The Art of Thinking for Ourselves

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Are you using judgement as well as data?

In March 2012, 3 Japanese students were visiting Australia. They had a hire car and decided to drive to North Stradbroke (near Brisbane). They didn’t know the area so they used the GPS system to guide them.

For some reason the GPS was not aware that the route was blocked by 9 miles of the Pacific Ocean. Not ideal, but you find another route, right? Not these Japanese students.

They stayed absolutely focused on their technology. They drove their car on to the beach and across the mud flats to the ocean. As the water lapped around their car they finally realised that they were stuck. As astonished ferry passengers looked on, the students abandoned the car and waded to shore. The car was a complete write off.

This happened. We are not making it up.

Psychologists call this automation bias (we could think of some other things to call it…). Automated systems lull us into passivity. We go with default options. We follow what the computer says.

We have become used to following these recommendations without thinking. Modern life has made it easy to do so. Who needs mental arithmetic when you walk around with a calculator on your phone? Who needs to think about what book to buy next when Amazon tells you?

We’ve got into the habit of not thinking for ourselves. Though, of course, driving a car into the ocean is a pretty extreme example!

Why are we talking about this? Well, in our industry (like many others) we have access to lots of information and data – EPOS, panel, loyalty card, brand tracking, research testing. All this information is a potential strength. It should help you make better decisions. However, we think that too often it is a weakness. You become too reliant on what the data says – you blindly follow the data or you don’t make a decision because you don’t have the right data to make it.

A good decision is a combination of art and science. It needs good data inputs to inform it. Then it needs a layer of judgement to direct what you actually do.

So, how can you add this layer of judgement?

Price Positioning. Most pricing discussions are based on modeled data, price index charts or questions about how much respondents say they would be prepared to pay for something in a (pretty artificial) concept test. But the shopper who stands in front of the shelf deciding what to buy is looking at an absolute price, comparing it to what else is on shelf and seeing what other value signals they are noticing. And they are doing all this in a couple of seconds.

How many shoppers have you heard saying “I really liked the look of the product and I thought it fully justified a price index of 130 vs the category average, so I bought it”? Never. Use pricing data inputs, but then make an informed decision about what to do. How will it really play out in the real world when the shopper is actually making a decision.

Shelf Layouts. In our experience this is one of the biggest areas in which people get lost in data. There is a big over reliance on ‘decision tree’ information and a big under reliance on judgement. Decision tree data makes the assumption that shoppers stand in front of a shelf and work through a neat decision tree process in their head (right, first format…, then brand…, then pack size…). Then they do this 40 more times as they walk around store.

It doesn’t happen. Shoppers have learned all these decisions already. They are just looking for the easiest way to make sense of how the shelf is laid out and to find what they are looking for. The job is not to develop the perfect decision tree. It is to make the shelf layout as simple and intuitive as possible. Then to direct shopper attention to what we most want them to see.

Activity Investment. Every company is looking for better ROI on brand and shopper marketing investment. But, to try to get there, many companies are trying to get to the silver bullet(s) – a model that tells them exactly what to do and exactly where to do it. But, the silver bullet(s) don’t exist. For instance, it is incredibly hard to isolate the different elements of a shopper marketing campaign. How much did the 6 sheet poster outside the store contribute? What about the secondary display? What about the shelf barker?

You’d need to run hundreds of test & learns to get there. Much better to have some key rules about what you do & don’t do. Then tailor these rules to the objective of the campaign and execute it really well. The old quote from John Wanamaker, the US department store owner, is as relevant in the data driven world of today as when he said it (he died in 1922) “half the money I spend on advertising is wasted, the trouble is I don’t know which half”.

We are not saying that data is not important. But, we are saying it is an input not an output. It is something that is used to make better decisions not something we should blindly follow.

Don’t end up in the ocean.

Feel free to forward.  Have a great weekend and speak to you next week.

© 2020 by Insight Traction