Ross N. Feinstein

On building with Data


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Designing for Win/Loss

I walked into the movie theater last Sunday evening intending to see Catching Fire. At the touchscreen kiosk, I hit “Buy Tickets” only to find on the next screen that the button labeled Catching Fire had a red background because it was sold out. I hit “Cancel”, and left the theater.

The theater will never know if it should have allocated another auditorium at this time to play Catching Fire to maximize profit, and it won’t be able to adapt tomorrow. The movie ticket kiosk was not designed to understand Win/Loss.

Understanding Win/Loss and its Value

Marketers and salesmen conduct Win/Loss analyses to understand the reasons why their firm earned, or did not earn, a sale or other action from a customer. For example, as a skier, I may choose to buy a flight on airline A rather than airline B because it does not charge $100 to check a pair of skis. After interviewing a number of customers, airline A’s Win/Loss analysis might yield the insight that the airline wins sales in part because it does not assess checked-baggage fees, whereas airline B’s analysis may yield the insight that the airline loses sales because customers do not like checked-baggage fees.

Performing an analysis can be a very lightweight process, and it isn’t necessarily different from good market-driven product development practices. A proper analysis involves retrospectively understanding customer purchase criteria and considerations, whether the criteria were met and why, and how the considerations impacted the outcome. Businesses collect this data via interviews or other means.

Understanding Win/Loss is valuable because it allows businesses to make data-driven decisions to ultimately drive more profit. Depending on the business and the context, understanding Win may be more important than understanding Loss, or visa-versa, but solid insight is crucial. In online retail, for example, where a much higher percentage of customers don’t make purchases than do make purchases, understanding Loss may be both more important and more difficult. If an online retailer sees a 5% conversion rate and understands Loss such that it can convert 1% of the sales losses, it will increase its business by 20%.

Tweak the Movie Kiosk User Interface

Even though using Win/Loss insights to optimize a business can be extremely valuable, not all businesses design to facilitate Win/Loss analysis. In my trek to the theater, a slightly redesigned kiosk user interface would yield significantly more valuable data in facilitating Win/Loss analysis—an analysis that might help it understand how it allocates auditoriums, one of the movie theater’s main levers.

For a simplified, illustrative example, suppose I walked into the movie theater Sunday evening intending to see Catching Fire, and at the touchscreen kiosk, I hit “Buy Tickets”. On the next screen, I still find a button labeled ”Catching Fire”, but this time, we tweak the button’s design so I don’t know the movie is sold out until after I select it. When I hit the ”Catching Fire” button, the theater captures my intention to see the movie independent of whether I can see the move or not; now, because the theater has captured customer intent prior to losing the sale, it has awareness of the lost sale, a requisite first step in capturing it the next time!

Design to Facilitate Win/Loss Analysis

Design products and processes to engage and extract data—purchase intent, purchase criteria, etc.—from the user as early and often as possible to facilitate Win/Loss analysis. In the checked baggage example, if the airline collects the fact that the customer intends to travel with skis, its Win/Loss analysis will be more specific and yield more fruitful results. In the end, designing to collect the purchase intent and purchase criteria to facilitate Win/Loss is no different than basic market-driven business best practices, only with the added consideration, “Thou shall not win or lose a sale without proper data for conducting business-improving analysis.”

The data that drive Win/Loss analyses are functions of current business processes or products. Therefore, better design for Win/Loss means tweaking current processes or products to engage and extract data, then designing and implementing a process to persist the data for aggregate analysis and actionable results. For example, see what the customer’s purchase intent and purchase criteria are before requiring a lengthy sign-up process or a captcha that may push the customer out of the funnel. Or, as a car salesman, use the test drive time to understand the customer’s family, background, and job to understand his purchase intent and purchase considerations.

Smart businesses design to facilitate Win/Loss: don’t win or lose a customer sale without capturing purchase intent or purchase criteria.


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