Today’s consumers are highly demanding. They expect curated movie recommendations from Netflix, one-click restaurant reservations from OpenTable, on-demand limousine service from Uber, limitless housing options from AirBnB and the world of commerce available 24/7 from Amazon Prime. It’s a great time to be alive for a consumer, but perhaps the worst possible time for the CMO of any other company. Just think, Uber doesn’t own cars. They are a technology company built from the ground up to deliver personalized service at scale to consumers—that’s what today’s marketing is all about.
Only a few short years ago, CMOs had a difficult, but simpler, remit: build the brand and the consumers follow. Absolut vodka was about as undifferentiated a product as anything on the market, but great packaging and a clever ad campaign made it a power brand. It thrived because the world still worked on the principles of How Brands Grow, Byron Sharp’s 2010 book. Sharp posited that a marketer needed two things to succeed: availability in the consumer’s mind and availability of the product at the shelf. Brands like P&G’s Tide control lots of mindshare with mass media budgets, and P&G ensures it is widely available at every supermarket so a consumer can easily choose between it and Wisk at the “moment of truth.”
That system is dying rapidly, as mass media channels become fragmented into thousands of websites, apps, streaming media channels and experiences we don’t even understand yet. As a marketer, you can’t “buy eyeballs” today like you used to. This paradigm is largely responsible for the ever-shrinking average CMO tenure (from 44 months last year to only 42 months today). CMO’s must be prepared to insert themselves along steps of the consumer journey that move from channel to channel, and also have the ability to capture each tiny piece of digital exhaust that consumers’ gadgets and gizmos throw off, helping to inform their understanding of how they engage with a brand.
To make it clear, here’s a chart:
|OLD CMO||NEW CMO|
|Rents access to people||Owns people data|
|One-to-many marketing||One-to-one engagement|
|Big bets on limited channels||Small bets on dozens of channels|
|One “big tent” message for many||Dozens of messages for segments|
|Panel-based attribution||Real-time feedback|
|Agency defines strategy||Marketer owns strategy, agency executes|
Yesterday’s CMO would “buy eyeballs” with big TV and print campaigns, and use subscriber information as a proxy for targeted reach. Today’s CMO wants to own cookies and mobile keys so they can have a one-to-one conversation. Yesterday’s CMO looked at the performance at the end of a campaign, and optimized for the next one based on results from a survey. Today’s CMOs crave access to real-time performance data so they can optimize at run time. Things couldn’t be more different.
In this new norm, what should CMOs do to ensure they stay ahead of the curve? They have to change the way they think about consumer identity and how that impacts their work as marketers–and redefine the way they think about “marketing” in general.
Identity beyond IDs
A few months ago, I wrote that “identity is the new basis of competition” in marketing. That’s still true—you can’t build meaningful cross-channel experiences if you can’t tie people together with their devices. To that end, I recently was invited to an internal town hall with marketers from a large beauty company where the CMO announced that they just now eclipsed over 500 million addressable IDs in their data management platform. Her staff started clapping. Why? Because these weren’t known buyers, just cookies and mobile IDs—but they represented the ability for marketers to connect and build experiences for anonymous people who interacted with their website, mobile app or an ad. That has real, tangible value.
But, devices don’t buy things, people do. Just because you have a good device graph with billions of cookies, e-mail addresses and mobile keys doesn’t mean you have a good view of the people behind that information. Identity data must be augmented with data from systems of engagement to formulate a true view of the consumer. Every click, download, article read, and video view throws off digital exhaust that is filled with scraps of information that machines can use to paint a truer picture of a consumer’s identity. When marketers start valuing all data as a financial asset, they are starting the process of turning IDs into people.
For those of us in the industry, we can be forgiven if we think the world revolves around display, social, mobile and video advertising. We’ve gotten really good at delivering personalized digital experiences in real time, and we have a Lumascape full of clever technologies that are moving the needle for brands that are trying to reach connected consumers. CMOs must think outside the Lumascape, and connect these important addressable touchpoints to mass channels like TV, radio and print in order to deliver personalized experiences at scale.
More than Marketing
The problem is that our definition of marketing often misses the concept of touch points that can exist separately from marketing. These touch points can include interactions between salespeople and potential customers, what happens when a product is returned, conversations on community sites and forums where customers talk to each other about a brand, and also within the e-commerce experience when a consumer is making a purchase. These are arguably more valuable interactions with consumers than a digital banner ad or email because these are either people that are existing customers or those about to buy. They’re incredibly valuable to a brand and don’t involve the traditional notion of “marketing” whatsoever.
Let’s take a look at an example. I fly Delta because I love their app, and they reward my loyalty with special phone numbers so I can reach someone no matter how hairy things get throughout my travel experience. Every time I interact with their website, app and service representative is an opportunity for Delta to market to me—and also an opportunity for the brand to learn more about the way I fly and what matters most to me as a consumer. Getting it consistently right keeps me loyal, but getting even slightly wrong brings me one step closer to tweeting #DeltaStinks. Not fair, but that’s representative of brand relationships today.
To be successful, CMOs must expand their definition of identity. “Identity” is more than just an ID. It’s what is formed after capturing every possible insight from every interaction. And “marketing” is not just about cross-channel messaging, it’s about creating great consumer experiences with every touchpoint that happens including sales, service, commerce and more.
It’s a great time to be a data-driven marketer.
[This article originally appeared in AdExchanger on 10.16.2017]
Today, eConsultancy launches Best Practices in Digital Display Advertising, a comprehensive look at how to efficiently manage online advertising. We asked the author, Chris O’Hara, about the report and work that went into it.
Why did you write Best Practices in Digital Display Media?
In my last job, a good part of my assignment was traveling around the country visiting with about 500 regional advertising agencies and marketers, large and small, over three years. I was selling ad technology. Most advertisers seemed extremely engaged and interested to find out about new tools and technology that could help them bring efficiency to their business and, more importantly, results to their clients. The problem was that they didn’t have time to evaluate the 250+ vendors in the space, and certainly didn’t have the resources (financial or time) to really evaluate their options and get a sense of what’s working and what isn’t.
First and foremost, I wanted the report to be a good, comprehensive primer to what’s out there for digital marketers including digital ad agencies. That way, someone looking at engaging with data vendors, say, could get an idea of whether they needed one big relationship (with an aggregator), no data relationships, or needed very specific deals with key data providers. The guide can help set the basis for those evaluations. Marketers have been basically forced to license their own “technology stack” to be proficient at buying banner ads. I hope the Guide will be a map through that process.
What was the methodology you used to put it together?
I essentially looked at the digital display ecosystem through the lens of a marketer trying to take a campaign from initial concept through to billing, and making sure I covered the keys parts of the workflow chain. What technologies do you employ to find the right media, to buy it, and ultimately to measure it? Are all of these technologies leading to the promised land of efficiency and performance? Will they eventually? I used those questions as the basis of my approach, and leveraged the many vendor relationships and available data to try and answer some of those questions.
What’s the biggest thing to take away from the report?
I think the one thing that really runs through the entire report is the importance of data. I think the World Economic Forum originally said the “data is the new oil” [actually, the earliest citation we can find is from Michael Palmer in 2006, quoting Clive Humby] and many others have since parroted that sentiment. If you think about the 250-odd technology companies that populate the “ecosystem,” most are part of the trend towards audience buying, which is another way of saying “data-driven marketing.” Data runs through everything the digital marketer does, from research through to performance reporting and attribution. In a sense, the Guide is about the various technologies and methodologies for getting a grip on marketing data—and leveraging it to maximum effect.
There’s an explosion of three letter acronyms these days (DSP, DMP, SSP, AMP, etc) that marketers are still trying to sort out. Do we need all of them? Is there another one around the corner?
I am not really sure what the next big acronym will be, but you can be certain there will be several more categories to come, as technology changes (along with many updates to Guides such as these). That being said, I think the meta-trends you will see involve a certain “compression” by both ends of the spectrum, where the demand side and supply side players look to build more of their own data-driven capabilities. Publishers obviously want to use more of their own data to layer targeting on top of site traffic and get incremental CPM lift on every marketable impression. By the same token, advertisers are finding the costs of storing data remarkably cheap, and want to leverage that data for targeting, so they are building their own capabilities to do that. That means the whole space thrives on disintermediation. Whereas before, the tech companies were able to eat away at the margins, you will see the real players in the space build, license, or buy technology that puts them back in the driver’s seat. TheBest Practices in Digital Display Advertising Guide is kind of the “program” for this interesting game.
To learn more about the Best Practices in Digital Display Advertising Guide, download the report here.
Technology may still capture the most advertising value, but what if publishers own it?
A few years ago, ad technology banker Terence Kawaja gave a groundbreaking IAB presentation entitled, “Parsing the Mayhem: Developments in the Advertising Technology Landscape.” Ever since then, his famed logo vomit slide featuring (then) 290 different tech companies has been passed around more than a Derek Jeter rookie card.
While the eye chart continues to change, the really important slide in that deck essentially remains the same. The “Carving up the stack” slide (see above), which depicts how little revenue publishers see at the end of the ad technology chain, has changed little since May 2010. In fact you could argue that it has gotten worse. The original slide described the path of an advertiser’s $5 as it made it’s way past the agency, through ad networks and exchanges, and finally into the publisher’s pocket.
The agency took about $0.50 (10%), the ad networks grabbed the biggest portion at $2.00 (40%), the data provider took two bits (5%), the ad exchange sucked out $0.35 (7%), and the ad server grabbed a small sliver worth $0.10 (2%), for a grand total of 64%. The publisher was left with a measly $1.80. The story hasn’t changed, and neither have the players, but the amounts have altered slightly.
While Kawaja correctly argued that DSPs provided some value back to both advertisers and publishers through efficiency, let’s look ahead through the lens of the original slide. Here’s what has happened to the players over the last 2 years:
- Advertiser: The advertiser continues to be in the cat bird seat, enjoying the fact that more and more technology is coming to his aid to make buying directly a fact of life. Yes, the agency is still a necessary (and welcomed) evil, but with Facebook, Google, Pandora, and all of the big publishers willing to provide robust customer service for the biggest spenders, he’s not giving up much. Plus, agency margins continue to shrink, meaning more of their $5.00 ends up as display, video, and rich media units on popular sites.
- Agency: It’s been a tough ride for agencies lately. Let’s face it: more and more spending is going to social networks, and you don’t need to pay 10%-15% to find audiences with Facebook. You simply plug in audience attributes and buy. With average CPMs in the $0.50 range (as opposed to $2.50 for the Web as a whole), advertisers have more and more reason to find targeted reach by themselves, or with Facebook’s help. Google nascent search-keyword powered display network isn’t exactly helping matters. Agencies are trying to adapt and become technology enablers, but that’s a long putt for an industry that has long depended on underpaying 22 year olds to manage multi-million dollar ad budgets, rather than overpaying 22 year old engineers to build products.
- Networks: Everyone’s talking about the demise of the ad network, but they really haven’t disappeared. Yesterday’s ad networks (Turn, Lotame) are today’s “data management platforms.” Instead of packaging the inventory, they are letting publishers do it themselves. This is the right instinct, but legacy networks may well be overestimating the extent to which the bulk of publishers are willing (and able) to do this work. Networks (and especially vertical networks) thrived because they were convenient—and they worked. Horizontal networks are dying, and the money is simply leaking into the data-powered exchange space…
- Data Providers: There’s data, and then there’s data. With ubiquitous access to Experian, IXI, and other popular data types through 3rd party providers, the value of 3rd party segments has declined dramatically. Great exchanges like eXelate give marketers a one-stop shop for almost every off-the-shelf segment worth purchasing, so you don’t need to strike 20 different license deals. Yet, data is still the lifeblood of the ecosystem. Unfortunately for pure-play segment providers, the real value is in helping advertisers unlock the value of their first party data. The value of 3rd party data will continue to decline, especially as more and more marketers use less of it to create “seeds” from which lookalike models are created.
- Exchanges: Exchanges have been the biggest beneficiary of the move away from ad networks. Data + Exchange = Ad Network. Now that there are so many plug and play technologies giving advertisers access to the world of exchanges, the money had flowed away from the networks and into the pockets of Google AdX, Microsoft, Rubicon. PubMatic, and RMX.
- Ad Serving: Ad serving will always be a tax on digital advertising but, as providers in the video and rich media space provide more value, their chunk of the advertiser pie has increased. Yes, serving is a $0.03 commodity, but there is still money to be made in dynamic allocation technology, reporting, and tag management. As an industry, we like to solve the problems we create, and make our solutions expensive. As the technology moves away from standardized display, new “ad enablement” technologies will add value, and be able to capture more share.
- Publisher: Agencies, networks, and technologists have bamboozled big publishers for years, but now smart publishers are starting to strike back. With smart data management, they are now able to realize the value of their own audiences—without the networks and exchanges getting the lion’s share of the budget. This has everything to do with leveraging today’s new data management technology to unlock the value of first party data—and more quickly aggregate all available data types to do rapid audience discovery and segmentation.
The slide we are going to be seeing in 2012, 2013 and beyond will show publishers with a much larger share, as they take control of their own data. Data management technology is not just the sole province of the “Big Five” publishers anymore. Now, even mid-sized publishers can leverage data management technology to discover their audiences, segment them, and create reach extension through lookalike modeling. Instead of going to a network and getting $0.65 for “in-market auto intenders” they are creating their own—and getting $15.00.
Now, that’s a much bigger slice of the advertising pie.
[This post originally appeared in ClickZ on 2/1/12]
Today’s digital media agency has access to enormous amounts of data, but using it effectively is what is going to make the difference between the shops of the future and the also-rans. Delivering data-driven insights is the key to being a 21st century agency. Here are three ways you should be working with data to secure your future:
How much time are you and your colleagues spending collating data, building reports, and formatting spreadsheets and PowerPoint decks for your clients? Most of the agencies I have worked with over the years admit to dedicating an embarrassingly large amount of (highly expensive) time towards these menial tasks. It’s not that getting your clients the data they need is not worth the time, it’s simply that there are now so many automated ways to deliver the data without burning salary.
To paraphrase former agency head and Akamai leader David Kenny, if you are doing things with people that you can be doing with computers, you have already lost. Why spend time formatting Excel spreadsheets and populating PowerPoint report templates with data, when you can be spending salaried employee time selling more services, optimizing campaigns, and delivering great strategy and creative? Today’s automated ad management solutions and DMPs offer powerful ways to port both audience and ad serving reporting data into a single interface, to get instant access to key metrics such as frequency to conversion, churn rate, and channel attribution.
Ask yourself if the cost of such a system is more than the cost of the time your employees you have been spending building reports—and, ultimately, more than the cost of your eventual demise, should you ignore the changes afoot in your business.
Aggregate and Activate it
Think of all the data you have access to from a digital media standpoint. If you are helping clients execute a digital media campaign, you have traditional serving data from your demand side server, such as DFA. You probably also have engagement data from your rich media ad server. If you have access to your clients’ website pages (or at least tags there), you have site-side data, including conversion event data. If you are using an audience measurement tool, or are doing audience-specific buying through a demand side platform, you also have audience measurement data. Great. What are you doing with all of it? Moreover, what kind of data does your client have that you can help them add to activate the common advertising data types I have just described?
Let’s take the example of an agency using an audience measurement reporting tool, alongside an ad server report. In this case, it is possible that the analyst knows that the highest frequency converters for his travel campaign belong to a popular PRIZM segment, and he may also know that visitors to a popular travel site are three times as likely to engage with his rich media ad creative. Now what? Obviously, the right move is to buy more of the audience segment and double up with guaranteed advertising on the travel site. But what about audience overlap?
How can the advertiser reduce ad waste by ensuring that members of his audience segment that he is securing for as little as $2.00 CPM on exchanges are not overrepresented on the premium site for which he is paying $18.00 CPM? Plus, how many members of that audience are also already registered as customers? If you are not deploying a DMP to aggregate your clients’ CRM (first-party) data alongside the site-side and ad serving (2nd party) data and the purchased (3rd party) data segments, then there is going to lots of duplicated uniques in your audience. Smart data aggregation creates ad activation through waste reduction, lifting conversion rates, while lowering cost per conversion. Getting an effective universal frequency cap across digital channels is very difficult, but every dollar not wasted on duplicate impressions is another dollar that may be spent finding a new audience member. Reducing waste adds reach—and performance, which every client likes.
As a digital media agency, you’ve run hundreds, perhaps even thousands of campaigns, producing thousands of data-rich reports for your clients. How much of that knowledge are you leveraging? Although you might know the top travel sites and audience segments to reach “moms of school-age children in-market for a beach vacation,” how readily available is that knowledge? Is it sitting inside your Media Director’s head, or hidden in various documents that don’t talk to one another? How about access to normative campaign data? How quickly can you find out how certain sites performed against similar KPIs without doing hours of research?
Like or not, advertisers want to know how their campaigns are performing against known standards, and it’s gotten a lot more complicated than beating a 0.1% click-through rate lately. Knowing how your last 10 travel campaigns performed—from which guaranteed site buys succeeded, to which audience segments performed, to which creatives elicited the highest CTR—is just step one. Having that data available for quick reference means that every new campaign can start from an advanced performance level, and your media people don’t have to recreate the wheel every time you receive an RFP.
Today’s smart DMPs also feature the ability to leverage your data to an even greater extent, especially for audience buying. Why limit yourself to pre-packaged audience segments that do not include your client’s first-party data? Today’s more advanced DMPs give marketers the ability to create audience segments on the fly, building discrete segments from data that includes available third-party data—but also first-party data, such as registration details, transactional records, and signals from hosted social media listening solutions. It’s the difference between buying from an ad network and creating your own.
Buying into portals’ site sections was the first phase in the effort to bring contextual and audience relevance to ad buying. Networks followed, offering packaged audiences at scale. Then bidded exchange buying came, offering pre-packaged audience segments at the individual cookie level. Today’s best practices include marrying all available data types to give marketers the ability to create their own targeted buys, and modern data management platforms are helping the largest advertisers automate what they have been doing since the first direct mail piece went out: finding targeted audiences. Leveraging today’s DMP technology can not only help you find those audiences more easily, but help you understand who they are, why they respond, and help you find them again.
Chris O’Hara is head of strategic partnerships for nPario, a DMP with clients that include Yahoo! and Electronic Arts, among others. A frequent contributor to industry publications, this is his first column for The Agency Post. He can be reached through his blog on www.chrisohara.com
[This article originally appeared in The Agency Post on 1/25/12]
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.
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.
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.
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.
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.
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]