapult

At Escalent, our White Space Finder is based upon an advanced merger of Kano and Shapley Value analyses and the greater level of consultation that enables. If you’d like to learn more about how the financial services team at Escalent helps clients propel their products and services forward with feature optimization, contact me or Lindsey Dickman. You can also click below to learn more about our Catapult approach and how it can propel your brand forward.