Consumer behavior is always changing. Even with COVID-19 affecting people’s lives and how businesses operate, it will never be the same. How can businesses better serve customers by staying ahead of changes and trends? Data.
Today’s guest is Jonathan Silver from Affinity Solutions, a data intelligence platform with access to consumer data. Jonathan talks about how businesses need to collect data, know how to interpret that data, and turn it into action to succeed.
Some of the highlights of the show include:
- Affinity Solutions: Access to unique data around people’s purchasing habits
- Permission and Participation: Banks provide businesses with consumer data
- Business Benefits: Use data to build relationships and grow, retain market share
- Consumer Benefits: Use data to improve people’s lives to get what they want
- Shifts: COVID changes behavior with price sensitivity, personalized experiences
- Trends: Parallel reality where physical environments change with technologies
- Predictions: Colder weather will spike COVID cases, continue habit to buy online
- Data Types: Understand and adapt to consumer behavior with purchasing info
- Regulatory and Privacy Trends: Personal data cloud and operating system
- Survive and Thrive: Expand to include external data to redefine competition
- Insight into Action: Distinguishes successful businesses and drives returns
- Data Platform: Artificial intelligence/machine learning make directed decisions
- Downward to Upward: Use data-driven tools, dashboards during difficult times
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Ben: Hey, Jonathan, how are you doing this morning?
Jonathan: I’m doing great, Ben. How are you doing? Thank you for having me on your show.
Ben: I’m not doing too bad. We are getting our first snow of the season here in North Dakota, which is a little bit sooner, but we’re tough. We’re dealing with it. Would you mind taking a moment just to introduce yourself to our audience and explain what you do at Affinity Solutions?
Jonathan: Happy to do it. Jonathan Silver, I’m the founder and CEO of Affinity Solutions. What we do is use data. We have a ton of unique data around people’s purchasing habits because we have relationships with thousands of banks for which we run loyalty programs. They send us every day, every transaction that happens. We’ve been able—with permission from the consumer—to take that data and make it available to others to help them.
Particularly, businesses build deeper relationships with their consumers, with their customers and prospects, so that they can grow and retain their market share, in a time, of course, COVID, when business challenges are significant.
We are using their data to help businesses build and grow their market share, and the underpinning of all of this is using data to improve people’s lives. There’s a consumer orientation, which is about helping people get what they need, create personalized experiences. We’re even looking at how data can be used in personalized health and education, but the primary client, if you will, a customer is helping businesses use that data to improve and grow their market share.
Ben: With access to as much data as what you have. I imagine you’ve been able to understand all kinds of changes in shifts in consumer behavior that have been developing since the beginning of the pandemic.
I’m curious, what are some of the biggest shifts in consumer behavior that you’ve seen that you can attribute to everybody’s lives, essentially, just being upended?
Jonathan: It’s certainly been interesting to see those trends play out in the data that we’re getting. Beyond the obvious, people are buying online. They’re doing things. You do something once—it’s interesting, it’s novel, you do it twice. But once you do it three or more times, it really starts becoming a habit, and more and more people—even those that have typically not have done so—have gone online.
Hybrid—buy online pick up in-store, but what we’re excited about is the trends that businesses are starting to reorganize around this, creating highly personalized experiences. This is not in five years, not in three years, probably in the next 24-48 months. Imagine walking into a store and it becoming the Ben Sailer Store. I imagine all of the products that are tailored to you.
I was telling folks back in January, I was at CES—formerly known as the Consumer Electronics Show. The CEO of Delta Air Lines, Ed Bastian, was on stage, and he was bringing some of his partners on the stage to talk about the future of travel.
Even though travel was put on pause, what was really cool is they were about to introduce—in Detroit Airport and LAX—this cool technology called parallel reality, where Jonathan Silver and Ben Sailer can both be standing in front of a billboard. You’re looking at that billboard, and you’re seeing things that only relate to Ben Sailer. You’re seeing what time you’d be at your gate, the restaurant down the terminal that has food that matches your preferences, the weather, and the destination city. Everything about your travel experience, and nothing else.
I’m standing right next to you looking at the same billboard, and I’m seeing things that relate only to Jonathan Silver and not Ben. We’re not wearing special glasses, we’re not doing anything, and yet, we’re having this incredibly personalized experience. That kind of thing where physical environments are changing with these different technologies is going to become a norm. That’s more of what’s coming, but definitely, as we look backward in addition to online, we’re seeing more price sensitivity.
One really interesting thing that I think your listeners would want to hear is there has been a dichotomy in higher-income and lower-income spending. Where people that are higher incomes, they have the ability to shrink their discretionary spending down, and because they haven’t wanted to go out to restaurants and haven’t wanted to go out to service establishments, and so forth.
That’s been the most significant decline in spending has been among the higher income versus the lower-income where there’s not a lot of discretionary spending to decrease. We’re seeing interdependency between those groups. The higher-income folks, if they’re not going to restaurants, the lower-income servers or waiters aren’t getting tips, they’re not getting employment.
If higher income is not going into a nail salon or a beauty salon, then the people working in those establishments aren’t getting paid. There’s this weird interdependency with higher income folks spending less, and how that affects lower-income employment, and so on. I can give you more examples, but those are just some of them.
Ben: Sure. I’m sure there are all kinds of changes. I’m sure that’s an ever-evolving situation right now.
Jonathan: Can I give you one other example?
Ben: Absolutely. Go for it.
Jonathan: We’re only a short time away from an election, and so we’ve been also looking at the spending behavior of Republicans versus Democrats because the southern states tend to be a little more republican leaning. What we’ve seen is that the southern states—republican leaning states—are doing a bit better in terms of consumer spending and employment. Of course, it’s coming at the expense of coronavirus cases.
We’re seeing a lot of willingness based on the posture of the governments in those local and state governments, as well as the attitudes of the people in those states. More businesses are open, more people are going out of their homes to shop. Coronavirus cases are spiking, but the economy is doing better in those states.
Ben: Interesting. One other question I would like to ask you along that train of thought. This is something that’s going to become relevant to people very quickly, if not already, and I think especially for those of us in colder climates. Also, keep in mind, this episode is going to go live sometime around the end of November or early December, somewhere in that window. How do you anticipate just like colder weather impacting consumer behavior?
Obviously, in places where you don’t get a lot of snow or maybe if just inclement weather isn’t likely to impact a person’s willingness to leave their home, maybe it’s not such an issue. But if you are looking at places like where we’re at in the upper Midwest, maybe on the East Coast like the Northeast Coast, maybe the Northwest Coast—places where whether it’s a bit more of a factor. It might be difficult to gauge if you don’t have data to look back at retroactively at this point.
Do you have any predictions or any educated guesses as to how the winter season could impact consumer behavior when you’re taking that and you’re combining it with what’s going on with the pandemic?
Jonathan: Well, I think there’s at least a consensus that with the colder weather, there’s going to be additional spikes in Coronavirus cases, so that the combination of it being really cold out, and more cases will keep people indoors more for sure.
The trends that we’re seeing in online spending will certainly be there. A lot of the home delivery services like Instacart for grocery; Grubhub, Uber Eats, and DoorDash for restaurants are obviously going to be continuing to consolidate share.
We’re seeing some restaurants getting really good at home delivery. We always talk about Domino’s and Papa John’s because they always have home delivery, of course, but what they managed to do with COVID is to make it completely end-to-end contactless, so there are no human hands touching the pizza from beginning to end.
I think one of them, you can order food to specify the front door, the side door, or the back door of the house. They’ve perfected home delivery and that experience. You’re going to see more people hunkering down clearly if the cold weather starts to spike.
I think also just the habit of buying online, there’ll be more and more innovation around personalization, bringing that virtual reality even into the home. This technology around virtual reality, mixed reality, augmented reality, and the internet of things where the home will become transformed into this commercial environment that if I never have to leave it, I could survive.
I think more of that, but we’re seeing a prediction that the cold weather is going to be pretty intense for certain states as we head into the winter.
Ben: Yeah. That’s something that I’m bracing myself for personally. I was just curious to get your insights on how that might be a factor. Obviously, you’ve got access to just an incredible amount of data. I would believe that you have a very strong understanding of which types of data—as it pertains to consumer behavior—are most important for marketers to gather, analyze, and understand so that they can better adapt to those changes that are occurring very rapidly right now.
In your view, if I’m a marketer and my business is being impacted by the pandemic—which is pretty much all business right now—which types of data points or which things would you say are most important for that marketer to be looking at right now?
Jonathan: As you know, I’ve shared earlier in the call, in the podcast, we have a ton of purchase information. We see that it’s foundational because the best predictor of future purchase behavior is what you’ve done in the past.
If you’re a business, looking to organize your products and services and your customer experience in a way that meets customer demand, you need to start with this foundation of purchase behavior outside in.
There’s also a ton of other data and because our data is what they call matchable, meaning, even though it’s anonymized, we do the anonymization in a way that can match up to other datasets.
We’ve linked and matched to that data all kinds of demographic, behavioral, and lifestyle data, which is incredibly useful, so we can understand the difference as we talked about earlier between higher-income and lower-income folks. Generation Y versus millennials versus baby boomers. We’re seeing differences […] there. You have to understand your customer in that regard.
It’s also this other massive data set out there for location data, where are you at any given moment, your online behavioral data. We believe that all of that data is going to be consolidated into what’s called the personal data cloud. There are trends going on now, both regulatory wise and business application development.
Imagine, Ben Sailer, you’ve got your personal data cloud, all of this data sitting there. Imagine a couple of years from now or even sooner, this new app store where your buddy will tell you, hey, Ben, you got to go check out this incredible experience. You walk into Home Depot, they recognize you by name. They make recommendations. It becomes the Ben Sailer store, and you’re like, oh, cool. Let me go check it out. You go sign up for the app, and when you sign up for the app, you’ll provision or permission your personal data cloud to that experience.
We talked about this idea of a personal operating system. Not to get too techie, but the operating system is usually thought about as associated with a device like Windows for your laptop, iOS for your iPhone, or Amazon has its own version of it.
We think about it as an operating system wrapping around a person. Ben Sailer has his personal data cloud. There’s consent management to make sure that your data is only provisioned to those that you give permission to do so or privacy controls. There’s machine learning that allows you to intersect with the world and get personalization, and we think it’s going to go beyond commerce.
We think it’s going to go to medicine. Imagine personalized medicine taken to a whole new level. Education, imagine three, five, seven years from now, our current educational system will look prehistoric compared to what it will be then. It’ll be personalized based on young adults’ and kids’ aptitudes, interests, and skill sets. And it will be a whole different way of educating.
We see that all of this data filtered through the lens of a personal data cloud will be extremely valuable, both for the businesses that want to personalize their offering to consumers, as well as consumers who want to make sure they get what they need.
Ben: Sure. Getting a little bit more specific, what are successful companies doing differently with data right now that’s helping them to survive or even thrive under our current circumstances? What is really separating top performers from those who are struggling?
Jonathan: Great question. We talked about Domino’s and Papa John’s, they figured out the whole contactless delivery. We’ve seen grocery chains is one very big one that we’ve worked with. It’s redefining their competition.
Grocery stores—let’s say Safeway or Kroger—would look at other groceries as their competition. What we were able to demonstrate with our data is your competition isn’t just other groceries. Your competition is restaurants. Your competition is QSR. Your competition is delis that are competing for your share of stomach. That’s another way of saying share of wallet in the food business.
The same thing with McDonald’s, they started to reorient themselves as their competition isn’t just Burger King and Wendy’s for hamburgers. They were able to show—when Popeyes introduced their chicken sandwich—that McDonald’s had the most significant lots of share, not to other burger places, but to Popeye’s. That led to McDonald’s introducing their own chicken sandwich.
What we’re seeing is the businesses that are doing better are realizing that they can’t rely on their own internal data. There was a big hole punched in the data with COVID. People didn’t come into their restaurants or stores. They weren’t going to their websites. You have to rely on outside-in views of what’s going on, and that outside-in view leads to insights that you wouldn’t have otherwise.
If I were to boil it down, it’s businesses that are getting near real-time insights, ideally, at the local level. The McDonald’s at One Main Street may have a different dynamic in terms of customers than McDonald’s halfway across the country at Two State Street in another city. It’s understanding and then being able to take action on those insights very quickly.
In the case of McDonald’s, they introduced a new chicken sandwich. In the case of Safeway, they might change their food service to compete with restaurants, or there’s a whole marketing dimension to taking action. Which is if I know what products are most interesting to this particular segment, I can target that segment more effectively. I can optimize the marketing that I’m deploying because I only have so many marketing dollars.
That whole insight to action—being able to get real-time insights locally and being able to act on those quickly and short turnaround time—distinguishes the successful from the less successful.
Ben: One takeaway we can extract from Jonathan’s insights here is the importance of personalization moving forward. This is something that a number of other recent guests on the show have also discussed. Whether you’re talking about personalizing brick and mortar experiences like Jonathan does in this episode, or you’re talking about digital experiences on your website, in your app, or whatever the case may be. It’s something I have a feeling is going to turn from being optional to being table stakes sooner rather than later. Now, back to Jonathan.
A follow-up question I have to that is when you’re moving really, really fast, I imagine you might not always have quite as much time to think through what you’re doing, as what you may have felt that you had under normal circumstances. Particularly, with large companies that maybe struggle to do anything with any amount of speed.
If that’s changing and you’re being forced, you’ve got to get this data, understand what it’s telling you, and react very, very quickly. How do you balance that with making sure that you aren’t just really, really rapidly burning through whatever budget you have? If you’re doing things like you’re using that data to help you quickly, not just take action with it, but take action that is going to help you drive a return very quickly as well.
Jonathan: It’s all about ultimately, technology. How we’re showing up Affinity Solutions in the market is we call our data platform—for lack of a more imaginative name. The data platform for us is the technology that has artificial intelligence and machine learning built-in so it can make decisions for you with your direction quickly.
We have a product called purchase signals. What are purchase signals? If I’m running a campaign, there are a lot of variables that go into a campaign. There’s the creative, there’s the offer, there’s the positioning, there’s what websites I advertise on or social media—if it’s Facebook, or whatever. It’s the timing of delivery. It’s the audience that I’m targeting because you could do that in programmatic advertising. It’s the frequency. It’s all of those variables. How can a person make a decision that quickly with data to your point?
Purchase signals are a way to say we’ll feed real-time signals into the machine learning engine, to be able to optimize the allocation of those budgets in near real-time so that it has the best return on investment. If it turns out this creative on these websites to this audience is performing better, then that creative on the same website, but to a different audience, then that’s where the money starts to go.
Instead of a human being having to think that through and spend a lot of their brain and time when things are changing so rapidly anyway. What’s true today may not be true two weeks from now, the machine can do it for you. It doesn’t mean that you’re just sitting there idle, it means you give direction. The data platform is designed to enable all kinds of companies to create applications that will take inputs from clients, will take inputs from businesses, and then they’ll optimize for those.
I want to optimize for new customers. I want to optimize to get my existing customers to spend more. I want to optimize to reduce attrition on the back end. You tell the machine what to do, the data feeds into it. Obviously, insights are available to be viewed and acted on independently of the machine, but the machine can then act on your behalf.
Ben: Sure. Marketers very often have access to a lot of data, or they’re crunching a lot of data and point insights out of it that are certainly going to be helpful for their own purposes, or for their own team or department. Very often, that data achieves its full potential or full value when it’s shared with the entire organization. There might be folks in other areas of the company or other departments that could also make better decisions if they have access to a lot of that data.
A roadblock that marketers often run into is one, figuring out how to even make that data accessible in a way that other people can consume and understand what it means. Two, also getting other people in the organization to care about it.
In your view, what are some of the advantages of breaking down data silos, and making marketing data available to a whole organization is the first part of the question? The second part, how would you advise a company to go about getting buy-in? If they’re running into either—if not resistance, just passive indifference within their organization? How would you advise that they build the case to say, hey, like this data that we have is valuable? We think that departments X, Y, Z should also be looking at this.
Jonathan: Great questions. I have to say, that’s one trend that we’re seeing. Of course, there are always early adopters and early movers. But this idea of breaking down silos and getting not just the marketing department. We’re starting to see—in these early movers—companies that are getting full alignment, this idea of the consumer at the center of the business has always been a story that marketers will tell.
We’re starting to see supply chain line up merchandising within retailers, merchandising, supply chain, customer experience, and real estate. All of the different parts of the enterprise are lining up around this idea of the consumer at the center.
There are two ways that, as a marketer, we can get these other groups to line up. One is, of course, to show them these examples of early movers and the success that they’ve had, and there are a number of them. But it’s also the threat. If you don’t do it if you don’t get the company lined up in that way, you’re going to get surpassed. In this environment of COVID, I think it’s caused a lot of companies to rethink their business models and look at their customer experience. Not just how their ads go out the door, and whether the ad is properly targeted to the right customer, but the whole end-to-end experience when the customer walks in the door. The story I told earlier about personalized experiences is a big part of the story.
The operating teams have to line up in order to create that experience and deliver it. The best way to convince internal groups to line up is to show how the best companies are executing on that, and we’re seeing some really good examples of that.
Certainly, some of the digitally native companies that are emerging, they’re starting from that premise. They don’t have to change their legacy systems to line up. We are seeing tools that make it easier for companies with legacy systems to transition. The typical scenario is the infrastructure makes it so hard for these companies to move. It’s becoming a lot easier now with some of these new tools.
Ben: Sure. The last question, I’ll throw your way. If I’m a marketer and I feel like I’m struggling to produce results and that struggle is directly tied to a downturn that is connected to the pandemic. Maybe they started the year thinking they were going to hit a certain set of numbers. The unexpected happens. Suddenly that’s not maybe looking possible in the way that it maybe did in “quarter one.”
Where would you recommend that marketers start to look to find answers, to help them guide their way forward? Maybe this marketer understands how to use data. Given that we’re in a time where a lot of people don’t feel like they know which way is up anymore, which can make it difficult to know. If you’re even wanting to begin to try to dig yourself out of a hole that you might be in right now, you really might feel like you’re really up a creek right now.
Also, just given that different marketers and different companies could find themselves in all manner of different scenarios. With all of that in mind—and this is going to be a long question—but where would you recommend they start? What’s a basic guiding principle that you could follow to find your own starting points right now?
Jonathan: First we have to distinguish between smaller and larger businesses. I know many of your listeners are smaller companies. What I’m excited about is that there’s this emergence, this democratization of toolsets. The data-driven tool sets that were historically available only to the bigger companies are now available to smaller ones, and that’s fantastic.
It’s almost like the days of computers—big mainframes, minicomputers, and finally, all of us have this massive computing power machine on our desktop and in our hands. Same thing with the tool sets that are helping businesses manage this typical time.
It will not surprise you to tell you that data-driven is the answer. If I was having a difficult time, my first order of business would be to find the most efficient way of getting information that’s the outside-in view of my customers and prospects.
For example, if I have a restaurant in the Southside of Chicago, we can look at the share of stomach for that restaurant. We can see what kinds of customers are coming in or not coming in. If competitors are winning more of that share of stomach, and what do those people look like? How can you, therefore, change your product mix and stories so you attract some of the customers you’re not getting? Are more of my competitors getting the home delivery or the online business than I am?
All of that information is available to you on the dashboard. Imagine turning on your laptop every day logging in, and having this information of what happened last week, or even the last few days—be available at your fingertips. That’s what you need.
Our strategy and approach is to make this data platform—with all of its embedded technology that happens behind the scenes—available to partners, who in turn make available applications to small and large businesses that will allow these tools to be leveraged.
Insights to action is the storyline. I get insight, I get recommendations, and then I choose to act or not act, and I can make decisions. You got to start with a toolset that gives you a view of what your customers are doing, not just in your businesses, but also outside.
Ben: Like I said, that was the last question I had prepared. But before I let you go, is there anything else on this topic that you feel is particularly important that you maybe haven’t mentioned yet, or maybe there’s something that you want to reiterate, just to leave as a parting thought with our audience?
Jonathan: Sure. We talked a lot about businesses’ access to data today. I think the most important thing that we want to keep in mind is data to improve people’s lives.
If everybody orients how they use data. Obviously, you want to be privacy-centric. That’s one element of consumer centricity. We’re at the tip of the iceberg right now, in terms of how data is going to be used to improve people’s lives.
In a commercial context, giving people what they need, aligning them, personalizing the experience, and recognizing them when they come in stores. It is incredibly valuable in terms of building deep, sustainable, long-term relationships and creating an emotional resonance that you want to have with customers.
That’s our mission is to help businesses take advantage of those tools and data, and to ensure that consumers’ lives are improved along the way. We think the best is yet to come as the months and years ahead. You’re going to see some really exciting things.
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