Joe Doran: Good morning, everybody, and welcome to today’s webinar, Data Onboarding: The Cornerstone of Identity Resolution. I’m Joe Doran, the chief identity officer here at Signal. Today’s webinar will explore the art and science of customer data onboarding activation — the key to highly personalized, contextually relevant experiences that today’s consumers demand from all of us.
Onboarding is the process of connecting offline customer data to online identifiers to create a holistic consumer profile. It extends customer engagement, as we know it today, beyond basic targeting and remarketing use cases, enabling real-time content personalization that boosts loyalty and revenue. But onboarding approaches really vary greatly from one identity vendor to another, and those disparities can make the difference between delivering the right message to the right place, at the right time, or delivering a relevant message that’s days too late.
We’re very fortunate today to have some great speaker, including Susan Bidel, Senior Analyst at Forrester, and Tommy Liantonio, CEO and co-founder of ClickCertain. I’m really excited about today’s webinar. But before I pass it off to Susan to get us started, I just have a couple housekeeping items for the audience. One, the webinar is being recorded, and the recording will be sent to all attendees after the session. So, please feel free to make note or to replay this later. Two, all attendees have been muted. So if you have any questions, please time them into the chat pane. Near the end of our time today we’re going to have a Q&A session, and we’ll try to answer all of your questions at that time.
So right now, I’m going to turn it over to Susan to get this webinar started. Susan today is going to really define match rates and discuss why they matter. She’s also going to explore identity’s evolution, and address why it’s so imperative that brands select the identity vendor that most closely aligns with their marketing ambitions, both now and in the future. So I hand it over to you, Susan.
Susan Bidel: Thanks so much, and thanks for having me. I am Susan Bidel, I’m a senior analyst at Forrester, and I cover data, among other things. So today we are going to talk about onboarding as the cornerstone to identity resolution. And I would argue that identity resolution is critical to marketers in order to equip them to be able to deliver those relevant messages that we all expect as consumers. And so, we’re going define identity resolution from Forrester’s perspective, we’re going to look at why identity resolution matters, we’re going to take a little bit of a nitty-gritty look at how it actually happens, and then we’re going to look at the cornerstone of identity resolution, which is onboarding, and who does identity resolution.
Before we get started, though, just for context, let’s be clear that the screen-rich consumers that we all are expect relevance in our advertising and marketing communications. We expect not to see, for example, an ad for a shirt that we bought two or three days ago. That doesn’t serve our purposes as a consumer, and it certainly doesn’t serve the purposes of the marketer because: A. it’s wasted money, and B. it irritates their customers. So underlying that, when you take into account the fact that the average online U.S. adult has 3.5 devices to their name, you can see that trying to tie those devices and online activity to a single person is critical. Marketers are interested in doing it. There are specific companies out there that facilitate it.
Forrester defines identity resolution as the process of integrating identifiers across available touchpoints and devices with behavior, transaction and contextual information into a cohesive and addressable consumer profile for marketing analysis, orchestration and delivery. In other words, figuring out a way to know who owns what devices, and what they do on those devices and when, as a marketer, I have messaged those people on those devices. And it all has to be done in a privacy-compliant manner.
So why does this matter? Identity resolution delivers improved contextual marketing. You can’t know that the person that you’ve been trying to sell a shirt to bought that shirt two days ago unless you know who they are. And so, it’s critical that you build up identity so that you can deliver messages that are relevant.
It also allows for improved data management. So data management is the aggregation, and analysis, and then deployment for marketing of all your data resources. And those can be offline data resources that you will onboard, and we’ll talk about that later, and those can be online data resources that you pick up with the help of a data management platform, for example. And tying all of those keys and data points together into a single data set that is tied to identity will give you much better productivity out of all of your data resources.
It will allow you to better target and personalize interaction. So within the data management platform, if you’re using one, you can use the data resources that you have to not only target your known consumers, but to build models of consumers who look like your known consumers, and then you can target and personalize the interactions that you have with your known consumers, and with consumers who look like them should be good prospects for you.
And then you can get much greater efficiencies through measurement. So if you know who that consumer is who bought that shirt, you can suppress all the ads that are trying to sell the shirt that would be otherwise targeted to the person who already bought the shirt, saving you money, and as I said, not irritating your consumer.
Forrester has a variety of research products where we look at sectors of business. This is called the Forrester Tech Tide, where we assemble and aggregate the opinions of experts within Forrester to identify, in this particular case, what are the martech technologies that we believe are important for marketers, and at what stage they are at. So we have Invest and Maintain, Divest and Experiment. And Invest is really those sets of technologies that we believe are core to some process that we believe is core to the success of marketers. We have identified in this Tech Tide, which we published early this year, that cross-channel identity resolution is critical to customer-obsessed marketing, and by that we mean understanding who your customer is and devising your marketing strategies around that understanding. We believe that those companies that we identify as worthy of investment will deliver or do deliver significant business value to Forrester clients. And we have identified cross-channel identity resolution as critical because we believe that it is moving to the forefront of issues that marketers are extremely interested in tackling.
So we say that identity is on the rise — cross-channel technologies are on the rise. The reason for that is that the Holy Grail for marketers is to be able to plan, execute and measure across channels, and to deliver the messages that they are using to generate business in a coordinated fashion. So understand whether the person is just beginning to be in the market, whether they are looking and doing research on their desktop, whether they plan to buy on their phone, or doing just some comparison shopping, for example. It’s important for the marketer to understand who’s using what device, in order to do what, in order to deliver the right message. And all of this has to be done in Europe — and with European consumers wherever they are in the world — respecting the rules of GDPR, which went into effect in May of this year, and anticipating the rules of the California Privacy Act, which will go into effect in 2020
A slight aside about that is that we believe that the GDPR rules are likely to be edited, perhaps, or revised between now and 2020, and we believe that California’s Privacy Act, which is relatively loose or free-form at the moment, was devised that way so that they can learn from the mistakes and strength of GDPR, and create a law that works for California. And if it works for California, it pretty much by default will work for the United States as a whole.
So this is a little bit more detail on that Tech Tide. As we said, we took a look at cross-channel identity resolution. We consider it a requirement or a requisite for measurement, for accurate targeting, for relevant personalization, for the delivery of the right message, to the right consumer, at the right time, and on the right device. And that really sums it up. You have to know who the consumer is, you have to know what devices that consumer uses, you have to know why and when that consumer uses those devices, and then deliver your message with respect to all those personal pieces of information. It does require holistic planning and investment.
So how does it actually happen? It relies on data keys, and data keys can be anything from your address — that’s probably the most solid, most concrete, most deterministic piece of information that a company could have about you, to your device IDs, to your social handles. There are a variety of different keys with a variety of different levels of certainty about them. And then you, with the help of a company, marketers would identify those keys, would link the keys together, would have a way to understand that Susan has a desktop that she uses, she has a cell phone that she uses, she has an iPad that she uses, and sometimes she uses them simultaneously. When the keys are tied together, it’s possible for the marketer, with the help of these companies, to create identities that are more descriptive, that have an understanding of that behavior that I just talked about, and then use those greater profiles, if you will, in orchestrating those holistic messages or streams of messages.
These are a variety of different kinds of keys. You can see that they are either very broad segment keys, like an IP address, or highly individual, like an email address or secure cookie — specific account details if a company, for example, has you in their CRM database. Because you have done business with them, you have bought from them before, that’s pretty solid first-party data. And then as I said, if you collect all of the metadata together and you analyze that, you’re able to come up with pretty strong profiles of who the individuals are that you’re doing business with.
There are a variety of strengths of identity. They range from the anonymous to the fully-identified. So the anonymous would be a number that is assigned to me based on a collection of anonymous keys to a fully-identified identity based on deterministic data. Clearly, the fully-identified is the more solid, if you will. However, as a marketer, you have to trade in scale for that kind of deterministic data set. So as you require or decide … If you place more importance on deterministic data, your overall pool of consumers is going to get smaller and smaller, and that isn’t always the best strategy for marketers. So you can see that there are a variety of different identities that are extremely useful for marketers.
The cornerstone of identity is onboarding, and by that, we mean taking, for example, your CRM offline data set and using an onboarder to make that data useful in online environments. Onboarding results in matches. And what that really means is that, as I said, you have your onboarding file. It’s often a result of registered users, or loyalty programs, or a combination of those things. And through the onboarding process, the onboarder compares your files, your marketer file with their truth set, which is typically made up of publisher truth sets, direct marketers, credit card companies. So they look to see, does this person — ABC, XYZ, identified as that — match up to what you have, which is in my data set, does that match up with Susan Bidel in your data set? And if it does, it’s a match.
The most important consistent identity across the sets is a match. As I said, it’s based on deterministic data, and cookies are deterministic data, and it’s supplemented with probabilistic data. As a general rule, from an industry perspective, the industry benchmark is roughly 65%. So a marketer with 100,000 names in its CRM file can fairly, if it’s maintained the right cleansing and maintenance of its files, can expect to get a 65% match in the online world.
Match rates matter. They indicate the percentage of the marketers offline file that’s available, so 65% in general. Match rate processes can erode the quality of data over time. So if you’re a marketer and you’re onboarding your data, if you’re an onboarder and you’re going to get 65%, and then you’re going to send that data to a demand-side platform for activation against media buying, you will then incur a second onboarding process, which will sort of winnow that out and have another, let’s just use industry standards, 65%. And so you can see that multiple onboarding processes reduce the usefulness of your original data set. They can, however, improve over time depending upon how they are used. So for example, if you are using a re-targeter, and the re-targeter learns over time the patterns of behavior of some of those entities within your data set, then your match rate will improve over time.
Really, at the end of the day, the only matches that matter are quality matches — the ones that can be reached and served. So the quality of your data set is in how it actually works for you, depending upon what it is that you are trying to do, but for example, if what you’re trying to do is buy media against a targeted set, it’s when your ads reach your consumer.
So who does identity resolution? Forrester has another research product we call a Now Tech, where we take a look at a sector of business that is pretty compelling to our clients and showing a tremendous amount of traction, and we take a look at the set of vendors, and we look at what their strengths are within that sector, what they do, and what we think our marketers and our clients are interested in learning. We published a Now Tech on identity resolution in June of 2018, so just a couple of months ago. Typically, with a Now Tech, we break the vendors up into whether or not they’re large companies, they are mid-sized companies, and they are small companies. And it’s important to note that those designations are based upon revenue in the specific product or service that we are looking at in the Now Tech. So some of these companies, for example, have multiple business units. We are only looking at the business unit that, in this particular case, deals with or offers identity resolution.
And then we looked at the basic disciplines of these companies. Are they onboarders as the cornerstone of their business? Are they first-person PII identifiers? In other words, are they exercising identity resolution based on PII, which might be its personal identifiable information? And that would be an email address, it could be a Social Security number, it could be whatever a person might share with a vendor.
There’s digital identity, and then there’s cross-device linking. So digital identity helps the brands target and personalize across online channels. And then there’s device linking. And you could say that all these are critical to actual identity resolution. Cross-device linking is what I was referring to earlier, and that is knowing whether Susan has a desktop, a cell phone, an iPad, and/or any other device — a game unit, for example — and if so, tying all those devices to one identity.
So we align the vendor solution to the organization’s needs, and we identify the primary function segments of each of these companies. We identify where in the world they operate. I think most of us [in the webinar audience] must be based in the U.S., but many global companies are very interested in this as well. We identify the vertical market focus — what companies do they specialize in working with — and then we give an example of some of their customers.
By working with these organizations, what we say to marketers who are prioritizing identity resolution as key to their customer obsessed cross-channel or omnichannel marketing strategies, our advice is to establish an identity roadmap, understand where you are in this roadmap, where you would like to be, and then identify the vendors within the Now Tech, for example, who can help you move along that path.
Most important of all is to select a cornerstone ID resolution partner. These are the foundational building blocks across categories and use cases, and you need to keep your roadmap in mind, and you need to be realistic about what you can accomplish at each step in that roadmap. When you look at vendors to partner with, we say to marketers that it’s important to know where you are today, but also where you want to go, and which vendor can go there with you.
We always tell marketers to ask as many questions as you can imagine. There are no stupid questions. Ask also to speak to customers, other customers of the vendor to make sure that they are delivering what you need, at least to their other customers, what you need for them to deliver. And then consider vendors with experience in whatever vertical of business you are in, simply because all the vendors working in your vertical will have learned a thing or two from other customers like you, they will know what other companies like yours have … what mistakes you’ve made, what steps they may have taken that they may not have needed to take. So you can leapfrog over them with the benefit of the experience of the vendor. And it also helps you avoid conflicts of interest.
I hope that you have found that interesting and informative. And now, I will turn the webinar control over to Joe.
Joe Doran: Susan, that was an amazing presentation. Every time I hear you speak, I learn something new, and that was just great. I learned so much. And when I think about what U.S. marketers today are on pace to do in spending almost $900 million this year on services and solutions dedicated to solving identity resolution problem, it is absolutely critical that they understand the criteria for selecting the most complementary identity partner. So thank you for that session. And to the audience, we’re recording the conversation so you can play it back later. But also don’t forget that you can submit us questions in the chat pane, so you can ask more questions of Susan and the rest of us as we go forward.
Right now, I’m going to turn it over to a true practitioner in the identity space, Tommy Liantonio, to explore the immense value of the identity graph and how identity resolution represents the engine driving the world’s most powerful brands into the future. So off to you, Tommy.
Tom Liantonio: This is going to be the comedy portion of the presentation, if we will. The only reason I’m on here is because I own a graph, I use a graph, and I profit from a graph. So all you’re going to get from me is war stories. And having done this as long as I have, I can tell you that I’ve made every mistake that you could possibly imagine, all right?
When we started this three and a half-plus years ago, I had no idea what an identity graph was. But I’m one of those guys who reverse-engineer things. So I was looking at Google and Facebook, and specifically, I would ask questions to my partner who is the technologist — he’s the data scientist, he’s the coder — and I would say, “Why are they doing this?” Because I couldn’t understand the process. I wanted to kind of dismantle it, I’m a marketer. So we talked about, for example, why does Facebook allow other companies to use their logins? It was identity resolution. I couldn’t understand Google+, I couldn’t understand a lot of things these companies were doing.
Slide: “Behavioral targeting is now the white meat of marketing. The ability to attach behavior to specific identities is the quiet war taking place in media.” — Scott Galloway, entrepreneur, marketing professor and author of The Four: The Hidden DNA of Amazon, Apple, Facebook and Google.
As you start to dismantle this stuff, it comes right down to it, and the reason I picked this quote is because Google, Facebook, Amazon and Apple are using identity resolution. That’s why they are the way they are. To me, this is really simple. I want to be able to bring in behavior that allows me to use it in a way that I can convert, right? So we’re a performance marketing company. That’s what we do. We don’t close, we don’t get paid, all right? When we built this graph, we didn’t have investor funding. My partner and I put up all the money, so all the mistakes were on my dime. Everything we did, going forward, was us. We didn’t have anybody telling us what to do, because almost everybody in the industry was just as confused as we were. So there weren’t a lot of places you can go to educate yourself, and obviously, we were feeling our way around in the dark.
So I used Google and Facebook — and specifically, Google, Facebook, and Amazon — as my guide, because I wanted to understand exactly what they were doing. And for all intents and purposes, we’ve all used data in some form or fashion, mostly second- and third-party data. But once you overlay the identity onto that data, it becomes extremely powerful. And when I started to look at Google and Facebook and Amazon, I started to realize why, because they knew they had behavior, right? So there’s a part of this [Galloway] book previous to this [quote], in the section on AI, that talks about behavior marketing becoming the future of marketing. And if you’ve done marketing for any number of years, we’ve used personas, right? We’ve used demographic, psychographics, etc. And now all of a sudden, we’re using behavior.
So the first thing I’m going to tell you is that, when most people are using the word “data,” they’re referring to people data, right? Behavior. And it’s important that you do that, because we sell products and services to people. And when you use the word “data,” you’re dehumanizing, if you will, the person, and that’s the last thing you want to do. And when you open your mind to this thought, you’ll start to see different things that you didn’t see before, right?
So for us, as a company, all we were looking to do was market better. That was it. It was nothing complicated. We wanted to be able to get them early in the buyers’ journey, we wanted to be able to get frame control, we wanted to be able to control the conversation, we didn’t want to have to deal with powerful suppliers dictating to us how we were marketing, and we wanted to be able to bring in conversion at a reasonable conversion costs. And then from there, maybe grow the back end. And that was the beginning. That’s how we started.
Where we are today … I’m going to define a couple of words. I’m going to try to stay away from jargon. I hate the industry jargon stuff, I’m not good at it. So for me, in-funnel means somebody who’s on my landing page, inside my collateral in some form or fashion, on my website. I define in-market as somebody who is actively pursuing by either research, keyword search, URL level navigation, pursuing a purchase of what I sell, right? So the vast majority of the stuff that I sell is complex. It’s maybe a three-, four-month sale cycle, sometimes longer. Almost every sale happens offline, but the sale starts online, right?
So for us, having to onboard sales, it was all about onboarding that sale. And it’s more than just onboarding an offline sale. It helps you with the predictive analytics part, because I knew nothing about machine learning when I started, right? I’m not a data scientist. But I understand patterns, I understand that there’s a common path that prospects take.
So once I had the understanding of what machine learning is, and that machines are dumb, and they have to be taught, and the data in the specific example, the specific individual consumer, the path to purchase, the chronological path to purchase is so very critical. So once you feed that into the algorithm, now we start doing that for 10, or 50, or 100, or 500 prospects. You start to see the behavior pattern that leads to a sale. And then all of a sudden, now we’re doing predictive, we’re doing machine learning. And again, when we started was it was very, very basic and now obviously more advanced after three and a half years.
Everybody’s going to have to tap into their Amazon, right? You’re not in the business that you think you’re in. You’re in the relationship business. There’s a saying in digital marketing about building a list — that the money’s in the list. The money’s not in the list. The money’s in the relationship. And if you think about what Amazon’s doing, is they’re just leveraging that relationship. They’re the number one seller of batteries, the number one seller of socks. It doesn’t matter how the relationship starts, what we’re doing with LTV growth — obviously, there are some natural fits on the back end in growing the lifetime value in the relationship with a customer. But we’re extending that, we’re extending it.
I was on a call with a finance publishing company, and I said, “You have five million customers. Do you know how easy it would be for you to onboard those five million customers? And just cross-reference that against car buying behavior. These are your customers, you can send them an email.” And these guys were world-class at lifetime growth, growing the back end. I mean, most of their acquisition, they go dark six months before they see a profit. They’re willing to eat the cost of acquisition, six months. That’s how good they were. It had them changing their whole mindset on how this is going. So for us, where we started is not where we are today. We want to be able to utilize an identity graph so that we can do better machine learning, all right?
So I’m going to give you my definitions of first-, second- and third-party data. Because to me, it’s really simple, right? First-party data is information that I have on my own clients, my own audience. To me, second-party data is buying someone else’s first-party data directly. And third-party data is buying someone else’s first-party data indirectly. Now, you could debate the definitions, I don’t really care. For me, all that matters is how do I get this incredibly important piece of information on my graph? Right? How do I map it to the person?
So, when I talk to companies and they tell me, “Our primary channel is Facebook and Google,” I get it — I get the thought process. But for me, in our company, we talk about Bob. Bob’s a human being, Bob’s a person. That’s the business I’m in. My job is to help Bob make a smart buying decision. My job is to meet him as early as I possibly can in the buyer’s journey. My job is to help Bob figure out everything, right? My job is to build a relationship before I sell to him, because people buy from people. They don’t buy from companies — they don’t buy from websites, right?
So how do I develop a relationship? For me, how I use second-party data and third-party data is using common sense. I look at keyword search, I look at URL-level navigation, I use content, and I ask myself, “What content, if I was looking to buy this product or service, would I be consuming?” And we reached directly out. You’d be surprised how much data is available direct. You don’t have to go through other companies — you can go direct, because that data is worthless after that person leaves, right? They can only show them so many ads when they visit the page. So when they navigate away from the website, if they have your pixel on the page, they can pass you that URL-level information attached to your cookie, which is in your graph, which is basically attaching it to your identity. And now you’re able to start to do all sorts of really cool things in terms of not only just predicting, but knowing what people are doing in the buyer’s journey.
So for us, how we build that trust, because trust is at the heart of all relationships, is that we’re going to help them when they’re doing their research. We’re going to help them when they’re getting their arms around their problem. So if someone’s buying a car… we do business and legal, we’ve done clinical trials, we’ve done things in the drug rehab space, we’ve done things like cruises, mortgages, real estate. People do research, right? And when they research, they’re not looking for solutions, yet, they’re looking for problems, right? They’re trying to get their arms around “Well, do I have a problem? How big is my problem?” And then they start looking at solutions. That still doesn’t mean they’re reaching out to us, right? They’re researching their solution options. What are their alternatives? It’s not until they get through that, where they can actually now start to interview solutions, that they come to your page.
So for us, we use all of our first-party, second- and third-party data in helping us start to build out that path to purchase. Because the more information I have about that person, the better I’m going to be able to do business with them, the better I’m going to be able to help them navigate their information search and build that trust.
Here’s a simple example. Somebody comes to your website, you drop a cookie on them. That person comes back the next day — let’s say, day one, they come to your website from their desktop. Tomorrow, they come from their laptop. Without having an identity graph and the device connected, you’re not going to know how that person got your website. You have to have that cross-device connection to start to understand some of the basic fundamentals of just retargeting even. And I’m sure a lot of you guys already understand this, but for us, when we start to look at the paths, the total number of paths that people take to a purchase, it’s like looking into a spaghetti bowl.
I mean, there’s a million different ways that people navigate. People are across two, three, four devices in a day. And I’m not going to give you stats, but there’s a lot of smart people predicting a heck of a lot more than four devices. In North America, they predict in 2021 that people are going to have 13. Now, that’s an interesting thing. But if I have a graph, I know that guys like Signal are going to make sure that I have every device ID I need to be able to do business with them wherever they go, and however they navigate their journey, right?
So for me, it’s about having the right partner in place to be able to do what I call true cross-device resolution, because it has to be deterministic. And it has to be something that if we’re onboarding an offline sale, that I have to be able to tie back, and I have to know that this actually had value to the conversion — otherwise, we’re just playing around. And so in the process of three and a half years in doing this, like I said earlier, there’s a lot of fugazis, a lot of phonies, there’s a lot of wannabes, a lot of pretenders, and we kissed a ton of frogs along the way. And as I said, I spent my money and I got it wrong. And so the biggest thing that I can tell you about the partner concept of who to do business with is this: You’re going to need somebody for both today and tomorrow. So today is pretty clear, you’re going to know what you need. But you cannot use the past or even the present to predict the future, right? It’s all going to change. What we don’t know, we don’t know.
So when I started this journey, I was going to my vendors, and I was talking to them as if they were actually interested in helping me. We had to find a strategic partner, a strategic solution partner, because tomorrow I’m going to wake up and I’m going to have a problem that I didn’t anticipate today. That’s an absolute guarantee. And if you don’t have a company that’s going to help you piece that together, it’s not just about owning a graph, okay? And towards that end, if somebody’s selling you something that boxes you in or restricts you, you’re in trouble. It’d be great if at the end of this, you get yourself a graph, and I obviously think you should have one.
But it’s not enough just to have a graph. You have to have the right graph. You have to have the right person providing all of this back-end technology. And for me, having the right partner is everything. And I use the word “partner.” When we started two and a half years ago, it was a hodgepodge of solutions. That’s not the case anymore. So for me, having the right partner relationship is critical. When I spoke to Signal, I asked them very specific questions about my needs. I didn’t care about their products, right? Because if their products didn’t solve my problem, I needed them to have a solution for my problem, right?
So that was critical for me, and I cannot stress that enough. Having a graph where the use case restriction is wide open… again, I’m going to say this and I don’t really care what anybody thinks, this is just the fact, and I know this is a fact because I own a graph and I use a graph. I promise you, there’s going to be things that are going to come up tomorrow and you’re not going to know what to do. And you better have somebody at the other end of the phone who’s not only going to take the call, but help you solve the problem. So having restriction boxes you in. You want to be working with someone who sees the relationship as a partner and not a vendor, all right?
The last thing, variable cost. For me, having fixed costs for us as we grew the graph and as we grew the usage on the graph, our costs come down. Having that ability obviously ends up on the bottom line for us. And again, when we started this, it was very, very restrictive, but it was also very expensive because it was variable. The only example I can give you is if somebody were to charge you on usage, right? And now you’re using this thing and you’re doing well, you’re converting, you want to do it more. Well, it’s going to cost you more. And it’s kind of counterintuitive if you think about it. So it was one of the things that I really, really liked about having a fixed cost was that I made a huge investment in my graph. The last thing I want to do is use less, I want to use it more, and I want to come up with more creative ways. Well, I got to tell you, it’s an absolute relief to know that I don’t have to sit here and calculate what’s this going to cost us, because I already paid the fee. The more I use it, the more value I’m getting out of it. So again, those are important things that you should take a good look at.
I’m going to give you an example of selling a car. If you owned the car dealership, I would have you onboard your existing clients. We’re going to map it to the graph. What are we going to do with that? As I said before, I build out path to purchase, right? So we bring in second- and third-party data. And again, how do we get it? Money — dirty green paper — and we link it to the graph, meaning when we bring in this behavior, URL-level navigation, keyword search, content consumption. When we bring this in, it’s not anonymous behavior, right? Our behavior database is tied to an identity now. So I’m bringing in Bob’s auto-buying behavior, let’s say.
Let me tell you, there’s a lot of places you can buy directly, and it’s all there. And if you have any doubts, obviously, you’re on this call, you know how to market, you just look at the keyword searches, right? Google ranks URLs, there’s companies right there. Will they all do business with you? No. But here’s the thing. When somebody leaves a website, they’re no longer a value to that publisher, unless they have identity resolution. And they don’t have to have a graph, they just have to be willing to drop your pixel and pass you that piece of information with that cookie ID, and it’s so you can match it back to your graph, and you’re off to the races.
So we build out a path to purchase, right? Because at the end of the day, all machine learning is prediction — using information you have to generate information you don’t have. I don’t need to have every single piece of behavior to predict somebody buying a car to be able to do it highly accurately. And I’m going to show you a little tip here in a second where you can leverage Google and Facebook to do it. We put a pixel on our client’s website. We onboard the sale, we onboard all their past sales, and we sync it to the graph. So if any of their existing customers dip a toe, and are in-market doing research, what do we do? We notify our client. So we prevent migration. That’s number one, right?
What else can you do now? Well, if I’m protecting the home for the dealership, now I got to steal customers from other dealerships, right? They call it “conquest”. So I’m looking at the behavior of non-customers. All we’re doing is predicting based on the behavior that matches a previous buyer. So what does that mean? Let’s say Joe buys a car, and he’s one of the people that I’m tracking through my database — through my graph, I build out Joe’s path to purchase. That’s the training sample that I’m going to feed into the algorithm. You do that for a couple of hundred sales, and you begin to build out a behavioral profile — a chronological behavioral profile.
So as my individual behaviors come in, and I’m buying my second- and third- party data, when that comes in, all I’m doing is using that to predict which one of these people are going to be in-market, and run ads. If they buy offline, obviously that’s the ultimate goal. But in the short term, we’re just measuring. And that’s closed-loop analysis. All we’re doing is predicting — measuring that prediction by running ads to that prediction. And we measure it off the pixel, and then we feed that result back into the algorithm, and we make a new prediction, and it’s a flywheel. And as flywheels go, they pick up speed and start moving on their own. They’re able to produce highly accurate predictions.
But even if you don’t want to get that crazy, it’s simple. I put a pixel on a page: my dealership is driving traffic to that page every day. All I have to do is take that first-party data and go to Google or Facebook, and now I get to ask them for a behavioral lookalike, which is the tip I’m recommending to everybody. You’re priming the pump for them to be able to give you the behavioral lookalike. And so in all of our case studies, obviously, Google and Facebook are tremendous at this. They have way more data than everybody else. And Amazon does this now. There’s a lot of companies that are offering behavioral lookalike.
Again, for the person who visits the page — the in-funnel — we’re sub-segmenting. We’re using a variable inside our pixel, and we’re breaking out which one’s looking at the Q5, and which one’s looking at the Q7 if it’s an Audi dealership, for example, and we’re segmenting and obviously doing the basic fundamentals of market message to that person. But one of the biggest mistakes that I see companies make is that there’s demand generation, and then there’s a whole world of demand that’s already out there, and they’re not leveraging the low-hanging fruit of the existing demand. Think about it. If somebody is in-market, actively pursuing the purchase of an Audi or a competitive car, or if they’re in-funnel, that person’s the greatest probability of profits — the quickest path to profits, the best use of resources for profits, and probably the largest opportunity today for profits.
All these things that we’re talking about, I can only do because I have a graph, and that’s it. If you don’t have a graph, how do you compete? So it sounds phony when I say this to people. I know you can hear it in my voice — I get into this. Because as a business owner, you wake up in the middle of the night, you’re staring at the ceiling and you’re asking yourself, and everyone’s asking the same questions, “How do I grow profits?” I need a competitive advantage, and for me, simple blocking and tackling. If I know before a competitor, and I can build a relationship, I have a chance of controlling the perspective. I can set the buying criteria. I can define what value is. And if I can grow that relationship, because I own the ability to target, and I can onboard that anywhere I want, I own and control that. So that means that I can have the conversation anytime I want, on any topic I want.
There was a study about multi-channel campaigns. “You’ve seen 100 ads in the last 24 hours — name one.” And when I ask that to people and I shut my mouth, which is very difficult to do, I get crickets. And the reason is because people forget, and it’s a basic fundamental for us in our company is we just know that people cannot act on what they forget.
Now, is there a diminishing return by doing too many ads? Of course. Obviously, you guys know what you’re doing. But in today’s day and age, [we know] behavior on everybody, 24 hours a day, seven days a week, no matter where they go. And now you have to have a system, a tool to be able to make sense of that.
And so knowing who to advertise to, or how long before you should wait before you should show it to them — being able to do omnichannel, all the basic stuff that everybody would love to do, it’s all built off of a graph. I don’t have a dog in this hunt, I have no skin in the game here other than that we got our ass kicked and I wouldn’t want to see anyone else have to go through what we went through. Everybody needs to have a graph, period. And when I came to Signal, my rep is Juan Molina — good salesman, very attentive, doing his job, and I had that conversation with other people. So everyone puts their best foot forward. All I can tell you is, every step of the way, he did exactly what he said. And for me, having gone through everything that I’ve gone through, that meant a lot.
The second thing is that once we got introduced to the team, I didn’t have off-the-shelf problems. I had very specific wants and needs that I wanted, and they met them. So it’s like every chance they had to disappoint me, they didn’t. They went the opposite direction — they blew us away. So you need the right partner.
The question is, do you need it right now? There’s a Forrester quote that I put on my walls: by 2020, companies who effectively master AI will steal $1.2 trillion per year from those who don’t. Not win, steal. it’s going to be that easy. If you’re not going to have this and the company that you’re competing against does, they have a competitive advantage. They are going to have sustainably higher profits than you. If I can spend more to acquire a client, how are you going to beat me? You can’t.
So the reason they had me on here is because I own a graph. I think you all should on a graph, and I think you should all give Juan a call, I really do. From the bottom my heart, every fiber of my being, you need to be doing business, and if you’re going to do business, it should be Signal. That’s it.
Joe Doran: Tommy, thank you so much for sharing those insights. That was incredible. Your experience as a practitioner in this space speaks volumes about the dramatic role that data onboarding and identity really play in a business success. And you clearly outlined some formidable challenges that are ahead for brands that are trying to really get to where you’re going today, and really drive their own identity journey.
First and foremost, identity — as you heard from both Susan and Tommy — is a journey. You should map out your plan of where you’re going to start, and when you’re going to start, and how you’re going to grow and build against that business. We see this every day with our clients. And the good thing for us is that we can meet you where you are in your identity journey, and help you move that forward. And as we talked to a lot of brands and marketers, they all have very, very common challenges when they think about what’s happening here, and you heard this in buckets from Susan and Tommy today. Brands and businesses just need to move at the speed of their customer. Susan was very clearly articulate in the case of “Hey, if I buy a shirt, why am I still getting retargeting ads for up to a week after I bought a shirt?”
A brand needs to think about their purchase cycle, and how quickly they need to act against the data and behaviors that they’re seeing, so that they can actually move at the speed of their customers. If they see an intent or a signal from a customer, they need to onboard and activate against that data. They need to do it minutes, not in days.
Brands also need to find real customers, not cookies. And really, I’m just going to steal what Tommy said: you need to market to Bob. And marketing to Bob, a real person, is so much more productive and will drive a better ROI for you in building your relationships with your brands.
The data that you have on your customers is your gold. And brands really need to own and control their own data, and they really need to own and control their own relationships with their customers that Tommy spoke so eloquently about. And you can’t do that in unless you have control and understanding of how your data is being collected, how it’s being stored, how it’s being shared — and you have to have trust in the partners that are there for you.
When we think about Signal, we have three differences. It’s speed: we onboard at the pace of minutes, not weeks, so that you can actually match your purchase cycle with your customers. When we talk about accuracy, as Susan said at the middle and the end of her presentation, in onboarding, it doesn’t matter if you’re matching to a record, unless you can actually make that addressable and reach that consumer. We pride ourselves in having the best accuracy in the industry, as well as control. We give our marketers full transparency and control of the data that’s there — we help them build the graph for them and allow them to use it.
When you talk about the match rates, the industry average sits at about 65%. When we start with those emails or persistent identifiers from the customer’s CRM files, we see match rates at and above the industry benchmark at 65% to 80%. A lot of our customers are the high end of this. But more importantly, as Susan mentioned, match isn’t worth anything unless you can actually address that consumer in media. So we see 95% addressability of those match rates with our customers at the activation points — the DSPs, those points of distribution that the customer actually has. It’s a journey, and we can go and work with you.
There have been a lot of questions that people have provided to us, and we want to just dive into the Q&A right now. Susan, based on your research and observations, where are most B2C brands at in the respective journey on identity resolution? And what are some of the common missteps that brands are making on this journey?
Susan Bidel: According to my research and my observations, I would say that there is not a B2C marketer out there that isn’t aware of the fact that they would be better at what they do — meaning connecting with their consumers and best prospects — if they knew more about who those customers were, and therefore, were able to model out who the prospects were. The real challenge for them is how much first-party data do they have on their own customers? So there are certain categories of B2C marketers who are more well-endowed with first-party data: I think about retailers, travel companies, financial services companies that have abundant first-party data. There are other companies like consumer package goods — for example, Coca Cola. On the one hand, they could think that almost every adult is a potential consumer of theirs. On the other hand, they don’t have any specific information about any of those customers, because nobody goes to cocacola.com to buy a Coke, or to do any research about Coke. So that’s the spectrum of first-party data that they have.
The other big challenge — and I would say that this is a real frustration — is that those that do have any first-party data are frequently collecting that data in different silos in their organization. So they may have an email program or a loyalty program. They may have a list of customers in a CRM file. And those two lists are not aggregated in a uniform manner. So the email address might be, on one, email@example.com, whereas another one might be firstname.lastname@example.org. And because their files are not cleansed and well maintained, they’re going to hit stumbling blocks from the very, very beginning. That’s the single biggest mistake that is completely within the hands of marketers. They should spend time cleansing and de-duping their own data.
Joe Doran: Yeah, Susan, that’s an outstanding point. We see that all the time with brands as they bring together multiple sources of information and data collection together. I want to build upon the comments that you made, and really circle back to your statement on identity resolution requiring holistic planning and investment. And I really want to pick your brain on how are brands measuring the success of these efforts for the brands that are on this journey today, and they’re moving in this direction, and they’re planning against this. How are they measuring success against those investments?
Susan Bidel: Well, the ultimate measurement of success is whether your top line and your bottom line are moving up — whether you’re selling more product or service, quite frankly. But there’s a less sort of tangible measurement, and that is how do your customers and prospects feel about you? Do they regard you as a company that respects who they are and delivers messaging that is appropriate to you at the point in your acquisition journey? And so the relationship between the customer and the brand is one that delivers value and does it respectfully. And I think those kinds of measures are extremely important. And when they’re positive, they lead to long-lasting relationships and bigger baskets.
Joe Doran: Absolutely. I wholeheartedly agree with that, because a consumer’s putting great expectations on the brands that they know them without actually explicitly telling them that “You should know me.”
Now, Tommy, to you, I was just thinking about this from a brand’s point of view in terms of really digesting all the information you gave them and putting it in context. What does ClickCertain understand about identity graphs and data onboarding that you think most brands don’t, or that they would probably struggle with?
Tom Liantonio: Obviously, there’s a lot of pieces to that. Everybody has to start really seriously upping their data collection, data cleaning, data analyzing, and data utilization. I go back to Bob. You sell products to people, and when people say to me, “We’re customer-centric” — well, guess what, if you’re not doing something like an identity graph, then you are not customer-centric enough, period. When people ask me, “What should I do first?” I tell them “You need to get going. And it’s going to be a journey.” There’s going to be a lot of things that you’re going to do and have to do, and it’s going to be piecemeal in the beginning as you learn it. I could probably talk for two hours about all the things I learned, and I’d still probably would leave people with some gaps. You’re going to have to have a graph to really understand.
Almost every single day, I’ll have a conversation with someone who has information I want. Think about that. That information, all I have to do is map it to my graph, and then figure out a way. So data plus data equals insight. I’m making better decisions because of my graph. You need to get started today. You’re falling behind. And here’s the thing: forget falling behind — it’s the opportunity. You’re really talking about a structural change in business, right? it’s not going to be the same.
The last greatest, biggest business breakthrough was the internet. Now we’re talking about the Internet of Everything, a trillion sensors. It’s mind-boggling, I’ll give you stats. I’ll share this with you, Joe: when I first started doing this, I met with a consultant, a futurist, and he gave me a piece of advice. He said that “If you can do it, someone else can do it. Don’t fall in love with your tech.” Meaning, just because you built it, it doesn’t mean someone else can. So I would say to my clients like, “Look at me, if I have this.” Think about that. I’m not diminishing who we are, but if I can have this, you better pray your competitor doesn’t.
The first question I ask companies is, “If you were competing against me, tell me how you can beat me. I’d like to know.” And the answer is, it’s going to be very difficult. Because if I know more than you, Joe. I have the upper hand. That’s a secret to business — knowing something that others do not know.
Joe Doran: Yep. That is a fantastic point. So when you’re talking to a brand that continues to drag their feet on investing in building the graph, what is going to happen to them? Their business is going to go to somebody else, to somebody like you, or they’re just going to lose it to their competitors?
Tom Liantonio: Extinction. I really mean it. I mean, the 2020 quote, effectively stealing — this is zero sum.
Joe Doran: Yep.
Tom Liantonio: It’s the outcome economy. That’s it. If you can’t produce an outcome better than I can, how do you beat me?
Joe Doran: Yep. Great insight, Tommy. Susan, I’m going to have the last question directed towards you. Building upon what Tommy just said, what counsel or guidance could you offer brands to help them avoid the fate that Tommy just described?
Susan Bidel: I think that brands need to get their arms around who their customers are, and build on that knowledge to identify who their best prospects are, and to deliver to both those segments the most compelling and relevant messaging to build relationships and sell products and services. Now, the first thing that they need to do is to take an inventory in the house of what they actually have in terms of data resources. Then, they need to make a real plan about where they want to go, and then the very realistic step between where they are now and where they want to be, and what kind of change, and at what pace of change, their company can accommodate. And then they need to talk to all of the vendors that they would need to facilitate that roadmap. And they need to be as pedantic, if you will, in the questions they ask.
So a lot of this it’s complicated, and a lot of marketers who are not used to this kind of thinking, don’t know what questions they should be asking. And so my advice to them is ask every question that pops into your head, and then ask more. It’s your money, and you need to be quite clear about how you’re going to spend it and with whom.
And then look for a company that understands where you are now, understands the challenges that you are inevitably going to face as you shift your marketing strategies, and understands where you want to go and can go along that road with you.
Joe Doran: Yep, I totally agree, Susan. I would add that I would ask them to do a lot of research on Forrester, and all the documents, and all the research that you guys have actually produced, because I think that’ll help them tremendously.
So we’ve gone about 15 minutes over. I apologize for going a little bit long, but this was a great, great topic. We have a number of questions that we have not been able to get to from the audience. And I’ll just rest assure everybody that Tommy’s favorite rep Juan Molina and the rest of the Signal team, will be following up with you after the session to answer all of your questions. And I want to thank Tommy and Susan for your time and your great insight and experiences that you shared today. It was very invaluable to the audience. And with that, I’m going to conclude the webinar. Thank you very much. Have a great day.
Susan Bidel: Thank you.
Tom Liantonio: Thank you.