The authors of Customer Data Platforms join my friend Russ Artzt, co-founder of Computer Associates, to talk about CDPs and the new book on the Datavana podcast, hosted by Jaime Muirhead
Great conversation about CDPs with Vala Afshar and Ray Wang, hosts of DisrupTV on CDPs with my co-author Martin Kihn (starts at 22:33).
I’m very excited to announce a new book I have written with Martin Kihn, which is the first book on the customer data platform (CDP) category, a very hot topic in advertising and marketing technology right now! Look for it in November 2020, from Wiley. Pre-order the hardcopy here.
Marketers are faced with a stark and challenging dilemma: customers demand deep personalization, but they are increasingly leery of offering the type of personal data required to make it happen. As a solution to this problem, Customer Data Platforms have come to the fore, offering companies way to capture, unify, activate, and analyze customer data. CDPs are the hottest marketing technology around today, but are they worthy of the hype? Customer Data Platforms takes a deep dive into everything CDP so you can learn how to steer your firm toward the future of personalization.
Over the years, many of us have built byzantine “stacks” of various marketing and advertising technology in an attempt to deliver the fabled “right person, right message, right time” experience. This can lead to siloed systems, disconnected processes, and legacy technical debt. CDPs offer a way to clear out the cobwebs and easily solve for a balanced and engaging customer experience. Customer Data Platforms breaks down the fundamentals, including how to:
Understand the problems of managing customer data
Understand what CDPs are and what they do (and don’t do)
Organize and harmonize customer data for use in marketing
Build a safe, compliant first-party data asset that your brand can use as fuel
Create a data-driven culture that puts customers at the center of everything you do
Understand how to leverage AI and machine learning to drive the future of personalization
Orchestrate modern customer journeys that react to customers in real-time
Power analytics with customer data to get closer to true attribution
In this book, you’ll discover how to build 1:1 engagement that scales at the speed of today’s customers.
Proud to announce that my book, Data Driven, has won the 2019 Silver medal for best Business Technology book!
In August of 2007, Jenkins Group launched the Axiom Awards, “recognizing and promoting the year’s best business books.” Now, 12 years later, they have announced the winners of the 2019 Axiom Business Book Awards, honoring this year’s best business books, their authors, and publishers.
The Axiom Business Book Awards are intended to bring increased recognition to exemplary business books and their creators, with the understanding that business people are an information-hungry segment of the population, eager to learn about great new books that will inspire them and help them improve their careers and businesses.
If you want to learn about data, Chris O’Hara is the right person to ask. O’Hara, who leads global product marketing for Salesforce Marketing Cloud’s suite of data and audience products, is a big believer in the data revolution—but first, marketers need to take stock of what data they actually have.
“Some marketers think they have way more data than they actually have, and others think they don’t have a lot of data but actually do,” O’Hara said.
Before joining Salesforce, O’Hara was at Krux, the data management platform that Salesforce acquired in 2016, working on data marketing. In October, O’Hara, along with Krux alums Tom Chavez and Vivek Vaidya, released a book, “Data Driven,” which dives into how marketers should think about using data to overhaul customer engagement and experience.
Before the book’s release, Adweek talked with O’Hara about the book and about how marketers can leverage the data they have while keeping data privacy and consumer trust in mind. A portion of that conversation, which has been edited and condensed for clarity, is below.
Adweek: A lot of marketers have talked about the importance of getting better at explaining to consumers what exactly is being collected and how exactly data is being used. Do you think it’s the responsibility of tech and advertising companies to explain that to the public?
Chris O’Hara: Marketing is better when you have the permission of consumers. Consumers are entitled to know exactly how their data is being used, and consumers are absolutely entitled to have control over their own data. As you talk about the opportunities to get more personalized with customers, you’re allowed to deliver great personalization if the customer has opted in for you to do that on their behalf. If you do that without their consent, it feels creepy and wrong, right? It’s common sense. We’re always going to lead with the idea that trust comes first and that marketing is better with consent. Period.
You write in your book that the biggest risks of harnessing data are centered around privacy, security and trust. As concerns about data privacy grow, and as data breaches continue to occur, how does the industry best rebuild trust with the public? Where does the industry start with reestablishing trust and maintaining trust with consumers?
It’s all based on permission and an opted-in consumer. I like getting advertising messages that are relevant. When I am shopping for a car and I give Cars.com permission to introduce me to new models and send me an email every week, I appreciate it because I’ve asked for it. When I engage with certain sites on the web, like The Wall Street Journal, where I pay for content, I trust them with a certain amount of my data so they can make my reading experience better. That’s the way it should have been, always. Unfortunately, there are some companies in the space that have taken advantage of little oversight to do otherwise. But what we’ve seen in the market is that companies that are not leading with trust are not being valued as highly or perceived as more valuable than companies that do put trust at the center of their relationship with customers.
What’s the biggest misconception marketers have with data?
Something we write about in the book is that some marketers think they have way more data than they actually have, and others think they don’t have a lot of data but actually do. One of Pandora’s svps, Dave Smith, came to us and said, ‘I have one of the biggest mobile data assets in the world. Everyone who uses Pandora is logged in, so we know so much about our customers: what kind of cellphone they have, what kind of music they like, perhaps the ages of the kids in their home, when they listen.’ That’s a lot of data. Pandora probably has one of the largest data assets in the entire world. But Pandora doesn’t know when people are going to buy a car or people’s incomes, necessarily. They don’t know when you’re planning on taking a family vacation. So they turned to second- and third-party data to enrich their understanding of consumers.
According to Blue Kai, I’m a tech-savvy, social media-using bookworm in the New York DMA, currently in the market for “entertainment.” At least that’s what my cookie says about me. Simply by going to the Blue Kai data exchange’s registry page, you can find out what data companies and resellers know about you, and your online behavior and intent.
In this brave new world of data-supported audience buying, every individual with an addressable electronic device has been stripped down to an anonymous cookie and is for sale. My cookie, when bounced off various data providers, also reveals that I’m male (Acxiom), have a competitive income (IXI), three children in my family (V12), a propensity for buying online (Targusinfo) and am in mid-management of a small business (Bizo). I’m also in-market for a car (Exelate) and considered to be a “Country Squire,” according to Nieslen’s Prizm, which is essentially a boring white guy from the suburbs who “enjoys country sports like golf and tennis.” Well, I’m horrible at tennis, but everything else seems to be accurate.
As a marketer, you now have an interesting choice. Instead of finding “Country Squire” or “Suburban Pioneer” on content-specific sites they’re known to visit, now I can simply buy several million of these people, and find them wherever they may be lurking on the Web. This explains why you suddenly see ads for BMWs above your Hotmail messages right after you looked at that nice diesel station wagon on the VW.com Web site.
Today’s real-time marketing ecosystem works fast and works smart. But, how do you decide whether to buy the cookie or the site?
Most marketers insist that audience buying is meant for performance campaigns. This is largely a pricing consideration. Obviously, if I want to sell sneakers to young men, it makes sense to buy data and find 18-35-year old males who are “sneaker intenders” based on their online behavior and profile, and reach them at scale across the ad exchanges. Combined data and media will likely be under a $4 CPM, and probably less since both the data and media can be bid upon in real time. For most campaigns with a CPA south of $20, you need to buy “cheap and deep” to optimize into that type of performance. It sounds pretty good on paper. There are a few problems with this, however:
What are they doing when you find them?
OK, so you found one of your carefully selected audience members and you know he’s been shopping for shoes. Maybe you even retargeted him after he abandoned his shopping cart at footlocker.com and dynamically presented him with an ad featuring the very sneakers he wanted to buy, and you did it all for a fraction of a cent. The problem is that you reached him on Hotmail and he’s engaged in composing an e-mail. What are the chances that he’s going to break task and get back into the mind-set of purchasing a pair of sneakers? Also, what kind of e-mail is he composing? Work? A consolation note to a friend who has lost a loved one? Obviously, you don’t know.
Maybe you reached that user on a less than savory site, or perhaps on a social media site where he’s engaged in a live chat session with a friend. In any case, you have targeted that user perfectly—and at just the wrong time. This type of “interruption” marketing is exactly what digital has promised us it wouldn’t be.
Perhaps a better conversion rate can be found on ESPN.com, or a content page about basketball, where that user is engaged in content appropriate to the brand.
How do you know where the conversion came from?
Depending on your level of sophistication and your digital analytics tool set, you may not be in the best position to understand exactly where your online sales are coming from. If you’re depending on click-based metrics, that is even more true. As a recent comScore article points out, the click is a somewhat misleading metric. Put simply, clicks on display ads don’t take branding or other Web behavior into account when measuring success.
Personally, I haven’t clicked on a display ad in years, but seeing them still drives me to act. Comparing offline sales life over a four-week period, comScore reports that pure display advertising provides average lift of 16 percent and pure SEM provides lift of 82 percent—but search and display combined provide sales lift of 119 percent. So you simply can’t look at display alone when judging performance—and you have to question whether you’re seeing performance lift because you’re targeting, or because your buyer has been exposed to a display ad multiple times. If it’s the latter, you may be inclined to save the cost of data and go even more “cheap and deep” to get reach and frequency.
How do you value an impression?
Obviously, the metric we all use is CPM, but sometimes the $30 CPM impression on ESPN.com is less expensive than the $2 RTB impression from AdX. Naturally, your analytics tools will tell you which ad and publisher produced the most conversions. Additionally, deep conversion path analysis can also tell you that “last impression” conversion made at Hotmail might have started on ESPN.com, so you know where to assign value.
But, in the absence of meaningful data, how do we really know how effective our campaign has been? I believe that display creates performance by driving brand value higher, and some good ways to measure that can now be found using rich media. When consumers engage within a creative unit, or spend time watching video content about your brand, they’re making a personal choice to spend time with your message. There’s nothing more powerful than that, and that activity not only drives sales, but helps create lifetime customers.
For today’s digital marketer, great campaigns happen when you understand your customer, find them both across the Web and on the sites for which they have an affinity—and find them when they are engaged in content that’s complementary to your brand message. Hmmm . . . that kind of sounds like what we used to do with print advertising and direct mail. And maybe it really is that simple after all.
Chris O’Hara is svp of sales and marketing for Traffiq. He may be reached through his blog at Chrisohara.com.
COLOGNE – At Salesforce, the acquisitions keep on coming, most recently that of AI-powered marketing intelligence and analytics platform Datorama. The company’s ongoing mantra is “integration” and it seems to have no shortage of assets to leverage in that quest.
It all stems from what Chris O’Hara, VP, Product Marketing, calls the “fourth industrial revolution” led by things like data, AI and the internet of things.
“It’s harder for marketers to deliver personalization at scale to consumers and that’s the goal. So everything we’re doing at Salesforce is really about integration,” O’Hara says in this interview with Beet.TV at the recent DMEXCO conference.
By way of examples, he cites the acquisition of ExactTarget about four years ago with the intention of making email “a very sustainable part of marketing, such that it’s not just batch and blast email marketing but it’s also your single source of segmentation for the known consumer.” The end result was the ExactTarget Marketing Cloud Salesforce Integration.
In late 2016, Salesforce bought a company called Krux and within six months had morphed it into Salesforce DMP. It was a way to assist marketers in making sense of households “comprised of hundreds of cookies and dozens of different devices” and aggregate them to a single person or households “so can get to the person who makes the decision about who buys a car or what family vacation to take,” O’Hara says.
Salesforce DMP benefits from machine-learned segmentation, now known as Einstein Segmentation, to make sense out of the thousands of attributes that can be associated with any given individual and determine what makes them valuable. Developing segments by machine replaces “you as a marketer using your gut instinct to try to figure out who’s the perfect car buyer. Einstein can actually tell you that.”
In March of 2018, MuleSoft, one of the world’s leading platforms for building application networks, joined the Salesforce stable to power the new Salesforce Integration Cloud. It enables companies with “tons of legacy data sitting in all kinds of databases” to develop a suite of API’s to let developers look into that data and “make it useful and aggregate it and unify it so it can become a really cool, consumer-facing application, as an example.”
Datorama now represents what O’Hara describes as a “single source of truth for marketing data, a set of API’s that look into campaign performance and tie them together with real marketing KPI’s and use artificial intelligence to suggest optimization.”
In addition to driving continual integration, Salesforce sees itself as “democratizing” artificial intelligence, according to O’Hara. “There’s just too much data for humans to be able to make sense of on their own. You don’t have to be a data statistician to be able to use a platform like ours to get better at marketing.”
This interview is part of a series titled Advertising Reimagined: The View from DMEXCO 2018, presented by Criteo. Please find more videos from the series here.
Good time with the Canadian Marketing Association digging into data management!
Currently, marketers don’t have a single source of truth about their consumers. Tomorrow, there must be a single place to build consumer profiles with rich attribute data, and provisioned to the systems of engagement where that consumer spends their time.
At a recent industry event, we heard a lot about the upcoming year in marketing, and how data and identity will play a key role in driving marketing success.
As a means to master identity, some companies have heralded the idea of the customer data platform (CDP), but the category is still largely undefined. For example, many Salesforce customers believe that they already have a CDP. The reason? They have several different ways of segmenting known and unknown audiences between a data management platform (DMP) and CRM platform.
In an article I wrote here last year, I introduced a simple “layer cake” marchitecture, describing the three core competencies for effective modern marketing. In such a fast moving and evolving industry, I have since refined it to the core pillars of identity, orchestration and intelligence:
With this new marchitecture, brands have the ability to know consumers, engage with them through each touchpoint and use artificial intelligence to personalize each experience.
Mastering each layer of complexity is difficult, requiring an investment in time, technology and people. Lets focus on perhaps the most important – the data management layer where the new CDP category is trying to take hold.
The next wave of data management
By now, it’s safe to say marketers have mastered managing known data. A few years ago, when I was working for a software company that also managed postal mailing lists, I was astonished at the rich and granular data attached to mailing lists. There is a reason direct mail companies can justify $300 CPMs – it works, because direct marketers truly know their customers.
After joining Salesforce, I was similarly awed by the power to carefully segment CRM data, and provision journeys for known customers spanning email, mobile, Google and Facebook, customer service interactions and even community websites.
How can we get to this level of precision in the world of unknown (anonymous) consumer data?
As marketing technology and advertising technology converge, so must the identity infrastructure that underlies both. Put more simply, tomorrow’s systems need a single, federated ID that is trust-based. Companies must have a single source of truth for each person, the ability to attach various keys and IDs to that unified identity, as well as have a reliable and verifiable way to opt people out of targeting.
Let’s take a look at what that might look like:
This oversimplification looks at the various identity keys used for each system and the channels they operate in. Today, the CRM is the system of record for engaging consumers directly in channels like direct mail, email campaigns and service call centers. The DMP, on the other hand, is the system of record for more passive, anonymous engagement in channels like display, video and mobile.
When consumers make themselves known, they “pull” engagement from their favorite brands by requesting more information and opting into messaging. At the top of the funnel, we “push” engagements to them via display ads and social channels.
As a marketer, if you have the right technologies in place, you can seamlessly connect the two worlds of data for more precise consumer engagement. The good news is that, martech and adtech have already converged. Recent research from Salesforce shows that 94% of marketers use CRM data to better engage with consumers through digital advertising, and over 91% either already own or plan to adopt DMP over the next year.
So, if mastering consumer identity is the most important element in building tomorrow’s data platform then what, exactly, are the capabilities that need to be addressed? There are three:
1. A single data segmentation engine
Currently, marketers don’t have a single source of truth about their consumers.
Here’s why: Brands build direct mail lists and email lists in their CRM. Separately, they build digital lists of consumers in a DMP tool. Then, they have lists of social handles for followers in various platforms like Facebook and Twitter. Consumer behaviors like browsing and buying that happen on the ecommerce platforms are often not integrated into a master data record. And distributed marketing presents a challenge because a big mobile company or auto manufacturer may have thousands of franchised locations with their own, individual databases.
Segmentation is all over the place. Tomorrow, there must be a single place to build consumer profiles with rich attribute data, and provisioned to the systems of engagement where that consumer spends their time.
2. Data pipelining and governance capabilities
This identity layer must also have the ability to provision data, based on privacy and usage restrictions, to systems of engagement.
For example, when a consumer buys shoes, they should be suppressed from promotions for that product across all channels. When a consumer logs a complaint on a social channel, a ticket needs to be opened in the call center’s system for better customer service. When a person opts out and chooses to be “forgotten,” the system needs to have the ability to delete not only email addresses, but hundreds of cookies, platform IDs and other addressable IDs in order to meet compliance standards with increasingly restrictive privacy laws and, more importantly, giving consumers control over their own data.
Finally, marketers need the ability to ingest valuable DMP data back into their own data environments to enrich user profiles, perform user scoring, as well as build propensity models and lifetime value scores. This requires granular data storage, fast processing speeds and smart pipelines to provision that data.
3. Leaping from DMPs to holistic data management
Ad technology folks are guilty of thinking of cross-device identity (CDIM) as the definition of identity management. Both deterministic and predictive cross-device approaches are more important than ever, but in a world where martech and adtech are operating on the same budgets and platform, today’s practitioner must think more broadly.
Marketers can no longer depend solely on another party’s match table to bridge the divide between CRM and DMP data. A more durable, and privacy-led connector between known and unknown ID types is required. Moreover, when they can, marketers need the ability to enrich email lists with anonymous DMP attributes to drive more performance in known channels—now only possible when a single party manages the relationship.
These three tenets of identity are the starting point for building the data platform of the future. The interest and excitement around CDPs is well placed, and a positive sign that we are evolving our understanding of identity as the driving force behind the changes in marketing.
[This article originally appeared in Econsultancy’s blog on 2/1/2018]