Is It Time to Say “Good-bye” to the Soccer Mom?

How many times have you cringed at a marketing or ad proposal that targets “moms who want to delight their children”? Or can there possibly be one more article on how to market to “today’s millennial”?

In marketing and advertising, personas help us define who we’re selling to and in turn, guide us in creating the right kind of messaging to reach our target audiences. But many personas are based on a handful of vague attributes like age and marital status. “Soccer mom” emerged during the 1996 presidential election when Bill Clinton was accused by his opponent, Bob Dole, of targeting busy moms who cart their children to their sports activities. But personas like this don’t really help us understand and connect with consumers on a deeper level.

It’s time to throw out personas we’ve been using for the last 20 years that are simply based on vague demographics like gender and number of children, and start fresh with personas that are more detailed, accurate and paint a more complete picture of the consumer.


Soccer-Mom-Blog-mini-InfographicWe’ve all been guilty of using generational personas. The whole idea that people born within a certain date range could have all of the same traits is a fairly new thing, perpetrated by advertising, marketing and media.

We often think of millennials as being uber tech savvy and loyal sharing economy consumers. We label baby boomers as being leery of online shopping and loyal consumers of traditional media. We think of Generation X, once referred to as “slackers,” as being heavily focused on finances as they juggle children headed to college and aging parents. And finally, there’s generation z, who has completely grown up with technology and is heavily guided by online influencers.

The danger in creating messages geared to a whole generation is that you ignore people in this same age bracket who don’t have the same traits. For example, the common misperception about millennials is that they’re all single, young, unmarried and only rent apartments. But this misses a whole segment of people who fit in this same generation but are actually married with children and own a home.

A consumer insights platform can serve as an important tool for agencies in developing a deeper understanding of their client’s customers. Resonate distills what we call the Human Element. This is a holistic understanding of a person that starts with what makes us the most human—our values and motivations.

Personas are brought to life with the Resonate Human Element. It helps agencies provide dimension to their personas and ensure engagement that delivers performance for clients. For example, let’s look at the person who buys North Face products, which are geared to “athletes and the modern-day explorer,” according to the company’s website. We can assume that the North Face consumer’s top hobbies are hiking, camping and other outdoorsy activity. But Resonate’s dynamic insights paint a different picture. This segment actually spends their free time trading stocks, visiting spas and resorts and going to the movies. And they’re only 12% more likely than the overall U.S. population to spend their time hiking and camping. So when you’re developing messaging for a brand that sells outdoor active gear, think twice about turning to the traditional “hiker” persona—these folks are more indoorsy than outdoorsy.

Now let’s look at the working mom. You might assume her personal decisions, including working outside of the home, are driven by a desire to prove her competence and skills and getting recognition from peers. But Resonate’s consumer insights show working moms care even less about those attributes than the average U.S. consumer. Their everyday decisions are actually driven by living an exciting life and creativity.



Modern personas are about connecting with consumers in more meaningful ways. Connecting with people starts with understanding them at a personal level. Creating more accurate personas based on these actual person-level insights brings tremendous value to agencies in a number of ways:

  • RELEVANT OUTREACH: With more detailed and accurate personas, you can develop more targeted messaging that resonates with your client’s target audiences. Agencies using the Resonate Platform have already seen significant reduction in CPA costs.
  • STRONG CLIENT PITCHES: Imagine pitching your client with a completely new take on their personas. Show them that their existing personas can be enriched and expanded based on continuously updated and more accurate insights. Plus, the time spent doing research for client pitches drops from weeks to hours using the Resonate Platform.
  • BETTER OUTCOMES: Taking a more personalized approach to target audiences rather than a broad brush based only on a few attributes will help you create unbreakable relationships between your clients and their customers. Agencies are seeing a 32% increase in return on advertising spend (ROAS) compared to alternative data sources.
  • EXPANDED STRATEGY AND BRANDING: When you know your client and what makes their customers tick, you can give better advice about everything from media strategy and creative to product packaging and its charitable mission.

Agencies are competing against more players like consulting firms and smaller, more nimble shops and dealing with major industry shifts like new pay structures and more privacy regulations. Being able to offer clients a new view of personas can be the key differentiator.


Resonate’s easy-to-use SaaS platform provides a unified view of the consumer. It’s continuously updated, so personas evolve to adapt to peoples’ dynamic lives.

With this level of accuracy and timeliness, agencies can build personas that consist of real-time attributes, rather than static demographics. The Resonate Platform also helps provide insights into the several layers that make up a human, from the top actions they take every day to their psychological drivers.

So yes, it’s not surprising that a working mom buys most of her groceries online to save time and prefers retailers with loyalty programs. But there’s a lot more to her shopping behaviors. For example, they’re also 32% more likely than the average consumer to shop online and then pick up in store. And they’re big Black Friday shoppers but stay away from Cyber Monday and Amazon’s Prime Day.

There are several layers to humans, making it vital to tap into the Human Element to help frame more relevant personas. So can we once and for all stop with the “soccer mom”? She’s moved on and we should too.

Want to wow your clients at the next pitch meeting with a better understanding of their actual personas? Let us show you how.

Your Campaign Can Influence Voter Behavior by 30%. Here’s How.

In December 2017, Democratic candidate for Senate, Doug Jones, implemented a revolutionary targeting tactic that influenced the online behavior of tens of thousands of voters a week before the election.

During the lead up to the election, Resonate’s data science team identified 250k voters who predominately engaged with news and reporting from conservative sources. Collectively, the constellation of sites and publishers comprising this conservative media bubble proved to be a formidable shield, and prevented the Jones campaign from courting the non-traditional voters necessary to win in too-close-to-call elections.

That reality changed when the Jones campaign took action and leveraged Resonate data to infiltrate the conservative media bubble and deliver a message to voters that was otherwise completely absent from their digital lives. These voters were served a pro-Jones video in the week leading up to Election Day. Amongst the 80,000 video engagers, we observed a 30% increase in liberal news browsing relative to untargeted voters inside the media bubble.

Fast forward – we’re 4 weeks out from the midterms and Resonate data scientists have identified targetable media bubbles (conservative and liberal) in districts and states throughout the country. This is voter targeting 2.0. Launch a sophisticated targeting campaign with Resonate that puts your messaging right in front of these voters. Impact the recommendation algorithms of just 2% of voters and you can drastically influence the actions they take now and on November 6.

Let’s take a look at some real life examples of digital media bubbles in battleground Ohio. Specifically, we’ll look for voters trapped in these bubbles who are sympathetic to the opposition based on relevant insights in the Resonate platform.

Ohio Conservative Media Bubble
Full audience size: 1.9M online adults

  • Identify as Democrat: 19% (361,000)
  • Support raising the minimum wage: 37% (703,000)
  • Voted for Clinton: 19% (361,000)

Ohio Liberal Media Bubble
Full audience size: 1.2M online adults

  • Identify as Republican: 26% (312,000)
  • Oppose Obamacare: 39% (468,000)
  • Voted for Trump: 25% (300,000)

The above audiences identified, numbering in the hundreds of thousands, are receiving the majority of their election-related news from partisan sources that dominate their feeds. A sophisticated digital campaign that moves a small percentage of these voters could be a major difference maker in races throughout Ohio and other key states and districts this cycle.

Are you ready to incorporate this strategy into your voter targeting efforts and begin driving real, impactful changes? Contact our Campaign Hotline today. Our models are pre-built, dynamically updated, and ready to launch immediately.


Get to Know 37M Organic Food Shoppers

Do you really know who your best consumer segments are? We do! Imagine having incredibly deep insights on who’s purchasing your products in various channels and why. This is what Resonate is doing at massive scale for our CPG clients.

One frustration I often hear from fast-moving consumer goods companies is the lack of easily accessible information and insights on WHY consumers do what they do. Most brands have plenty of sales, distribution, market share, brand health and consumption patterns data, but not much actionable information on the Human Element – the psychographics, motivations, daily habits and values on the people within their most important segments.

Companies that leverage relevant and actionable Human Element insights are 23x more likely to acquire new consumers and 6x more likely to gain new ones, according to McKinsey.

The best way to achieve similar results is to have the best consumer-centric insights at your fingertips. This empowers brands to create content and creative that makes a difference in consumers’ lives and begins to build a lasting and deeper relationship with their products and company.

Let’s look at some of the insights in Resonate’s consumer insights platform for guidance on the ever-changing organic consumer. The Resonate Platform has insights on 37 million people who buy organic food.

At a high level, we start to see an interesting picture of this consumer:

  • About half have kids, and over 60% are married
  • They buy food based on nutrition and incorporate fitness into their daily routine
  • They also reward themselves by visiting spas and enjoying art and music


By looking at their demographics in more detail, we see that 44% of organic consumers are between the age of 25 and 44. Diving deeper into these 16.4 million consumers reveals unique insights that help drive more meaningful segment level insights, ultimately leading to higher engagement, loyalty, consumer acquisition and sales.


One of the many unique insights revealed was that these consumers are significantly less likely to purchase based on price. This insight could have a significant impact on the brand’s trade strategy and save the company millions in unneeded price promotion.

Deeper Human Element insights are available to help organizations move beyond sales data or static custom research to a dynamic world of real-time consumer insights that help define the WHY behind consumer actions and dramatically increase engagement.

Want to learn deep insights on several other consumer segments? Check out our new State of the Consumer Report Q4 2018.

Ready to get started? Reach out for a demo.

Infographic: Consumer Insights for 2018 Holiday Shoppers

Did you know that nearly 80% of U.S. consumers choose retailers that carry cost-effective products? It’s not surprising that with so many consumers prioritizing cost this holiday season there are also 57 million consumers who wait for Black Friday and 50 million shoppers who wait for Cyber Monday to make purchases. Who are these shoppers and how can you attract them to your online and brick and mortar store this holiday season?

View the infographic below to learn more about these consumers and marketing tips to increase engagement and boost sales this holiday season!

CDPs: Yet Another Acronym That Lets Marketers Down

CDPs, or customer data platforms, are the latest venture capital darling. Unfortunately, they’re not going to help marketers connect more meaningfully with consumers. Andy Hunn, Chief Operating Officer, Resonate tell us why 

The newest acronym taking our industry by storm is CDP. And unfortunately, this one isn’t going to help marketers connect more meaningfully with consumers either.

CDPs, or customer data platforms, are the latest venture capital darling. Their big promise, the one that sounds so sweet on paper, is a single view of customers across multiple devices, largely built around a brand’s first-party data. New players are coming out of the woodwork, and existing acronym players are rebranding as CDPs as fast as their marketing teams can revamp their web copy.

For marketers who are seeing the “CDPs Are Our Industry Savior” headlines and struggling to understand where they fit within the current industry acronym soup, let’s have a history lesson.

The Evolution of the Acronyms

CRM. Customer relationship management (CRM) systems represented the first major investment wave focused on better knowing and understanding customers. CRMs represented a huge step forward in customer data management. However, these systems typically connected only to a company’s direct marketing and transactional data.

TMS. Then there was the tag management system (TMS). Tag management systems took a step forward by enabling marketers to easily deploy tags on their websites. Some tags were for measuring things like performance, and other tags were for anonymously identifying a user across the digital web. In short, observed tag audiences represent first-party data sets of anonymous groups of people that engaged with a brand, and could hopefully be re-engaged — with targeted advertising, for example. Google decimated this market with a free offering, forcing a transition among the companies in this space. This gave way too…

DMP. Being able to target groups of people who engaged with a company directly was nice, but marketers also wanted to be able to combine those first-party groups with third-party data that is known about those individuals. Enter the data management platforms (DMPs), which were created to meld two main sources of data for marketing purposes: CRM data of known customers and observed tag audiences who visit a brand’s website or interact with its messaging in some way (just like the TMS before them). DMPs anonymize CRM data into digital IDs that can be used to reach those customers online and enable marketers to advertise to other observed segments defined in the DMP as well. That’s it. DMPs were built to deliver ads to anonymous IDs that are relevant to a brand. DMPs didn’t care about anything happening offline because that’s not why they were built. They were built to retarget online ads to customers and people who visit a company’s website. Which also left marketers wanting. So now…

CDP. Here come the CDPs. They say they’re different because they unify the CRM customer data (the PII — such as name, address, email — of the customer) with the anonymous digital ID world. And they observe first-party (i.e., the brand’s own) customer transactions in both the digital and offline worlds. That’s nice. But a game changer? No.

When you strip all the nonsensical nuances away from these companies — the CRMs, the TMSs, the DMPs, the CDPs — they’re all one simple thing at their cores: identity companies. Yes, they leverage different IDs, but at the end of the day, they are simply IDs that represent a person and their devices. Now, is scaled identity useful to marketers? Absolutely. But let’s be honest: It’s all just plumbing. Plumbing is a necessary evil, but it is only a means to an end — identifying a customer — and it shouldn’t be sold as anything more than that.

Where All the Acronyms Fail

CDP is just the next acronym for LMD: Letting Marketers Down. Despite all the grandiose claims that have been made about how these acronyms will change a marketer’s world, they all fundamentally fail on three key fronts:

Identity isn’t everything. Knowing the identity of a person is not the same as knowing that person. Yes, it’s useful to be able to identify a consumer consistently and across their various devices. You can retarget ads to them until they die or buy your product. But the core questions marketers today want to understand are, “Why is this person interacting with me? What is it about my brand, my product, my offer, or anything else that caused them to engage?” The fact that a browser-based cookie and mobile phone ID are connected does not answer those pressing questions.

Brands don’t have a complete understanding of their customers. The various acronymed solutions assume that a brand has a perfect understanding of who its customers are, and if it could just tie that understanding to identity, all problems would be solved. But based on 10 years of speaking with CMOs, I can tell you that they don’t have a perfect understanding of their customers. Far from it. And slapping a CDP into place doesn’t solve that problem. Sure, brands have some CRM data on their customers — PII, demographic attributes. Hell, maybe they’ve even unified that information with past product purchase history. That’s great. But the reality is that marketers have used and exhausted the value within this data. They’ve squeezed every drop of blood from that stone. They’re yearning for real, substantive additions to their understandings of their customers.

Behaviors without motivations teach us nothing.  Marketers have been asked to do the impossible. They are asked to look at observed actions and touchpoints and to derive meaning about the person behind those actions. Someone clicks on an ad. Or browses the watches section of a website and then browses the jewelry section. Look, just like identity, knowing these actions is better than nothing. But marketers want to know why people are taking those actions, why they’re traversing the website at all, why they’re engaging with the brand. These are not the kind of questions the acronym soup answers.

To complicate things further, a marketer’s need for understanding goes beyond their existing customers. Marketers also need to understand the motivations and values that are driving the prospective customers who are showing up every day on their websites. Furthermore, they need to deeply understand their competitors’ customers in order to best identify their most fertile conquesting ground.

None of the acronyms get marketers any closer to this understanding. This is why DMPs are languishing in the Trough of Disillusionment right now and why CDPs will eventually suffer the same fate.

To date, our industry has been focused on building tools that capitalize on the infinite observability and targetability of people online. It’s driven immense gains in efficiency and ROI for performance marketing. But that’s no longer enough.

Our industry’s legacy approach doesn’t solve the most essential challenge that marketers face: understanding the person behind the unified device identities, and why that person is engaging. The good news is that the tools now exist to develop this deep customer understanding — above the level of individual marketing execution channels and above the level of the plumbing. Our vast access to consumer data and data science can now be used to make marketers smarter.

Once marketers have a deeper understanding of consumer motivations, all these acronyms and the plumbing they represent can be put to good use by delivering on a marketing strategy that is informed by a richer understanding of the “why” behind the consumer. But until then, the CDP is just three more letters in the same acronym soup.

This article was originally published on Martech Advisor – 7.19.20

Read Forrester’s Future of Marketing Insights report to learn about how Innovative CMOs are building strategies to understand the “why” behind the consumer.

[related_posts_by_tax format=”thumbnails” image_size=”post-thumbnail” posts_per_page=”3″ title=”You may also like these articles from Resonate:” link_caption=”true” ]

Bad to the Bone – How Good Surveys Produce Bad Data

Imagine doing an online survey to get a better handle of your target audience and throwing out 20% of the responses. Crazy? Well actually if you’re not throwing out about that much, you’re probably using bad data.

Resonate conducts many surveys per year and uses a proprietary “fraud score” to throw out 10-20% of what is scoring as “bad data.” It’s really the only way we’ve found to ensure that the insights we’re providing are the closest measure of consumers.

As is true across the industry, we rely heavily on surveys to measure audience behavior. To understand humans and how to connect with them in an impactful way, we must ask them directly about their buying habits, their daily routines, how they choose which stores to shop at, what kinds of values go into their buying decisions and what their motivations are when pursuing a happy, productive life. But humans are not perfect and there are many factors that can affect the way they answer surveys that ultimately impact data quality.

So, what goes wrong exactly? Well for starters, if you ask someone their political affiliation and they mark Republican but they’re really a Democrat, how are you supposed to know? People provide poor answers for a variety of reasons. Of all the reasons, the most likely is that you’ll have respondents who do lots of online surveys and they blow through the answers to get paid. You’ll also get people who reduce their mental effort while they’re taking the survey to keep their stamina up.

Getting these bad responses has terrible implications for a company seeking high-quality survey data, including skewing data and throwing off compositions used in business decisions. Also, we estimate that about $3 billion-$4 billion is wasted annually on this bad data.

There are a few techniques for identifying bad survey responses but they all have their flaws. Straightlining is a commonly used technique where people choose answers like “agree,” “disagree,” “no opinion” on big matrix questions. People who straightline will just check off the same response all the way down the row. But we’ve actually found that many respondents straightline on these but on all other questions provide high quality data. Consistency checks can be helpful, but they, along with attention checks, can actually cause additional bad data. Extreme timing does catch bad actors, but in general, unless it is used with other techniques, it turns out not to be overly helpful.

Resonate finds bad data through a proprietary approach we call ‘fraud score,’ which is based on a few factors:

  • We look at the likelihood of certain answers given the respondent’s other answers. Someone saying they didn’t like their phone all that much means that they probably wouldn’t recommend it to friends. But answering the opposite of that could be a red flag.
  • Some questions prompt responses that together can give useful insight into a person’s thinking. For example, if asked for the color of your mother’s living room carpet and their political affiliation, those two answers don’t provide much information about each other. But if someone is asked for your political affiliation and their stance on abortion, their answers provide mutual insight.

We use fraud scoring because it’s an absolute measure that considers mutual informational relationships and is scaled by unconditional likelihoods. Also, when someone fills out a survey, we can tell you how much pure information they gave us. In the end, we throw out at least 15% of the data responses to get the most accurate insights.

I recently presented Resonate’s fraud detection process at the Advertising Research Foundation’s 13th Audience Measurement conference this month. Take a look at my presentation slides to get more details on how we avoid bad data.


[related_posts_by_tax format=”thumbnails” image_size=”post-thumbnail” posts_per_page=”3″ title=”You may also like these articles from Resonate:” link_caption=”true” ]

The Buzz and the Buyers: iPhone X vs. Galaxy Note 8

Resonate’s Senior Analytics Manager, Kevin Shea, takes a look at the data behind the highly anticipated iPhone X release to see how it’s really stacking up in the market compared to its Samsung rival.

In late August and early September Samsung and Apple announced new versions of their flagship mobile devices, the Samsung Galaxy Note 8 and the Apple iPhone X. With Samsung reporting record sales numbers for the Galaxy Note 8 and Apple banking on the iPhone X to make up for disappointing sales figures for the overlooked iPhone 8, the two rivals are set for a head-to-head showdown.

But talk is cheap, so we wanted to do our own investigating and see how these two phones were really stacking up in the marketplace and learn if we could unlock who will come out on top.

The Buzz

There’s been no shortage of media flurry promoting both launches. And while Apple and Samsung are both touting marketing success, we wanted to take a look at how consumers were actually engaging with Galaxy Note 8 and iPhone X content online in the weeks before and after their product launches.

iPhone X and Galazy Note 8 Content Hits

Without a doubt, the Apple-hype machine was and continues to be alive and well. Views of iPhone X-related content on the day of the launch dwarfed the Galaxy Note 8 and continued to be higher even after the Galaxy was publically available. After a brief lull, iPhone X engagement surged again as the pre-order finally began 45 days after Apple’s product announcement. However, the claims of record sales from Samsung, despite the consistently low level of engagement online, may speak to an incredibly loyal Andriod following.

The Buyers

At a high level, the iPhone X may be generating significantly more interest than its competitor, but that’s only half of the story. Who are all of these potential iPhone X and Galaxy buyers (who clearly aren’t scared away by a $1,000 price tag)? And how do they compare to each other?

Well, not too surprisingly, both phone shoppers skew toward a younger male demographic. Galaxy Note 8 and iPhone X shoppers are both approximately 75% male, with 60% of shoppers between 25 and 44 years old. While both groups trend to be higher-income individuals, it’s worth noting that the Galaxy Note 8 attracted a much greater proportion of shoppers making less than $50K per year.

 Househol Income - iphone vs Galaxy

Now demographics are great to give us a baseline understanding of consumers, but here at Resonate we like to dive a little bit deeper and look at the personalities and drivers of these buyers. From a personal motivations and purchase perspective, iPhone X and Galaxy Note 8 buyers showed some differences in four main areas:

Psychological Drivers - Iphone X vs Galaxy 8

When it comes to choosing their next phone, iPhone X and Galaxy Note 8 customers share the same top three considerations:

Top product considerations - Iphone vs Galaxy

However, iPhone X shoppers highly rate “Cross-Device Content Sharing,” indicating they may already own or plan to purchase other Apple devices while Galaxy Note 8 shoppers are more concerned with hardware features like “Camera Quality” and “Storage & Memory” options. What makes things more interesting in this rival showdown is that the extended iPhone X ad touts many of these new hardware features which could attract greater numbers of Android shoppers than a typical iPhone release.

The Verdict Is Still Out

The iPhone X did generate considerable buzz in the immediate days following its announcement and in the last two weeks as pre-orders started and the doors burst open this morning to long lines of waiting customers. Given that the two rival phones have similar target audiences, there still remains a strong potential to poach customers. But we’ll all find out over the next few weeks if the long wait between announcement and release date dampened expected sales for Apple, or if buzz and dollars equate, giving Apple its continued reign in the smartphone market.

3 Steps to Data Accuracy Done Right

Not all data is created equal.

Earlier in this blog series, we highlighted the prevalence of dirty data and some of the inconsistencies and inaccuracies that exist on even the most basic of consumer data points within DMPs and 3rd party data providers. Remember, this is the data you’re placing your trust in to help shape and inform your strategies; from segmentation and targeting to content and campaigns, and from channel selection and media placement to measurement and calibration.

But we can’t put all of the blame for this inaccurate data on vendors. Many marketers are stuck on data and insight approaches that no longer work. As a result, their segmentation and targeting miss the mark and their messaging becomes irrelevant and disconnected.

It’s due time that you, as the marketing and consumer insight keepers of your brand (or client’s brand), take responsibility for understanding the harmful effects of bad data on strategy and execution, and turn it from a “should” to a “must”. It’s time to challenge what you think you know, question if you have the right data partners, hold them to a higher standard and demand greater transparency and accountability.

How you ask? We’d recommend checking the box on these three items first…

1. Dig deep on methodology.  

Seriously, we really can’t stress this point enough. Ultimately the foundation and relative success (or failure) of your marketing performance comes down to quality of data. And if your data provider is hesitant to answer any of these questions or gives you the run around… buyer beware.

a. Where does the data come from?

How is it collected and what are the sources? Is it short or long-form consumer surveys or questionnaires, public or government records, online or offline directories, property and assessor files, online web forms and cookie data, mobile advertising IDs or a combination of pieces and parts of any of the above? Or is it data collected, analyzed and aggregated all by one company? The vast majority of data providers do not organically generate the data they sell. In fact, most license information to each other or pull together databases from hundreds of current and outdated, reliable and unreliable sources.

The problem is, a data provider that uses multiple sources opens the door to poorly collected and/or outdated information which decreases accuracy rates. They may miss or be totally unaware of causal relationships between data points or incorrectly interweave data sets. And the more the sources, the more these mishaps are compounded. The result – a plague of inconsistent and confusing data, embarrassing campaign missteps, frustrated marketers and worse, a trail of unforgiving consumers.

b. Is it contextual?

Folks are hot to trot for “behavioral data”. Knowing not just who your customers are, but what you can learn from their online behaviors. But without the proper context, it can be highly misleading.

Case in point… earlier this week my neighbor asked me if I remembered where my daughter shopped for her homecoming dresses (my daughter is now graduating from college so that was a few years back). My daughter couldn’t remember, so I started searching “homecoming dresses” online to help jog my memory and, low and behold, I’ve been receiving emails and targeted ads for all things “teen girl” this week (and not just retargeting). I already survived the pain and suffering of my daughter’s teenage years… please don’t make me go back and do it again!

But seriously, the point is… if you look at my behavioral data alone vs. applying a layer of context (my demographics plus additional online/offline behaviors), these kinds of incorrect inferences and false data points will dilute your consumer data quality and tank your targeting accuracy rates.

c. How recent is it?

In the race to perfecting 1:1 customer experiences, real-time data and insights are essential. Extensive market research, in-depth personas and 360-customer profiles are great, but with the ever-changing consumer and increasingly competitive marketing ecosystem, we can’t be left waiting months or even weeks for fancy studies or reports that are outdated before they’re even published… we need that data NOW, and we need it to be current!

2. Get your hands dirty.

No matter what promises of accuracy or grandiose scale your data provider may claim, before you use it to guide your decisions and marketing strategies, we would implore you to explore the data yourself.

The easiest way we’ve found? Do an exploratory 3rd party data analysis on yourself. Or, more likely, ask for an audience sampling or snapshot. Only a few providers make their registries public or don’t directly collect PII, but if your data provider won’t give you a sample custom audience profile – red flag! If the data provider can’t accurately target you or a sample audience, are you going to trust their data to accurately target and execute your resource-heavy and expensive media campaigns?

3. Measure what really matters.

It’s easy to look at results of an ad campaign and get excited over deliverability and click-through rates. But you shouldn’t stop there. How do you really know if your data is working for you? The answer is being able to measure your marketing performance against your segments or target audiences, at the individual-level, in order to optimize creative and messaging to replicate or re-calibrate for best success.

Exactly who are your campaigns reaching? Is it your desired audience? Are there new/additional audiences you’ve been missing out on? Those are the insights your data provider should be giving you. Otherwise how do you know if the audience you paid for, is what you’re really getting?

So please, ask the questions and do your homework.

And if what you find doesn’t pass the smell test… walk away. Irrelevant messaging. Disengaged audiences. Wasted campaign dollars. The risks and potential damage from dirty data is just too great. It’s not only your campaigns that are at stake, it’s your brand.

Good luck!

Where do we get our data? We don’t “get” it. It is our own, single-source proprietary data. We are the largest traditional research company that kicks it up 100 notches by combining our traditional research with cross-device and online contextual behavioral analysis. Drop us a line at or check out our full methodology to find our why our consumer data and insights are trusted by hundreds of the world’s leading brands, agencies and publishers. 

Facing the DMP Data Marketplace Yard Sale

So many choices, so many sellers and you never know if what you picked is any good…

Have you ever been to a neighborhood yard sale? Wandering aimlessly from house to house, wondering what enticing things await you as you pick through endless tables of the same old odds and ends.

You may be wondering what the heck a DMP data marketplace has in common with a neighborhood yard sale. The answer; countless “providers” to choose from, all offering the same thing, and no idea or assurance of which one(s) are going to give you the best data to meet your needs. Bottom line: confusion, inconsistency, no view to quality and wasted money on things (data) you don’t really need.

50.4% of Marketers Have a DMP¹

But, only 30% of marketers are satisfied with the results they are getting from their DMP1, and [tweet_dis]according to a Kantar Millward Brown study, only 37% of advertisers trust the data that comes from DMPs.[/tweet_dis]2

Let me make a quick disclaimer… this blog is NOT a bash on DMPs (we actually partner with most of them for activation). However, it is no secret that DMP data marketplaces are often highly complex, contain inconsistent data points and lack transparency or promise of any level of quality – or how often the data is updated. So why do we, as marketers, continue to place our trust in these data marketplaces to inform strategy, create segmentation and build targeted audiences when the end result can be irrelevant messaging, disengaged audiences and wasted media spend?

Let’s run through a little exercise…

Say you’ve identified your segmentation plan and are ready to build your target audience. In a data marketplace, you typically have the following data options: that of the DMP, demographic, geographic, interest, intent, past purchase, predictor, media, and device data, as well as pre-determined segments and the whole host of their branded 3rd party data partners (anywhere from 50-90 to choose from). Most of these 3rd party data providers offer the same data categories and verticals as the DMP, and conversely, of those that offer out-of-the-box segments, seldom are any two alike.

So, let’s start with a test on the basics – the simple demographic of U.S. adults 65+ years in age. When looking in one of the industry’s leading DMP data marketplaces, here are the audience sizes that came back from the 3rd party list providers (the very people helping you with your targeting):

Demographic: Age = 65+
U.S. Census Bureau – July 1, 2016 = 49,115,382
(Online U.S. Population 65+ = 32,909,3063)

Audience Size Branded Data Provider
19,427,100 Acxiom
86,826,000 Datalogix
38,920,200 Experian
15,226,200 Kantar Media TGI
129,206,100 Lotame
52,575,600 MediaSource
17,493,600 Neustar
221,989,800 Oracle
134,350,500 PlaceIQ
57,599,400 V12 Data

Since all but 4 of the 11 DMP data marketplace providers shown came back with audiences HIGHER than the reported number of U.S. adults over 65 by the U.S. Census Bureau or online U.S. 65+ population3, you have to wonder who all these other people are that you would be wasting your money on with irrelevant and unnecessary media!

Now let’s take a look at interest data from these folks for U.S. adults classified as interested in “healthy living”. Here are the results:

U.S. Adults Interested in Healthy Living

Audience Size Branded Data Provider Segment/Interest
35,758,200 AddThis Healthy & Fit
241,417,200 Datalogix Healthy & Fit
131,686,200 Experian Health & Fitness
236,179,500 Lotame Healthy Living
280,423,800 Oracle Healthy Living
996,000 VisualDNA Health & Wellbeing

According to the July 1, 2016 U.S. Census Bureau report, there were 245,576,910 U.S. adults over the age of 18 (and the total U.S. population was 323,127,513).

It is exciting that Datalogix, Lotame and Oracle identify (and help you target) that 96% to 114% of American adults are interested in being healthy and fit. That’s great news for the country… but something isn’t adding up here.

And, speaking of segments and intenders, let’s get to those crisp, rich insights that DMPs and their marketplace data partners provide…

Segment Insights (you gotta love some of these segment titles… we didn’t make these up!)

  • King of the Wallet – Most active purchasers of men’s products from Alliant database. Top spending purchases of products related to men’s interests.
  • Affluent Men’s Shoppers – Most active purchasers of men’s products from Alliant database. Men’s shoppers with discretionary income making multiple purchases across product lines. (Note: both of the above segments are from Alliant. But from the insights provided, what’s the difference between the two?)
  • Fashionistas – This audience intersects country-specific IP info with users who share certain lifestyle attributes. These users are into the latest fashion.
  • Young, City Silos – Younger and middle-aged singles living active and energetic lifestyles in metropolitan areas.
  • Aspirational Fusion – Low-income singles and single parents living in urban locations striving to make a better life.
  • Birkenstocks & Beemers – Upper middle class established couples living leisurely lifestyles in small cities and towns. (This is my favorite as (a) what a great segment name, and (b) I did get rid of my husband’s Birkenstocks at a yard sale, but we live in a major metropolitan area.)

Intender Insights

  • Apparel – The Household Consumer Expenditure segment contains consumers who indicate a high propensity to purchase within a specific category. The segment takes into consideration the differences in purchase behavior for the various product categories.
  • Brokerages – This category contains people who are in-market for brokerages.
  • Mid-range Car Domestic – Sporty – Are likely to be shoppers for this type of car within the next 6 months. Vehicle examples in the Mid-Range Car Domestic Sporty category include: Pontiac G6, Pontiac G8, Pontiac Grand Prix, Pontiac Vibe, and Saturn Aura.
    • Like on most ecommerce sites, you also conveniently receive a list of “related lists” that may be applicable. Do these seem to be related to mid-range sporty domestic cars to you?
      • Related lists:
        • Full size vans
        • Small car – standard
        • SUV import – upper & basic
        • SUV domestic – large

As a sidebar, I am convinced that General Motors is in cahoots with this “mid-range sporty domestic car” data provider. Has anyone informed Ford, Dodge, Cadillac and Chevrolet that they don’t have and should offer mid-size sporty cars? It’s apparently a 31M intender market.

Is it Worth the Trade-Off?

If all of that left you scratching your head, you’re not alone.

“Confusion”, “complexity”, “inconsistency” and “inaccuracy” should all be words banned from the marketers’ internal vocabulary. DMP data marketplaces have the allure of multiple data providers and scale. However, unless you are in direct response, by trading accuracy for scale, you are wasting time and money targeting messages and media to the wrong people. And with relevancy being the new ROI according to Forrester, the cost and repercussions go well beyond wasted resources and media spend.

There Are DMP Alternatives

At Resonate, we don’t rely on 3rd party data providers. Our data is proprietary, using a combination of traditional and online contextual behavioral research which allows us to be transparent about our average of 87% data accuracy. [tweet_dis]The Kantar Millward Brown study revealed that 67% of marketers see a gap between traditional and digital research[/tweet_dis] and that marketers in the survey stated that it was difficult to “get the full picture…” of the consumer for accurate insights and measurement.  Well, with the largest understanding of the U.S. consumer at the individual level, we provide the most in-depth, unified view of your customers and prospects. Unlike a traditional DMP and their 3rd party data marketplace partners, we offer accurate data, rich real-time insights, completely custom segmentation and targeting based on your specific needs, audience activation at scale and measurement in a SaaS platform that’s super easy to use. Marketing is complex enough as it is. This part shouldn’t be.

Remember, DMP data marketplaces may offer the perception of “more”, but what is “more” and at what cost?

Good luck avoiding or navigating the neighborhood yard sale – or at least getting that wagon wheel table at a good price!


Haidee Hanna, Vice President of Marketing – Resonate

Our other Data Accuracy blogs:

Deloitte Study Reveals Consumer Marketing Data’s Dirty Little Secrets

Putting 3rd Party Data Providers to the Test

Contact us at or 855-855-4320 to find out how your customers map onto Resonate’s attributes and how our analytics platform can help you identify your customers, know what to say to them and find and engage more of them to win more business.

Source: AdAge/Neustar Study, February 2016

2 Source: Kantar Millward Brown study

3 Source: Pew Research, May 2017

Putting 3rd Party Data Providers to the Test

I was surprised to learn I could be so many people at one time!

Disclosure: This is an actual experiment you can try for yourself. We’ll give you some links at the end of this blog. Take a peek – you might be surprised/amused/horrified at who marketers think they really are targeting. 

DMPs and 3rd party data providers have long been promising marketers the equivalent of the holy grail – accurate consumer data, at scale. So many names, so much promise of the ability to develop and target a desired audience with grand reach, I must say it’s very tempting. But for all the hype, especially on intender data, it seems most data providers are missing the mark. In our last blog post, we shared the findings of Deloitte’s study whereby they asked consumers to validate the accuracy of their personal profile from a leading consumer data provider. [tweet_dis]Deloitte’s overarching finding – only 29% of consumers found their data to be at least 50% accurate or better.[/tweet_dis]


As a consumer and a marketer, I was both fascinated and mortified. So, I decided to test Deloitte’s findings myself! The challenge, I’d access my personal consumer profile, the same data marketers around the globe are purchasing for segmentation, targeting and activation, from a major DMP and a leading 3rd party data providers public registry, and compare it against the proprietary data we house here at Resonate to see just how well 3rd party data providers are living up to their expectation of accurate consumer data.

So, here goes… it’s A LOT of data, even massively pared down, but stay with me!

Major DMP – 33% Accuracy

It’s worth noting that DMPs will provide both their own data (if any) as well as an expansive data exchange or “marketplace” whereby you can pick and choose among many 3rd party data providers to build, target and activate audiences.

With this DMP registry, your consumer profile magically appears on the screen. They state that it reflects 3rd party cookie-based demographics and interests associated with the device from which you are viewing as well as the browser you use which may link to other devices. Your profile could completely change if viewed from a different device or browser. That’s comforting! This particular DMP was clearly going for scale as far as audience targeting, including me in multiple bands within one data variable as simultaneously, I….

  • Am single, single/divorced, married and not married [I’m married]
  • Have attended only some college, have graduated from college and have a post-graduate degree [I have a Bachelor’s degree]
  • Am listed in 5 different income bands
  • Own a home that is valued in 5 different bands for 3 different lengths of time [I do own a home]
  • Live in 3 different cities [Nope, just one]
  • Have either one or two children [I have 2]
  • Identify as a Joneser and a Gen Y/Millennial [I’m a Boomer – which crosses over with Jonesers]

The Hobbies & Interest data might have been the most entertaining. I pity the marketers targeting me for….

  • Hunting & Equestrian [Literally never in my life]
  • Arts & Crafts [Nope]
  • Collecting Antiques [Nada]
  • Gaming, preferring XBox & Kinect [Wouldn’t know how to turn either on]
  • Back-to-School Shopper [Both my kids are grown]
  • A Foodie [My poor husband only gets frozen TV dinners]

Professional Interest accuracy was just abysmal. Apparently, I have 18 occupations, none of which are marketing.

Data Exchange Partners – (See Below For Individual Accuracy Scores)

I didn’t have the patience to go through all 2,300 data points from all of the partners in their data exchange, so I got through the first 10 that had enough data to warrant mention. Here is their rough accuracy level on my profile:

  • Datalogix – 30% [They were the #1 data provider in their data exchange as far as volume]
  • Datalogix (DLX) – 20%
  • V12 – 25%
  • Experian – 60% [2nd largest data provider of the 10; – their purchase predictor intent data was almost all wrong, but their psychographics were pretty spot on]
  • Alliant – 30%
  • TransUnion – 5%
  • Profound – 45%
  • Dataline – 25%
  • Media Source – 10%
  • Analytics IQ – 35%

Leading 3rd Party Data Provider – 37% Accuracy

To start, I had to enter my full name, address, date of birth and last four numbers of my social security number just to access their registry. I wasn’t entirely comfortable, but expected that my profile would be pretty accurate as such.

The 3rd party data provider states three sources for their data:

a). Government and publically available records such as website directories, property and assessor files, and government issued licenses; b) Data from surveys and questionnaires I fill out [I don’t recall ever having done that or been invited to] and; c) General data from other commercial entities where consumers have received notice of how data about them will be used [how many of us have clicked Terms and Conditions without reading them!]

This provider lets you request to receive their Partner Marketing Data which is also sold for intent-based advertising, but upon request I received a polite email telling me it would take 7-10 business days to receive my PDF file by email which means I can neither update it nor opt out.

Overall, they provided six main categories for me to examine my profile–all at the household level:


  • Characteristic Data [Fairly accurate, but they asked me 5 out of the 9 data fields in order to access my profile]
  • Home Data [They had zero data for me, even though I provided my home address–so much for publically available records]
  • Household Vehicle Data [Kudos for 2 out of 4 vehicles owned; completely inaccurate on auto policy renewal information though]
  • Household Economic Data [I’ve only made 5 TOTAL offline purchases, spending a total of $780.00 in the last 12 months??]
  • Household Purchase Data [Evidentially I’ve made 14 online purchases for a total of $178 dollars – wait until I tell my husband – he’ll be delighted! ]
  • Household Interest Data [Apparently I’m really supposed to be into arts & crafts and antiques as the DMP reported the same]

Resonate – 87% Accuracy

Unlike the DMP and the 3rd party data provider, Resonate does not rely on 3rd party data. Our single source proprietary data is founded on 200K long form surveys fielded six times per year combined with real-time contextual analysis of 15 billion events per day-that’s over 1.2 trillion words every 24 hours. Using tracked online behaviors and advanced algorithms and technologies, we model out more than 7K attributes on more than 200M US adult consumers at the individual vs. household level. (We’re completely transparent about our multi-modal research approach and our accuracy rate so if you want to know the nitty gritty details check out our full methodology.)

Resonate scored pretty evenly across all 350 categories, with a few exceptions:

I don’t…

  • Have a dog
  • Drive a used Honda that cost less than $25k
  • Buy organic foods
  • Plan to buy a home audio system
  • Currently have GEICO auto insurance
  • Own a connected thermostat
  • Watch The Ellen DeGeneres Show

But what did Resonate get right? Too much to report, but I’ll share some of the breadth of the results. In this case, I confirmed that Resonate got my demographics and basic data right:

I am..HaideeNailedIt

  • A married Caucasian female with 2 children and a college degree that lives in the Mid-Atlantic whose primary language is English, who has not been in the military and serves in an Executive/Senior management role
  • Cat owner, who does not smoke and recycles regularly [Check!]
  • NOT a Minivan, pickup truck, hybrid or sports/muscle car buyer [whew!] Prefer imported cars and own an Acura
  • A hiking and camping enthusiast who prefers personal vacations at the beach, and most often makes both personal and business travel arrangements through Expedia

In addition to this basic information that the other data providers got wrong, I was able to find information (and potential target marketing data points) that more accurately reflected my own interests rather than those of my overall household. The data reflected that….

  • The personal values most important to me are being close with family and friends, financial security, and feeling a sense of accomplishment
  • Verizon is my voice, text & data wireless provider, I have an Android smartphone whereby selection traits important to me are ease of use and the camera picture/video quality, but own an Apple tablet
  • LinkedIn and Twitter are my predominant social media channels, where I am only a moderate Facebook user and have never used Instagram or Snapchat on any device [yes, I’m not hip]
  • My primary credit card is a VISA rewards card, I use online banking, am satisfied with my bank, but would consider switching based on rate increases – and PayPal is my preferred online shopping payment method
  • I will pay more for a brand I trust and that I download apps from my favorite retailers, join loyalty programs and use specialty retailer coupons
  • I prefer in-store shopping, but shop online fairly often and am an Amazon Prime member
  • Local and national network news are my weekday television habits, spending only 2-3 hours watching television per week, and that I almost never watch the MLB, PGA or NBA, but do watch NFL games and prefer college football and basketball
  • Pandora and Spotify are my main music hubs, I listen to music more on my phone than radio or other devices
  • I plan to buy entertainment room furniture and a television [which is spooky because I just picked out a new couch!]

The Takeaway 

[tweet_dis]Bottom line… when it comes to 3rd party consumer data, marketers would have better luck flipping a coin![/tweet_dis]


Marketers have been relying on this data to help them develop segmentation strategies, provide insights as a basis for relevant creative and messaging, and build audiences that will target the right customers and prospects efficiently and effectively. Targeting at a household level, when there are many unique individual buyers, all with different demographics, preferences, interests, motivations and media consumption habits, is bad enough. But targeting audiences when they fall in multiple bands of the same data point or in ridiculously vague general or just plain wrong attributes is even worse. If we’re paying good money for data, I think it’s time that brands and agencies demand more out of their data partners.

But, don’t just take my word for it, test your own consumer profile and see who you turn out to be…

The Digital Advertising Alliance provides individual consumers a list of all data companies that are capturing cross-device consumer browser/behavioral data on them for interest-based advertising. Consumers have the option of opting-out of some or all of these cookies-based collection methods at:!/

Some 3rd party data providers make their consumer data registry on individuals or households publically available so that consumers can edit their profiles. Here are a few:

Or you can write to them and they’ll send it to you

Happy profiling!


About Resonate

Contact Resonate to accelerate the ability to accurately identify the right customers or prospects, understand what they care about, know what to say to them, and find more of them across all marketing channels with precision and at scale. Resonate’s level of data attributes and individual insights allows savvy marketers to be more relevant and outperform. Resonate is helping marketers reduce marketing complexity, drive strategy and win more business, while reducing data costs and improving media accuracy.