For any of you who might still question my assertion that traditional advertising and loyalty businesses will soon be pushing up daisies, Nielsen’s recent report on how consumers buy will, without a doubt, convince you that I’m on to something.
Nielsen has access to scanner data on what consumers buy and where – not as much as they used to but they still see a lot of good stuff. They just completed a study based on 50,000 purchases across 100 fast-moving consumer goods categories – those things that consumers tend to buy in grocery and drug stores and that account for a large part of their monthly spend. Fast moving consumer goods can be both food and non-food and examples include produce, eggs, bread, pet food, medicine, candy, cookies, body lotion, snacks, cosmetics, and the two staples of life that everyone in the Northeast rushed out to buy in face of the weekend snowstorm – milk and toilet paper.
Nielsen concludes that 72 percent of purchases made in those categories are decided before consumers ever leave home, leaving the remaining 28 percent sort of up for grabs and in the category of highly sought after, high margin incremental purchases that retailers want consumers to make. At first blush this stat might seem like a real bummer if you’re a retailer trying to get consumers to choose your store and a brand trying to get consumers to try you out since it appears that most of the time consumers have already made up their minds. And, if all that stores and brands had to rely on was traditional advertising and loyalty techniques, I’d say that they’d probably have good reason to be bummed out.
But thanks to smartphones and apps and data and the cloud and clever players leveraging new technologies, they don’t have to be. If anything, Nielsen’s findings suggest that the most effective way to influence those purchase decisions isn’t the old fashioned advertising way at all, but via apps and in store technologies that put messaging literally in the hands of the consumer right smack in the middle of her buying process.
How about this, for instance? Apps that consumers download to their smartphones that are tied to store loyalty programs can be enabled to do all sorts of neat things that can influence planned and unplanned purchases. They can create shopping lists that prompt consumers to buy items and brands based on purchase frequency or even external events, e.g. a snowstorm is coming so make sure that you have bread, milk on hand or New Year’s is coming, better order stuff for your party menu now. It can, at the same time, present coupons or offers for brands that are bought (or not, depending) as a further inducement for making the trip to that store, versus another and a purchase of a new brand over an existing one. That app could also serve up promotions based on those high margin impulse purchases, so while consumers are reminded to buy the stuff they need and had planned to buy, like the milk and bread to weather the storm, they’re also prompted to buy unplanned things like marshmallows and chocolate and cocoa so that they and the kids can make s’mores and hot chocolate while the snow is falling. These apps can even present recipes for that New Year’s Eve party and offers on ingredients for making the menu items. Some players, like Amazon Fresh and Peapod and Whole Foods can even offer to deliver those purchases and charge the card on file. The net result here is that these apps and offers not only have the opportunity to keep customers loyal to a store, but to get them thinking ahead about those unplanned items so that more of them can be shifted over to the “planned” category over time, increasing basket size, margins and retailer happiness levels.
Once in the store, technologies like Beacon and iBeacon can convert robo-shoppers, who once cruised the aisles mechanically filling their baskets with planned item purchases, into engaged consumers by alerting them to offers in aisle in an effort to influence purchase. Nielsen reports that nearly half of the planned purchases that consumers make are totally done by habit, and some of the least engaged purchases are their biggest shopping needs. But what I wrote about last week was that Stanford University professors have found that people can be moved away from those ingrained habits if they’re given proof that others are doing something different, even if that behavior is tied to a purchase decision that costs more.
Nielsen’s report confirms this to be true with fast moving items, too. Their data show that brand loyalty can be overcome by “reminding” people in aisle that another brand has a better product quality rating, e.g. the wisdom of the crowd effect. So, using in store technologies to serve up information that provides ratings, or even information about the number of people who selected Brand A over Brand B that week or that day or that hour are all relevant inputs into reducing the risk that consumers feel by breaking old purchase habits. Letting them know that many others have done it will make them feel a-okay about doing it too. Add to that a simple way to leverage these in-store technologies and apps to streamline the check-out process, and you have a completely reinvented way of turning what was once thought to be a nearly impossible set of products to shift spend and loyalty from into a shopping experience that adds value to the consumer and value (and profits) to the retailer.
So, as I mentioned, last week, this is the new playing field for advertising and loyalty and it is being subsumed into the payments and commerce ecosystem. The enablers are those who are closest to the merchant and the consumer and the offers aren’t tag lines or ads, but information and promotions. What these players are using technology to do is to replicate what search advertising has done so successfully over the years – capturing consumer interest and attention while they’re thinking about making a purchase. But, the combination of smartphones, apps and in store technologies are taking this two steps further – influencing purchase at the time and the place that these purchases are being made and converting unengaged product purchase behavior into highly engaged product purchases.
The “hypothetical” scenario that I started with assumed an app tied to a store loyalty program but that is far from the only option available to consumers. In fact, I would say that it may be the category of player most at risk. Lots of third parties, large and small, are emerging who have clever ways of capturing consumer spending data and are using it to do things like compile shopping lists and then directing consumers to stores where the highly unengaged consumer product purchases like milk are the low-priced bait in an effort to help those consumers load their baskets with more of the higher margin unplanned items. And, apps that aggregate “wisdom of the crowd” data on key product category purchases are also shifting behavior away from stores and products that were once consumer “mainstays” to others that the community has said offers a better overall value equation.
So, I know what you’re thinking then – why the heck is Chobani (the Greek yogurt people) spending $4 million for a 30 second ad on the 2014 Super Bowl? Could it be that they really wanted a ring side seat to the Bruno Mars half-time show and figured this was a sure fire way to get one? Sure, I get that “designer” yogurt is one of the 28 percent unplanned purchase items that Chobani wants people to have top of mind when they are making their lists and checking them twice. But it does boggle my mind at least to think that an advertiser of a product category like this would spend $4 million dollars for a half minute of air time when those dollars could be redirected into the channel that reaches people when they are actually in the mode of buying yogurt – in the store standing right smack in front of the dairy case.