The power of “autopilot” – how do shoppers really cope with grocery shopping?

It’s a fascinating and familiar conundrum. Despite there being literally thousands of products in a supermarket that we never buy and are never likely to buy, we somehow manage to get in and out, buy our regular shopping, and complete the task in a relatively short time. Undistracted by everything we don’t need. I know we all want more “convenience” (one essential appeal of the online shop), but most of us do everyday routine shopping pretty well.

The way we do it is by learning and habit. We already worked out what and where our usual purchases are and don’t need to engage much of our pre-frontal lobe to repeat the pattern. It’s the same way I can play a piece on the piano without having to work out each note as I go (usually!) It’s easy to understand the process by considering when you go overseas and try doing a big shop at an unfamiliar supermarket. The store will be pretty much the same thematically (worldwide they seem to obey similar design rules), but different in the detail so your trip will take maybe three times as long. It lacks the subliminal cues that get you around your regular store – known layouts, known locations and known brands. You have to think about the whole trip. I find it fun, but my wife says it’s a nightmare!

The inspiration for this blog came from some fascinating data I received this week. We just ran a world-first evaluation of shopper behaviour at scale across an entire supermarket using our world-first video analysis software. We measured precisely where 100s of shoppers went, what they “saw”, engaged with and bought. We covered all categories in one process. It’s very cool!

But this time a client of ours also wanted to ask post shop questions at the exit on why a particular shopper hadn’t decided to buy a category they, in fact, had visited or seen — asking about barriers to purchase, in other words. So, we also asked by questionnaire which categories respondents remember “seeing” on that trip. Using this additional data, we then can compare their stated recall of seen versus actually seen, as objectively, behaviorally measured.

I am not going to get into the entire analysis today (white paper to follow I think!), but a key pattern was that for certain types of categories the recall, ie “noticed” was almost identical to the actual measured“seen”. For others, it was very much lower. The former tended to be (as seen our other data) high engagement categories (e.g. confectionery or potato chips). The latter tended to be regular grocery items (breakfast cereal or coffee). By the way, I should add that exit recall of what shoppers bought was pretty accurate across the piece.

My hypothesis is drawn from this discrepancy between “seen” and “mentally noticed” is that many shoppers will “wander” the store walking past categories where their predisposition is to be uninterested (e.g. already know I don’t need it today). Hence the presence of these categories doesn’t register much on that occasion. And that’s how shoppers get around a store so quickly. We only engage our brains when we come across something that’s on our agenda. Proponents of the often misunderstood concept of “System 1 and 2” will recognize some of this dynamic immediately. It’s why “bought” is recalled accurately – one can’t buy completely on autopilot!

This hypothesis (supported by the new data) has huge implications for brands, shopper marketers and display/point of designers. The idea that we can simply grab shopper’s attention with a piece of instore material, eg brand signage just by being visible is clearly underestimating the challenge. We have to break into their preoccupation and their pre-coded plans.  Particularly, it seems, for everyday groceries. Maybe there is more we can do with inherently more impulsive products….

The good news is that this new data is starting to show us how to improve engagement by analyzing where its better compared with worse. But one thing is for sure, all that money spent in-store needs far more careful evaluation to know if it’s truly working hard for us.

By | 2019-10-17T10:28:52+00:00 October 17th, 2019|Views and insights|