Not as you be here among the experts, so to speak, I will shift a little bit gears and talk about data and some underlying factors that belongs to us and how we actually experience them and how important they are or not. For that matter of fact, data, massive amount of data seems to be the holy grail in creating more sophisticated AI human-like chatbots or selling more products. But with GDPR kind of limiting our ability to collect more personalized identifiable data, to build more intelligence, what is next?
How can we create a better understanding, more sophisticated understanding about our customers needs and expectation in their behavior with less data. Most CEOs, CMO CEOs still believe that data is a new oil. We see this in fors magazine cycles in magazine articles, and it's no wonder that we still collect massive amount of data, personalized data.
Of course, if it's allowed behavioral data soft data that we run through natural language algorithms or programs to examine the interaction between humans and computers, to pull a meaning from the conversation to sell more, right? We believe the more data we collect, the more we know, but is this belief true or is this merely just a belief?
There was an article written beginning of the year.
The, the number night might be true, but SF January, 2019, collectively, we accumulated 2.7 zetabytes of data in the digital space. Does anyone in the room know what a Zeta bite is? Me included? I have no idea by the way, but to give you a reference, give you a reference Zeta bite, and it's on YouTube. So blame YouTube for this, but if you would watch a Netflix video for 30 minutes, that's one gigabyte, one gigabyte, if you would, BenchWatch YouTube videos, BenchWatch you have to go back to the beginning of time.
And I don't mean the a D C before that beginning of time, till now you would've accumulated roughly one Zite of data. That's how much data we have accumulated. And there was a presentation that we will accumulate, I think 115 terabyte trillion gigabyte of data in 2025. Interesting enough with all that data accumulated, we only analyzed 0.5%. So 99.5% has been analyzed. So it's no one that actually 85 of data science project fail problem. Number one, problem. Number two, if anyone is familiar with data science, we all know it's utterly complex.
And if you're familiar with the data science hierarchy of needs, AI machine learning,
You know, for machine to learn to pro process data on its own, without us interfering, it needs a massive amount of quality data, quality data, right? Problem. Number two, we need to have quality data, but even if we have this quality data, the question have, if this quality that we utilize, is it predictive of the behavior? Is it predictive of purchase, right? It's a problem. Number two, let me, let me show you a little anecdote with a, with a client we have, and a client said, Hey, we have a problem.
And this client is utterly sophisticated, utterly sophisticated. It's able to collect personal data, behavioral data, of course, with consent. And that we're able to create very sophisticated clusters. They analyze the clusters, they build machine learning algorithms to push the right message at the right time with the right price point to these individuals to Samoa because that's the goal for any organization. And what they saw is they saw a brief increase in sales because they optimized their system. But over the long term, they couldn't convert more customers.
What they believed with all the data they had available, it was directly correlated to purchase.
And within lies a dilemma that we believe that all the data we have is somehow linked to the behavior that we wanna project purchase. But whereas in reality, the answer, it's not always true. So if the data we have is not directly linked or is causing the behavior, then what is causing the behavior.
There was a study done by mass B mass B as a marketing accountability standards board in the United States, which over the last 15 years has a charter to understand which marketing measurement's directly correlated with market share and sales volume, right? Quite, quite important for any company and what they have found studies among 120 products in within 20 categories. That preference is in direct correlation where sales market sales volume and market share. If I prefer something sales volume goes up. If I prefer something less sales volume goes done very clear, right?
Well, the question is then what is governing preference? If it's not the data that we are collecting, how do we as humans actually form decisions?
We, we, all of us here, we are utterly complex too.
When we make decisions, they don't just happen in a vacuum, right? They don't just have online, offline. Every product, every service, every brand is surrounded by a set of factors that we use to make a decision. And these factors have little or nothing to do with who we are, our demographics, our lifestyles, cetera, et cetera.
The idea is based on the principle of behavioral economics that teaches us that multiple components, social, economic, cognitive, all combined allow us to frame a way and how we decide how much money we bring to pay, whether the product or service actually fulfills our expectation. Let's say, for example, Susie, Susie's on the marketed buy a new car, quick example, and she's looking at a BMW Audi and a messy dispense, right? And every day she's bombarded with messages. She drives by science that kind of communicates to her.
This is the right car for you,
But what she does in her mind, she's evaluating economic and psychological factors like the features of the car, the maintenance of the car, the value, when I drive it off the lot, how it might drive, how it might feel sitting in the car, how others might see me driving the car. And for each of these factors, she's evaluating whether these things can fulfill expectations here, a utility expectation, and not only does she has these expectations, she also puts these things in a very specific order. That's relevant to her and what she does.
She's evaluating the choices. That's valuable to her against that framework and hope in the end, the products and service will provide her with utility, hopefully on top of her expectation, but hopefully exceeds. So she falls in love with the product and service and what this might look like is like this, this is a simplified, psychological process of how she thinks we're on the left. The salient factors that really governs her behavior and on the right kind of the less relevant factors for her.
And if you think about this, we do this with everything in the world, how you pick this conference, how far from home, how much do I get knowledge from it? Who do I meet? Are these people there?
And this information that you make choices with might have little or nothing to do with who you are and what data is collected about you, how powerful this actually is. We demonstrated to another client, very simple, not analyzing it, even go forward deeper and actually measuring utility, but just purely by communicating what people need and want.
So we had a grocery store client in the United States and they wanted to understand how moms shop for the groceries. And there was a hypothesis back in the day, this millennial mom shop differently than mom because, you know, millennials, they're so much different than we are truth, be told or not. So rest is short, but they wanted to know how moms make their grocery purchase. And what we have found there is 10 factors. And by the way, in reality, there is for any given decision seven plus three factors, and there's something to do with the capacity of our brain, right?
If you ever played these memory games, you can easily pick out. He says a seven tiles. When it comes to the eight tile where it sits, it becomes complicated.
Well, what we did, we lump people into similar decision types like Susie, right into similar cluster, differentiating them between the primary and secondary driver. So price, discount, quality shopping, and so on and so forth, starting with their primary effect of how they think I need price dis first and what the quality is, you know, what my family wants and so forth, so forth. And what we said is if you can just communicate to them, their primary need that you have, that you can fulfill them. You can bring 'em into the boat.
So we did a study, let's looking at these four segments and said, if we would build a store that would reflect their specific needs, these people should come.
So we did a study and just said, Hey, we are building a store in your neighborhood that delivers on price discounts on the budget, that you have a valuable, the quality of the food and what your family wants. And these messages were not superlative claims, right? Just keep that in mind. They want like, oh, we have the best discounts.
Oh, we really fit your budget to the key, no non claims. And we didn't even go into the secondary driver price, discount quality. And what we have found that 77% who belonged to the price discount segment actually picked that store because they felt it would reflect what they need.
They say, well, these so and so forth, the reason why the last message didn't work because these women knew that store didn't exist. Right. Very simple as that. So the message failed because there was no store in the world.
He actually could deliver the family once the power of expectation, fulfilling it. There was another segment that we found, which is rather interesting is list shoppers. And by the way, these women look like this, they hate shopping. They would rather do the dishes for the rest of their lives than actually go shopping again. How many of you hate shopping? Yeah.
Like me hate shopping. And I feel like them, good thing. I have a fiance by the way, makes it way easier. But this is what the psychological process looks like a little bit more complex, but how they live in their world is that they have a family of five and every day they write down on the list, what they need.
Well, this very special beer for my husband. Well, I need this little organic food. My kids want this cheap, you know, easy to bite food.
So I, in her mind, she has to do all these things and come up with a place and time when she goes. So she's like, okay, on Tuesday, my husband can pick up the kids from soccer. Then take for piano. I have 45 minutes. Tuesday is bad because they're not price discounts. And there's not the quality food I want. So Wednesday, Wednesday, Wednesday, that store has, yes, it's on price discount. I can bet the quality food I want no cumbersome. So what she ends up is she goes shopping every single day of the week in different stores to fulfill her need.
What we told the client is like, Hey, what if you built an app that allows people to create a list of what they want for the price discount they want for the budget they have available for the quality food that they need.
And you deliver to their store at the time, a little bit more complex because the study was done in 2014. Now these companies pop up everywhere. One of them is Instagram. Instacart delivers your food to your doorstep from the store. What do you want at any given point in time of the day, delivering UN expectations.
This company currently has a revenue of $500 million a year, which is 2% of the overall grocery market in the United States. We know they have 2% more to go, and that's just capturing the folks who actually are list shoppers, delivering on expectation. Delivering on utility utility is extremely powerful.
If you understand what governs people's behavior, really, what are the set of factors that drives decisions? You're much closer delivering services that are relevant to the customer that you're serving.
And this will become even more important as we move into an era where we think we have to analyze everything and collect everything where in truth, what really is important is like, what is relevant to me? How do I wanna be transported from Monday to Friday, which might change on the weekends with I OTC approaching us and en crunching our lives in a very positive way. To be honest with you, because we are actually lazy. Wouldn't it be great if you would understand what needs to be in your fridge before you actually narrow it, but more so, how do you wanna live?
Which has little, nothing to do with who you really are and what the data is collected enough. But what if we can give these organizations information that we think is relevant to live a better life, where it's irrelevant with who I am, because in the near future, you all know this, I know this collecting more personal data will become even more complex and difficult. And since limited by GDPR, CCPA and other privacy laws around the world.
So to get outta the head of the curve, you need to shift your perspective from collecting data, about who, where, when, what, why to a broader understanding about why we prefer what we prefer and what really governs that preference.
Understanding us customers from a behavioral economics point of view will deliver. And I promise you superiority over your competition. It actually will help you understand people's expectation. You can serve them in a much more relevant, a much more direct way. And in the end, hopefully it will help you lead your customer's preference in your favor. Thank you.
