#p&g

With its delicate ornamental pattern, this design brings an elegant touch to the window. Along with Febreze performance, it also offers high heat shielding and UV protection—ideal for the coming season.

From the Febreze Curtains catalog, developed through a collaboration between P&G and Aswan.

────────────────── Catalog: Febreze Curtain Category: Sheer Name: Elkhid Item No.: FB003 Features: Flame-retardant, heat shielding, UV protection, mirror effect, washable, Shadow Off, antibacterial and deodorizing

Marketers have long been interested in data. It’s just that much has changed in how we collect it. Remember, a marketer’s implicit goal is to sell more stuff, and hopefully to more people. The assumption goes that if we can know more about shoppers, then we might be able to improve our chances of selling more.

Easy peasy, right?

Not so fast there, you data crunching animal.

Back in the 1950s, when marketers first became mesmerized by data, about the best they could do was observe shoppers. After all, credit cards were not at all common, even checks. Most transactions were made with cash, which has absolutely zero value when it comes to tracking people. Loyalty clubs weren’t even a twinkle in some marketer’s eye.

So marketers would position themselves in second-story offices at large supermarkets, behind a two-way mirrored glass panel that allowed them to watch people from above, but remain unseen, lest they blow their cover or unsettle shoppers. They would tally the routes people took through a store, how long they lingered at an end cap, whether they reached for the eye-level product or stooped low or reached high.

Along the way they discovered some highly intuitive things, but at least had some numbers to back it up. Eye level really is the best real estate on the shelf, but if you are a kid, knee level is best, from an adult perspective. End caps force people to slow down as they are rounding the corner and aiming for the next aisle.

But not every product can be at the proper level or on an end cap. This ultimately led to supermarketers figuring out they could charge for prime placement. That term is “slotting fee,” the legal bribe that manufacturers pay to be displayed prominently.

Bar codes, which were first introduced in 1974 on consumer packaged goods (trivia answer: the first item was a pack of Wrigley’s Juicy Fruit Gum), allowed supermarkets to track sales precisely, but without benefit of identifying individual customers. This beat having to manually count cans and boxes on shelves, then adding any still in the stock room.

Computerization allowed companies to start going more granular. As credit cards and checkbooks became more commonplace, shoppers left behind identifying data, such as their account numbers. This was the beginning of customer profiling, which only got more and more detailed as time unfolded.

It allowed for “If…Then” scenarios, such that a discount coupon could be printed on the back of a cash register receipt if a customer bought a pack of diapers. This, of course, meant they had a baby, so why not push some formula and other baby-related items for their next visit

Skip forward to the last decade or so, and we now leave behind massive amounts of data, little grains in the beach of data sand that begged to be analyzed. It is what allowed Target to correctly surmise in 2012 that one of its teen female customers was pregnant before her father did. Parents, imagine learning this by analyzing the pregnancy-related marketing promos that arrive by mail when you know full well that it wasn’t you who was procreating. Yikes.

But that was still in the era of static analysis, much like the relatively old search era of Google, et al. The best that could be done was crunching and pivoting in databases, hoping to squeeze a little juice out of the orange. It was good, but it wasn’t perfect. There was still nuance to be extracted.

AI just entered the chat.

Procter & Gamble, the largest CPG firm in the world, is now leaning into AI to take the study of consumer behavior to the next level, and it is using AI. It’s no longer enough to be satisfied with the face value of those data points. No, now companies like P&G want to know what they really mean, kind of like Target 14 years ago, but much farther.

And so we find them leaning into many other data points not previously considered, such as social media, online reviews, fan sites, and more. If they were to tap into the enormous amount of data saved at Google Maps, they could do even better.

I shop almost—but not quite completely—exclusively at Walmart here in Canyon, mostly because the only competitor has higher prices on nearly everything I buy. I use my Walmart+ app to make all of my purchases, which includes self-scanning items and then scanning a QR code on the screen to make my payment. Walmart thus has an explicit, detailed account of everything I have purchased since November 2022, when I opened that account.

I also use Alexa as my shopping list. This means that Amazon also has a very good idea of what I like.

The only problem is that neither have definitively concluded my dietary preference. They have not yet picked up on some very nuanced data, such as things I do not normally buy throughout the year (they have three years’ worth of data and patternicity now), but do buy right before Thanksgiving and Christmas. These are food items to prepare for my family whose diet is different from mine.

If they were really examining the data, they would know this. Furthermore, if they were scanning my Google reviews, they would have learned a very long time ago that I am vegan and write my reviews from the perspective of someone looking for similar food. And for what it’s worth, I am a non-militant one. What a person eats is their business. I don’t care what you put in your mouth, as long as you don’t care what I don’t put in mine. Peace out, y’all.

This is the kind of super-granular data that only AI could tease out, and by examining a lot of non-traditional sources to go along with the usual sales log. I am waiting for Walmart and Amazon to go the extra mile and truly peg me.

And you know what? I am good with this. I realize that data transfer is just the price of participation with these apps. I want marketers to know what I want and don’t want, because that means I will have a whole lot less clutter in my feed, my emails, etc.

This is about doing better marketing, not necessarily more. If you have a problem with sharing that much data with others, then please be careful with the story you are telling. In the end, though, the successful marketers of tomorrow will be those like P&G who go the extra mile to truly know their customers.

Dr “It’s All In The Data” Gerlich

It's one of Febreze (P&G) in Japan.

Does this line deploy in the US?

I absolutely recommend the "White Tea" particularly if you can get it. This is really really nice fragrance!!

I use it as a heavy user already, even though it's new merchandise. 😍