Thoughts on Data-Driven Audience Measurement

A Conversation with Scott Portugal of PulsePoint

What are some best practices for the modern digital marketer? Cookie-based data makes knowing your audience easier  than ever. Developing accurate audience profiles, optimizing campaigns based on audience composition, and validating audience reach are all critical components for marketers doing targeted digital campaigns. I recently spoke with Scott Portugal, long time digital media veteran and currently VP of Business Development for PulsePoint, who has been working with PulsePoint’s Aperture audience measurement offering, what marketers should be thinking about when it comes to measurement.

Scott Portugal: First and foremost, marketers must really understand the goals of the campaign. “Branding” vs. “Performance” aren’t goals – they are notional indicators of goals. “Increase brand awareness amongst men passionate about health and fitness by 50%,” is a goal. The more specific, the better. It eliminates the guesswork that agencies have to do around media tactics, and most importantly, specificity in KPIs means everyone knows which data sets to use along the way.  Also, a modern marketer knows that buying digital media isn’t an on/off switch. Once the buy starts, the work starts. Prepare to optimize everything you can – look at performance across targets, media partners, creative (the most important and often least optimized variable), etc.. Good digital marketers are like good scientists: ask plenty of questions, account for all variables, and constantly test to find success.

What new tools are out there to assist in audience measurement, and supplement the standard offerings from Comscore, Nielsen?  

SP: Data is ubiquitous – some might say commoditized. But there are a few platforms out there that are taking novel approaches to audience measurement. Certainly our PulseAudience platform is among that group. We’re able to build audience profiles at the domain level, meaning at a very granular level we can infer the audience composition of a page even without a cookie. Another new player is Korrelate, founded by the guys who ran TACODA. Korrelate is in the business of helping marketers understand how different data sets perform across different platforms – essentially helping a buyer know what data segment to buy when and where. At a broader level, audience measurement platforms are starting to look cross-media, bringing together disparate data sets that show impact of a campaign on ALL digital activity, not just clicks.

What about social data? How are technologies like Facebook and Twitter enabling a more concise view of audiences, and helping marketers validate their choices?  

SP: If you think about Facebook and Twitter NOT as destinations, but as communication tools, then you can start to see where a more holistic audience view can be created. Social media is more than updates – it’s sharing news, communicating about brands, raising hands about interests, and more. Social data, when done right, is true first party data that goes above and beyond standard behavioral data. Marketers can understand not just when a user engages, but how, where, and how valuable that engagement actually was (likes, shares, tweets, etc.). it should validate a marketers choice around creative and placement, but only if the creative and placements actually include social elements. Social data is powerful, but it’s only powerful if it’s part and parcel to other data sets and targeting mechanisms used in conjunction with social media. Nothing happens in a vacuum, and nothing happens ONLY in one channel.

Your company owns Aperture. Can you provide some examples of how progressive media organizations are using audience measurement data? Is it about audience validation? Optimization? Upselling clients?  

SP: It’s about delivering value via insights up and down the funnel. It sounds like ad jargon but it’s what we strive to do with every single engagement. Cookie targeting works, but we believe that there is real value in modeling at other points of content interaction – insights that help guide and inform at all points of the campaign. Our RTB partners can leverage some of this data in real time; our non-programmatic partners work with our data and insights group to go even deeper via custom reporting and deeper dives on how to get consumers to engage. Data availability and normalization—what we do—is what makes the tide rise to lift all boats.

How can (the right) measurement data influence brand advertising? Is this the key to bringing more brand dollars online?

SP: Brands will feel safe moving dollars over from television to digital when they can do two things: ensure the environment is safe and ensure that they are reaching the right audience with minimal waste. Does television have massive amounts of waste in it? Of course – but as an industry we promised the world that we would eliminate much of that problem via targeting and optimization, so we have to lay in the bed we made. So measuring not just reach & frequency, but the impact of that reach & frequency is critical. Did search queries go up relative to their competitors? Did social commentary increase? Are there more tweets about campaigns in other platforms (did you create awareness that increases awareness in other channels as well)? Like I said earlier – understanding the specific goals of that branding campaign, and ensuring that the right creative is matched with the right tactics, will allow for the right measurement data to be used.

What’s next in measurement?  

SP: To me it comes down to cross-platform impact. Devices and screens aren’t truly linked yet, but the audience at the other end of that ad campaign is the same person. They tweet, they promote, they like, they friend, they blog, they comment, they shop….but they do it across multiple screens in the home, the office, and on the street. The best measurement companies are going to be those that can build an impact assessment across ALL platforms and show the points of interconnection. It’s a big task – but the ones who get it right will be the ones working directly with marketers and become embedded into everything they do. The next big push will be to show marketers that social, search, display, video, and mobile are all tactics inside the same strategy…and then show them how each tactic impacts the other.

This interview, among many others, appears in EConsultancy’s recently published Best Practices in Data Management by Chris O’Hara. Chris is an ad technology executive, the author of Best Practices in Digital Display Media,  a frequent contributor to a number of trade publications, and a blogger.

Know Your Audience

Using Audience Measurement Data to Optimize Digital Display Campaigns

These days, advertising and data platforms are giving marketers a wealth of information that can be used to validate their strategies, and optimize their digital campaigns for better performance. There is a lot of data to sort through—some more useful than others. Sometimes, good campaign optimization comes down to the basics: Understanding who your audience is, and why they are doing what they are doing.

Let’s look at a real life example of a digital display campaign, run through the digital ad agency of a popular mattress retailer. The agency wanted to test new inventory sources for the campaign by running broadly on general interest sites, evaluating the demography of audiences that showed purchase intent, and optimize over the course of the campaign to maximize impact.

A theory being tested was that older audiences, who report more difficulty sleeping than younger demographic groups, would respond more favorably to the retailer’s online display ads. Campaigns were initially skewed to sites that over-indexed against audience composed of 50 and older.

Figure 1: Age of Ad Viewer, by Impressions.

As Figure 1 shows, a bulk of impressions during the discovery portion of the campaign were delivered to visitors aged 46-65 years of age, which was the desired demographic. After analysis of those who viewed or clicked on a display ad, and then went on to purchase, the audience composition was remarkably different. As shown in Figure 2, the bulk of conversions came from those aged 18-45.

Figure 2: Age of Mattress Purchaser (Conversions).

The agency adjusted the ad buy to heavy up on sites that over-indexed for a younger audience, and opted out of buys tailored to the older demographic. As wasted impressions were trimmed down in the overall plan, conversion rates increased dramatically. Testing and validating your instincts with data on an ongoing basis is the key to success in digital display advertising. The mattress retailer, who experienced better sales from older store visitors (offline), found a more responsive younger audience online. Although it seems obvious, having the initial data means being able to smartly allocate marketing capital, and having access to ongoing data means not having to rely on old insights in a changing marketplace.

Another offline theory the mattress retailer sought to validate was the mattress life cycle. After collecting brick and mortar sales data for years, the retailer knew that the average life of a mattress was approximately 7 years, and that the single greatest life event influencing the purchase of a new mattress was moving. Therefore, it made sense to target audiences based on length of residence (>7 years), and target content around buying or renting a new home.

Inventory was bought from a wide range of home-specific and moving sites, and measured using Aperture audience measurement populated with data sets from Experian, IXI financial, V12 demographic, and Nielsen PRIZM data.

 

Figure 3: Length of Residence, by Impressions.

Figure 4: Length of Residence, by Click.


As Figures 3 and 4 amply demonstrate, the mattress retailer was targeting the bulk of impressions towards individuals reporting over seven years residence in a single location, and clicks among that group indexed the highest in aggregate. That data validated the approach of buying into sites with a strong audience of self-reported homeowners. However, a deeper look into audience data revealed a strong distinction between renters and buyers.

Fig 5Comparing Impressions and Conversions by home ownership status.

As noted in Figure 5, although the bulk of impressions in the campaign were served to homeowners, renters were the ones buying the most mattresses. This learning did more than any other data point to drive campaign optimization.

Naturally, the next step in the campaign optimization process was to focus inventory delivery to sites that promised a concentrated audience of home renters. Sites such as ForRent.com, ApartmentGuide.com, and Renters.com were added to the optimization plan.

More insights came as the Aperture data was collected. Despite purporting to have a heavy concentration of renters, two of the more popular sites actually index much higher among homeowners, as shown in Figure 6. It looked as though homeowners that were looking into renting made up the majority audience—a fact that helped the retailer tailor specific messaging to them.

Figure 6: In this example, a media site aimed at renters, over-indexes against current homeowners.

Figure 6: In this example, a media site aimed at renters, over-indexes against current homeowners.

For this particular campaign, the ability for the retailer to validate certain audience assumptions using real demographic data was critical, as well as the ability to leverage the distinction between two types of potential customers: home owners, and renters. Additionally, getting real audience metrics beyond a publisher’s media kit or self-declared audience information enabled the retailer to craft its creative and messaging in a highly specific way that increased conversions.

When it comes to audience validation and campaign optimization, here are three keys:

  • Know Your Data: In today’s technology-driven marketing world, knowing how to leverage the data available to you is critical to both understanding and targeting your audience. Make sure your marketing investment decisions are driven through the analysis and usage of 1st party data, including registration data for demographic modeling; 2nd party data, such as ad server and search data for behavioral modeling; and 3rd party data, such as available audience segments from providers like Nielsen and Datalogix, for audience validation, matching, and lookalike modeling. Data is not just about buying audience segments for targeting; it’s about trying to get a 360-degree view of your ideal customer.
  • Choose the Right DMP: There are DMPs for every marketer, so be careful to choose the right one. Big Data needs call for pure play DMPs that can stitch together highly disparate data sets that include all data types, and make both insights, audience segments, and lookalike modeling available in real-time. Marketers looking to buy from a variety of 3rd party audience segment providers should choose a data marketplace such as Exelate, or be willing to access a more limited number of data sources inside a DSP such as AppNexus.
  • Leverage Audience Measurement: Finally, there is a lot that audience segments can bring to the table in terms of audience insights. Understanding the audience composition of who saw, clicked on, and converted after seeing your campaign gives you the ability to learn about your target customers, their online behaviors, and (most importantly) find more of them. Your DMP should have the ability to marry audience and campaign data to give you a highly granular level view of your best (and worst) performing audience types—down to the creative level.

Learnings from this case study, and other valuable information, can be found in my upcoming “Best Practices in Digital Display Media,” coming in January 2012 from eConsultancy.com.

[This article originally appeared in ClickZ on 1/4/2012]

 

Fish Don’t Know He’s Wet

If Your Company Depends on RTB, Put Your Helmet On.

The 5 Reasons RTB is less important than you think

All the hype in the display advertising industry has been around real time bidding for the last several years, and rightly so. Finding audiences with precision (cheaply) is marketing nirvana and, with all of the startup companies willing to work their tails off to make their “platforms” work for advertisers, the promise of media, layered with great technology, and tons of free service was hard to resist. Conference after conference, our industry leadership (well, actually I think it’s just the 30-odd people that speak at every conference) prognosticates on the latest data-driven success story, and ponders the meaning of the famed Kawaja logo vomit map, hoping that their flavor of audience technology gets acquired. But, like the old George Clinton lyric goes, the fish don’t know they are wet. After drinking the RTB Kool-Aid for so long, the real time practitioners may not realize that this fundamental driver of the display advertising ecosystem may not be as important as we all think. Here are five reasons to hedge your bets with RTB:

Quality Matters: Sorry, exchanges, but inventory quality still matters—a lot. The notion that you can splash a little bit of data on top of $0.25 CPM banner inventory and turn it into $5.00 gold was never really real in the first place. The great thing about RTB isn’t the enormous amounts of data you can apply to a media buy—it’s the enormous scale and price advantage that exchange buying brings. In a CPA-driven world, the most important metric is the cost of media. Today’s bidders give advertisers the ability to scour 800+ exchange inventory sources and buy cheaply and deeply into remnant inventory like never before. But, when you look at the reporting coming back, the clicks and conversions tend to happen where quality content appears. I’ve seen it time and time again: An RTB advertiser lucks into a bit of Tier I or Tier II inventory and finds performance. Unless publishers start changing their habits and stop putting banner code on every single web page they publish, there will continue to be a dearth of quality placements available in real time, and average real-time CTRs will not eclipse their .03% average.

Cookies Don’t Scale: This is the dirty little secret of the display media industry, and something that Datran’s Aperture team is out actively pushing. Anyone who has used a DSP can tell you that even a little bit of segmentation data applied to a media buy drops impression availability by a large factor. Cookie-based targeting is enormously complicated, and getting all the gears to turn in the same direction is not easy. How many people are in the market for a BMW are there in any given 30 day period, anyway? Well, according to AppNexus, I can find about 81,689 unique users that fit that description, and access up to 1.3M impressions if I win every single bid I place. Let’s go crazy and say that I am prepared to pay $30 CPM for every single one of them (I can probably win them at $8, though). That means, this month there is the potential of $40,000 of inventory to be sold for “BMW intenders.” Add in “Connecticut” and “Men” as additional segments, and you might as well call each potential buyer on the phone, or rent a plane and drop pamphlets on their house. But wait—you could probably mail them something really nice and reach them that way. Now that sounds like a business!

Legislative Tsunami: Many fish don’t understand what “Do Not Track” and other legislation is going to do to real-time bidding. Even if you take the most conservative reckoning, you would have to admit that some sort of consumer protections need to be built into our industry. I can’t tell you how many people are fascinated—and sort of bummed out—when I introduce them to www.bluekai.com/registry Personally, I have no problem being targeted (except for the relentless onslaught of industry-specific ads I seem to be targeted with). No matter how our industry tries to spin it, the fact that I just looked at flights for North Carolina, and am being targeted by travel ads two seconds later as an “in market travel intender” makes almost everyone uncomfortable, and it’s not a winning long term strategy. We need to turn over choice to consumers, rather than convince them that we are “protecting” their data. Watch out for companies that don’t run without the fuel of 3rd party data. Conversely, bet big on companies that collect tons of 1st party (volunteered) data like Facebook…at least until the government has a problem with that too.

Premium on the Rise: Call me a Project Devil fan. With people visiting an average of 3 sites a day (one of them being Facebook), it’s kind of hard to argue with the

It's Time to Break out of Pure RTB Business Models

fact that advertising needs to be engaging on the page. Whether it’s video, over-sized RM banners, in-app ads, or sponsored apps, advertisers are looking to engage users directly, rather than drive them to a site. These opportunities are the opposite of commodity-based exchange buying. You can’t standardize them…and you can’t buy these engaging units cheaply. Advertisers are starting to rebel against the low quality of exchange-based media, and publishers are really starting to rebel against the returns they are seeing on exchanges. They want technology that helps them understand and sell their own audiences, rather than technology that disintermediates them and sells their valuable audiences for them. Maybe we finally jumped the shark with the Admeld acquisition. Wouldn’t it be nice if technology helped advertisers find the right audiences where they wanted to be found, and publishers sell their audiences for more than $0.50? Was there ever an industry that sustained itself by crushing their main suppliers down on price?

Big Guys Have More Data than You: I don’t care how many cookies you have out there on the Web. Is it 150 million? 200 million? It doesn’t really matter. How many Facebook subscribers are there? How many Google Gmail users? We have given the biggest publishers absolutely every single piece of information about ourselves (including, for some Congressmen, too much information), and shared it with our friends, and shared our friends’ data with everyone too. Where cookie-based targeting doesn’t scale, first party data targeting on sites like Facebook scales plenty. You would think the ability to reach users with such specificity would be expensive, but no. Facebook ads are the best deal in town. I have never paid more than $0.50 CPM for my audience, no matter how many “segments” I want to apply. I can’t remember winning many display media bids in for that price. If you consider that Google is just starting to get into display—and Facebook is just starting to look at display, doesn’t that make you want to change your data strategy a little bit? If your business depends on the sheer amount of your data, you may need to get a longer ruler and think about just how much scale you really have.

There are a lot of ad technology fish swimming in the RTB sea right now, and every single one of them is wet. My advice to them is to break the surface of the water for a second, and see what else is around. RTB will be a part of advertising for a long time, but it will not displace premium, guaranteed advertising. It will also look nothing like today’s RTB in a few years. The advent of private marketplaces, higher value audiences exposed in real time environments, and the emergence of smarter branding metrics (via Vizu and others) is going to turn the conversation back to premium quickly. Jump in…the water is going to be fine.

[This post appeared on 6/23/11 in AdMonsters]

Notes from DPS 2011

Going Beyond Content and Delivering Value in a Multi-Platform World

Deer Valley, UT – If there is one thing I learned after spending several days at Digital Publishing Summit 2011, is that the people in this industry really love what they do. It’s not easy walking past world class spring skiing in what is arguably the United States’ best ski area, and enter a dim conference room to listen to a speech on “Auto-nomous Data Management,” but every session played to an SRO crowd of media and technology executives. The crowd was a veritable who’s-who of the “Digital Display Advertising Landscape” (LUMA) map, so I suppose you could argue that these guys got where they are today by skipping lots of fun, and building advertising and media technology instead.

Among the highly informative (albeit sometimes sales-y) content at the conference, there were some gems to be had. So, here is DPS 2011, organized by quote:

“Value is shifting from those that produce the content, to those that deliver the experience of consuming it.” – Saul Berman, IBM

Saul Berman’s keynote address touched upon the disruption happening in our space, but even the overhyped keyword “disruption” doesn’t touch upon the true chaos happening as publishers learn how to navigate the through all the new social media, exchange-based sales, and various technology partnering opportunities out there. Do you make Facebook Connect your friend (as Kristine Shine from PopSugar Media does), to drive new unique visits, and build your audience? According to Shine, for her organization, the call was to “go all in” with Facebook. For others, like Todd Sawicki, CRO of Cheezburger, Facebook can kill publications by migrating all of their native traffic (like message board comments) to their environment, without returning the favor.

So, for publishers, the challenge is not just continuing to produce quality content, but to make it for a multi platform world, where consumers are just as likely to value the way they are consuming it. That means having a multi-platform approach—and a multi-revenue approach as well. Why does a full song from iTunes cost $0.99, but a 10-second sliver of that song, sold as a ringtone, cost $3.00? In that case, it is the application of content in a clever way that adds value, a nice use case for anyone monetizing content in an experiential way.

“Media will be sold like pork bellies” – Frank Addante, Rubicon Project

There was quite a bit of discussion around pricing at the conference, and the founder and CEO of the Rubicon Project was not wrong in insisting that, without significant changes, media would indeed be as commoditized as the humble pork belly. Unfortunately, this trend has already happened. Addante was right to highlight the unfortunate fact that the same article in the NY Times commands a $20CPM in print as opposed to $2CPM online. That value gap, Addante argues, can be closed by “realizing the true value of digital experiences.” Rubicon would like to see one big gigantic “open market” that enables the industry to expand the digital advertising pie from $40b to $400b with full participation, but the details were cloudy. If that market concept involves having publishers suddenly not to sell their entire remnant inventory into an exchange, then maybe we can avoid the pork bellies fate.  Addante may be on to something, however. What the industry needs is one trusted third party aggregate high quality inventory, and create value around it, but that battle is in its very nascent stages.

That being said, a good bit of the conversation was around pricing. Both Saul Berman and Tim Cadogan of OpenX deployed the airline pricing scenario, to argue for dynamic pricing models. For Cadogan, three levels of inventory equate to three levels of seating: Exclusive (first class), Premium Guaranteed (business class), and Non-Guaranteed (coach). Just as airlines frequently change the configuration of their seating to account for their routes, seasonality, and passenger mix, so must the industry dynamically price inventory, based on its placement and value. The OpenX Enterprise server hopes to achieve that by putting guaranteed and real time exchange inventory into the same platform, and use smart decisioning  technology to maximize yields. A very smart idea.

For Berman, it was not only about “having 5 different passengers, paying five different prices,” but also about exploring entirely new revenue models, like Apple did in “switching the razor blade model” with the iPhone (expensive “razor,” cheap “blades”). Publishers must go beyond monetizing their content through advertising, and start looking at generating revenue from the larger  “marketing” bucket. Right now, that is called “selling apps.”

“Premium brands need to be associated with premium content” — Eric Klotz, Pubmatic

Truer words have never been spoken. Klotz explored some recent survey data which asked publishers and advertisers how the way they are buying media is shifting. The results were fairly predictable: more and more budget is finding it’s way into real-time bidding environments, as brand and direct marketers seek new ways to target their desired audiences. That’s nothing new. What is changing rapidly, however, is that all marketers are demanding more placement control, increased transparency, and brand safety. Brands want the same direct connections with publishers they have enjoyed with guaranteed buying, with the ease and cost efficiency of exchange-based buying. The takeaway? If you are a publisher, and not looking at building private exchange connections with your demand side partners, you are in trouble.

That sentiment was hinted at in a panel called “Selling in a Cluttered Market.” For Jonas Abney of Hachette Filipacchi, “general content gets beaten by specific content every time.” Marketers are looking for laser-focused, topical content that captures user intent, rather than more generalized content. Moreoever, today’s advertising sale is more educational than ever. For panelists like AdMeld CEO Michael Barrett and PubMatic’s Andrew Rutledge, a sales force cannot simply have media experience–they have to know the ecosystem, and be prepared to add value by educating clients. For Whitepages VP of Sales Craig Paris, it is simple math: Agencies get 100+ unique sales calls a month, from an increasing amount of new technology and media companies. Unless you differentiate yourself, you are not going to win business. “Thirty percent of your day should be spent reading the industry trades so you can have credibility, and provide insights to your customers.”

“Nielsen says people visit 2.9 sites a day, and one of them is Facebook” — Greg Rogers, Pictela

Last minute speaker Greg Rogers of Pictela provided some insights on how premium advertising units (specifically the new IAB 300×1050 “Project Devil” unit from AOL) can drive user engagement. If the above quote is true, it means that brands have to find a way to engage the user more deeply on the the sites they visit every day, and that way is through interactive units. Rogers has data that points to “dramatic” CPM increases from premium RM units, and makes a case for replacing three 300×250 units with the single 300×1050 “devil” slot. Patch and Huffpo have seen great results, and advertisers are getting good engagement, and plenty of reporting. Highly premium, brand-safe, engaging advertising…sounds like something from the past called “premium guaranteed.” I bet PopSugar’s Shine would agree. She has built a virtual in-house agency to build premium campaigns for her customers, and demands “150% control over every ad unit on the page.”

“Cookie Targeting Doesn’t Scale” — Michael Hannon, Aperture

Sort of a dark horse moment for me was Michael Hannon’s first slide, which threw down the gauntlet on cookie targeting. All the energy in the space for the last several years has been about  targeting using 3rd party data . But what if it doesn’t work? This is the 900 lb. elephant in the Ecosystem. Not only have many marketers had difficulties achieving significant scale when overlaying data on top of exchange buys, but the legislative tsunami of “Do Not Track” threatens to reduce that scale even further. Hannon makes an elegant argument for real audience measurement, and doing so in a cookie-less way.

That leads me to a great conversation led by Alan Chapell, a lawyer specializing in just these types of issues. In a room full of ad publishing and ad technology executives that depend on using data to identify target audiences, there was a great deal of confusion regarding how our industry is getting on top of what may be a very severe problem. More direction from the IAB in the form of specific self-regulatory principles and mandates is needed, and needed fast. For Chapell, inaction may cause the “privacy disaster, which enables Google, AT&T, and Facebook to own all the data,”  leaving the rest of the industry on the side.

[This article originally appeared in Adotas on 4/4/11]