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Behavior science is like DC lobbyists. Hidden from the spotlight but definitely pulling strings behind the scene.

Every retailer business is fascinated by the sway of behavioral influence. But few even understand this invisible force, and fewer still use it effectively.

And let me tell you. Those who use it win, and their competitors don’t even know it’s being used against them. That’s one of the nice things about this science. Unlike flashy marketing which is instantly copied (rendering it totally ineffective) it’s impossible to reverse engineer someone’s buyer psychology strategy.

Ok, enough talk. Let’s look at some mind blowing stories:

– Rock Bottom, restaurant and brewery, wanted to measure customer word-of-mouth. The surprising finding of this study was that the heavy loyals didn’t bring in a lot of new sales. One explanation is that these people had already done their buzzing prior to this campaign and had already exhausted their reach. The light loyals brought more business, but it was nonloyals, for whom Rock Bottom was totally new, who brought in the most. In fact, each word-of-mouth discussion by a non-loyal yielded incremental category sales of $192. (Source: Anatomy of Buzz Revisited). Lesson here: All of your competitors (and likely you too) and obsessed with giving special service to old loyals. But the group that could bring the most new customers are people who’ve recently discovered your brand and fallen in love with it. And we have a playbook for these people.

– Williams-Sonoma, known for premium kitchen gear, once offered a fancy breadmaker for $279. They later offered a somewhat larger model, pricing it at $429. Guess what happened?

The $429 model was a flop. But sales of the $279 model nearly doubled. Clearly, there were people charmed by the idea of a quality breadmaker from Williams-Sonoma. The only thing that stopped them from buying was the price. It seemed too high at $279. Once the store added the $429 model, the $279 was no longer seen as such an extravagance. It could be rationalized as a useful product that did nearly everything the $429 model did, at a bargain price. Adding another price point, even though hardly anyone chose it, increased the price consumers were willing to pay for a breadmaker. Welcome to the power of price anchoring. Is there room to apply price anchoring on your site? Yes there is.

– Caesar’s Entertainment (the casino) noticed something peculiar: majority of first-time visitors to their properties didn’t return. There are a number of reasons why a customer may not return but a big one is their first visit experience. If the customer has an experience they like, it GREATLY increases their chances of becoming a regular (thus making Caesar’s Entertainment a lot of money). In the casino business a bad experience is when a first-time visitor loses more than they expect. Since Caesar’s knows the distribution of winning/losing for each type of game they know when the first time visitor is on the losing tail of the distribution (bad experience). This raises a flag in their monitoring system. It’s important to note that most casinos would do nothing for this customer. But at Caesar’s when this event is triggered a manager walks to the customer and asks how they are doing. The customer says they are having a terrible time and the manager apologizes and offers her a free dinner, a hotel room or a limo ride (for example). To study bottom line impact of this strategy Caesar’s will make the offer to only 50% of first time visitors who are losing heavily. This allows them to compute the difference. And not surprisingly, that small shift in first visit experience greatly increases customer lifetime value.

– As retailers love giving buyers more choices. Hey, if 96% of my site visitors aren’t converting we should just keep more product types on the site. More we add to the site higher the chance the user would find something they like.

Psychologists Sheena Iyengar ran an experiment.

On one day she set a jam stall with 24 different kinds of jams.

Then, the next time she reduced the number of choices to 6 jams.
Iyengar found was that while the big display table (with 24 jams) generated more interest, people were far less likely to purchase a jar of jam than in the case of the smaller display (about ten times less likely).

Related example.