Creating the Fabled 360 View of the Consumer

ImageDespite years of online targeting, the idea of having a complete, holistic “360 degree view” of the consumer has been somewhat of a unicorn. Today’s new DMP landscape and cross-device identification technologies are starting to come close, but they are missing a key piece of the puzzle: the ability to incorporate key social affinities.

In the nearby chart, you can see that online consumers tell us all about themselves in a number of ways:

Viewing Affinities: Where they go online and what they like to look at provides strong signals of what they are interested in. Nielsen, comScore, Arbitron and others have great viewership/listenership data that is strong on demographics, so we can get a great sense of the type of folks a certain website or show attracts. This is great, but brands still struggle to align demographic qualities perfectly with brand engagement. 34 year old men should like ESPN, but they could easily love Cooking.com more.

Buying Affinities: What about a person’s buying habits? Kantar Retail, OwnerIQ, and Claritas data all tell us in great detail what people shop for and own—but they lack information on why people buy the stuff they do. What gets folks staring at a shelf to “The Moment of Truth” (in P&G parlance) when they decide to make a purchase? The buying data alone cannot tell us.

Conversational Affinity: What about what people talk about online? Radian6 (Salesforce), Crimson Hexagon, and others really dig into social conversations and can provide tons of data that brands can use to get a general sense of sentiment. But this data, alone, lacks the lens of behavior to give it actionable context.

Social Behavioral Affinity: Finally, what about the actions people take in social environments? What if we could measure not just what people “like” or “follow” online, but what they actually do (like post a video, tweet a hashtag, or engage with a fan page)? That data not only covers multiple facets of consumer affinity, but also gives a more holistic view of what the consumer is engaged with.

Adding social affinity data to the mix to understand a consumer can be a powerful way to understand how brands relate to the many things people spend their time with (celebrities, teams, books, websites, musicians, etc.). Aligning this data with viewing, buying, and conversational data gets you as close as possible to that holistic view.

Let’s take an example of actionable social affinity in play. Say Whole Foods is looking for a new celebrity to use in television and online video ads. Conventional practice would be to engage with a research firm who would employ the “Q Score” model to measure which celebrity had the most consumer appeal and recognition. This attitudinal data is derived from surveys, some with large enough sample sizes to offer validity, but it is still “soft data.”

Looking through the lens of social data, you might also measure forward affinity: how many social fans of Whole Foods expressed a Facebook “like” for Beyonce, or followed her account on Twitter? This measurement has some value, but fails at delivering relevance because of the scale effect. In other words, I like Beyonce, so does my wife, and so does my daughter . . . along with many millions of other fans—so many that it’s hard to differentiate them. The more popular something is, the broader appeal and less targetability that attribute has.

So, how do you make social affinity data relevant to get a broader, more holistic, understanding of the consumer?

Obviously, both Q Score and forward affinity can be highly valuable. But when mixing viewing, buying, and listening with real social affinity data, much more becomes possible. The real power of this data comes out when you measure two things against one another. Sree Nagarajan, CEO of Affinity Answers, explained this mutual affinity concept to me recently:

“In order for the engagement to be truly effective, it needs to be measured from both sides (mutual engagement). The parallel is a real-world relationship. It’s not enough for me to like you, but you have to like me for us to have a relationship. Mapped to the brand affinity world, it’s not enough for Whole Foods fans to engage with Beyonce; enough Beyonce fans have to engage with Whole Foods (more than the population average on both sides) to make this relationship truly meaningful and thus actionable. When true engagement is married with such mutual engagement, the result is intelligence that filters out the noise in social networks to surface meaningful relationships.”

As an example, this approach was recently employed by Pepsi to choose Nicki Minaj as their spokesperson over several other well-known celebrities.

What else can social affinity data do?

  • Brands can use social affinity data to decide what content or sponsorships to produce for their users. Looking at their users’ mutual affinity between the brand and music, for example, might suggest which bands to sponsor and blog about.
  • A publisher’s ad sales team can use such data to understand the mutual affinity between itself and different brands. A highly correlated affinity between activated social visitors to GourmetAds’ Facebook page and those who post on Capital One’s Facebook page may suggest a previously unknown sales opportunity. The publisher can now prove that his audience has a positive predisposition towards the brand, which can yield higher conversions in an acquisition campaign.
  • What about media buying? Understanding the social affinity of fans for a television show can produce powerful actionable insights. As an example, understanding that fans of “Teen Wolf” spend more time on Twitter than Facebook will instruct the show’s marketing team to increase tweets—and post more questions that lead to increased retweets and replies. Conversely, an Adult Swim show may have more Facebook commenters, leading the marketer to amplify the effect of existing “likes” by purchasing sponsored posts.
  • Keyword buying is also interesting. Probing the mutual affinities between brands and celebrities, shows, music acts, and more can yield long tail suggested keyword targets for Google, Bing/Yahoo, and Facebook that are less expensive and provide more reach than those that are automatically suggested. As an example, when “Beavis and Butthead” re-launched on MTV, Google suggested keywords for an SEM campaign such as “Mike Judge” (the show’s creator) and “animated show.” Social affinity data suggested that socially activated Beavis fans also loved “Breaking Bad.” Guess what? Nobody else was bidding on that keyword, and that meant more reach, relevance, and results.

I believe that understanding social affinity data is the missing piece of the “360 degree view” puzzle. Adding this powerful data to online viewing, buying, and social listening data can open up new ways to understand consumer behavior. Ultimately, this type of data can be used to generate results (and measure them) in online branding campaigns that have thus far been elusive.

Want a full view of the people who are predisposed to love your brand? Understand what you both mutually care about through social affinities—and measure it.

[This post originally appeared in AdExchanger on 4.14.14]

 

The Battle for Workflow Automation: What’s Next for “Programmatic Direct”

ImageEven though programmatic RTB has seen the lion’s share of venture capital funding and an enormous amount of innovation, RTB buying only accounts for 20%-30% of all digital media dollars. The real money still flows through the direct buying process, with agencies spending up to 400 hours and $50,000 to create the typical campaign, and publishers burning through 1,600 hours a month and 18% of their revenue responding to RFPs. What a mess….and an opportunity.

Everybody’s battling for a slice of that direct sales pie, and the game is all about helping buyers and sellers automate the manual processes that drive almost 80% of transactional value.

The Holy Grail for both sides is a web based, connected platform that will enable planners and sellers to thrust aside Excel, and start to transact business in the cloud. Although a number of companies have tried and failed to deliver on the promise of workflow automation, the time seems ripe for true adoption, as agencies are being challenged by their clients to create the same programmatic efficiencies across all media channels that they have embraced with RTB. As we speak, winners and losers are being selected, so let’s look at the landscape.

When you look at all of the companies providing a slice of the end-to-end workflow just in digital media execution, it’s hard to imagine that there can be “one system to rule them all” or a true “OS” for digital media. Yet, the dream is just that: An end-to-end comprehensive “stack” that handles media from research through to billing, and eliminates the many manual tasks and man hours involved in connecting the dots. But what are the realities? Let’s saddle up this unicorn and take a ride:

The End of the End-to-End Stack?

The notion of a single end-to-end “stack” for the digital marketer is a tough vision to execute upon. Build a system that has every little feature that a huge agency needs and you have effectively built something no one else can use. The flip side is building something so standardized that individual organizations find little value in it. The “operating systems” of the future that will win should enable agencies and marketers to leverage a standard operating system, but customize it with their own pricing, performance, and vendor data. This enables the efficiency of standardization while enabling data to provide the “secret sauce” that media shops need to justify their fees.  More importantly, the modern operating system for media must be extensible, to allow for a wide variety of point solutions to integrate seamlessly. The right system will certainly eliminate a few logins, but must not limit the numbers of tools that can be accessed through it. That concept necessitates a highly modern, scalable, API-driven, web-based platform. It will be interesting to see how today’s legacy systems (which are exactly the opposite of what I have described) adapt.

Hegemon Your Bets

Several years ago, I wrote that the merger between Mediabank and Donovan may actually be a good thing—provided it offered more choice, flexibility, and open standards. Looking some three years later, I am not sure agencies have any more of that today. Like any other near monopoly, Mediaocean has a disincentive to open up its ecosystem because it invites competition. So time will tell whether their nascent “Connect” effort will become a way for agencies to quickly consolidate their “stack” around a flexible operating system—or if it’s just an integration tax for vendors (a revenue strategy quickly becoming known as the “Lumascrape”). After an IPO, the company will face enormous quarterly pressure for growth. It will be hard to raise prices on already stretched agencies, so publishers will be in the crosshairs. I smell “marketplace” and some monetization strategies around “programmatic direct” enablement for guaranteed media. And what about open standards? Despite years of work by the IAB, the standards and protocols for creating electronic ordering and invoicing are still very much in flux.

Connecting the Dots

More than anything else, the most exciting thing happening in digital media is seeing real programmatic connections between buyers and sellers for guaranteed media. After so much innovation in programmatic RTB (hundreds of vendors, billions in venture capital), we now have some amazing pipes that impressions can flow through. Unfortunately, this has largely been limited to lower classes of inventory and focused almost exclusively on the DR space. Creating the same programmatic efficiencies for “premium” brand-safe inventory is now starting to happen. Whether it comes from new “programmatic direct” pure play technologies, or happens through the RTB pipes, it will not happen successfully without transparency. That means giving publishers control over their inventory, pricing, and what demand partners can access their marketplaces. Will these connections thrive? Not if vendors charge network-like fees, arbitrage media, or don’t provide transparency. Will the endemic fraud in programmatic RTB push more transactions outside the RTB pipes? I think so, and a lot of publishers (see Yahoo/AOL/Microsoft deal) are betting that there are better ways for buyers to access their inventory.

Time for Real Time

Look at all the RTB players who want a piece of the guaranteed action. Three of them (Rubicon, Appnexus, and Pubmatic) will IPO soon, and be under tremendous pressure to increase revenue, margins, and continue to innovate and find new markets. When international expansion stops providing double-digit growth increases, then it’s time to look toward new streams of demand generation—namely, the 80% of deals not currently flowing through their pipes. Those pipes have been engineered for real-time bidding, but guaranteed deals are neither real-time nor bidded. Can they innovate fast enough to provide real value between buyers and sellers? Can they apply years of innovation in DSP and SSP tech to the more prosaic problem of workflow automation? Probably, but there are still business model issues to work out. Most of these companies have put a stake in the ground for either publishers or marketers, and a transactional platform must be agnostic to sit in the middle. It will be interesting to see how new offerings are received in the marketplace.

As the Chinese curse says, “may you live in interesting times.” Indeed, the past several years of ad tech has been nothing but interesting, but the real action is just starting—and it’s taking place in what was the most uninteresting field of workflow automation.

[This post originally appeared in AdExchanger on 3.12.14]

The Four Keys to Programmatic Direct Success

SuccessI was recently talking to the Chief Digital Officer of a large agency that does a lot of digital media buying. He has been working closely with a number of software providers to standardize his operations on a media management system. Getting all his vendor information, order management, and billing information has been a huge undertaking. Apparently, half the battle at an agency is getting paid (getting paid in less than 120 days is the other half)!

We were talking about some of the upfront processes behind putting together a media plan, which were mostly manual: putting the actual plan together in Excel, trading e-mails back and forth with vendors in the RFP process, trafficking ad tags, collecting screenshots, etc. Wouldn’t it be valuable if computers could streamline much of that work, and connect buyers and sellers together more seamlessly?

He agreed that it would truly transform his business, but accepted much of that manual work as part of the cost of doing business (paid for, incidentally, by his clients). The real way to transform his business, he said, was to answer the following questions. If “programmatic direct” technologies simply nailed down these four things, the payoff would be enormous. I paraphrase his answers below:

How much should I buy?  “I basically know that I am going to have AOL, Yahoo, Facebook, and GDN on almost every plan. For my more vertical clients, in auto for example, I also know 95% of the sites and networks I am going to be on. Sure, I use research tools to validate those recommendations to my clients, but media discovery is not a huge pain point. Where we struggle is answering the question of media investment allocation. Should I spend 30% of my budget with Facebook? 40%? I really don’t know, and often don’t have the right mix until the campaign is nearly over. It would be great to have some business intelligence built into a system that recommended my guaranteed media mix programmatically.”

What should I pay? “I also have a pretty good idea what things cost, thanks to the RFP process. When you RFP 40 publishers in a vertical, you find out pretty quickly what your best pricing for guaranteed media is, and you can leverage that information to insure you are giving your clients competitive rates. Unfortunately, it feels like we go through this exercise every time on every RFP. We have the historical pricing data, but it’s all over the place in spreadsheets—and often in the planner’s heads. It would be great if this information was in the same place, and if a system could make pricing recommendations up front in the process, which would also shorten the negotiation process with publishers.

Why am I recommending this?  “The biggest thing we struggle with is justifying our media choices to our clients. When we present a recommendation, often we are asking our client to invest hundreds of thousands or even millions in an individual vendor. My deck has to have more in it than basic audience information. I have to talk about the media’s ability to perform and hit certain KPIs for the price. It would be really useful to have recommendations come with some metrics on how such placements performed historically, or even some data on how other, similar, investments moved the needle in the past. Right now, getting to that data is nearly impossible, and usual resides with your senior planner in the account. The other obvious problem with that is employee turnover. My best planners, along with everything they’ve learned over two or three years walk out the door along with my data and relationships. The right system should store all of that institutional knowledge.”

You need that when? “The other thing a system can help with is speed to market. Publishers hate it when we ask them for huge, innovative proposals—in 24 hours. The reason we do that is because our clients ask us for amazing and innovative media recommendations in 48 hours. The pressure to deliver plans is huge, and you can easily lose large chunks of business by reacting to such requests too slowly. What programmatic direct technology may be able to help with is giving planners access to tools that compress the pre-planning process down, and enable agencies to deliver thoughtful, data-backed recommendations out fast—and at scale.”

Especially for larger agencies, programmatic direct technology has to be more than just workflow efficiency tools and automating the insertion order. (Although that has to come first). The next generation of programmatic efficiency or guaranteed media has to include serious business intelligence tools that can solve the “how” while simultaneously answering “why.”

[This post orginally appeared in AdExchanger on 2.11.14]

The Nuts and Bolts of Programmatic Direct

ImageAn interview with Econsultancy’s Monica Savut and me, on the recently published programmatic direct whitepaper.

Econsultancy: Why now? In other words, why has this “programmatic direct” trend been on the radar lately? What’s driving all of the conversation the space?

Chris O’Hara: It’s really something my boss Joe Pych calls the “Sutton Pivot,” inspired by the famous thief Willie Sutton who robbed banks “because that’s where the money was.” Over 70% of digital display dollars are transacted in a very manual way today. Despite all the LUMAscape hype over RTB, most of the digital money still gets transacted through the request-for-proposal (RFP) process. Everybody wants a piece of the action, hence the “Sutton pivot,” in which all the ad tech companies are running to try and provide automation technology for directly sold deals. It’s actually a good thing. Today’s process for buying guaranteed digital media can take over 40 steps and suck up over 10% of media budgets just in man hours.

Q: The concept of “programmatic direct” or “programmatic premium” is a relatively new phenomenon, but it’s really just about automating the buying process for digital media, right? What makes it different from the automation happening in real-time bidding? What’s the difference?

A: Real-time bidding, or what we are starting to call “programmatic RTB” has been a real boon to the industry. We now have a set of “pipes” which connect demand- and supply-side platforms that make the digital media procurement process hugely efficient. Today’s systems are modern, cloud-based, scalable, and super low latency. We are seeing the type of liquidity and deal flow that happens in systems like NYSE and NASDAQ. That said, 70% of buying that happens in digital is neither “real time” nor “bidded.” It’s just two organizations trying to make a deal. You need different technology to enable that kind of guaranteed transaction, and marketers are starting to wonder why they are paying so much in transactional costs to access higher classes of digital inventory. RTB proved that efficiency can happen in digital, and now marketers want faster and more efficient access to more than just remnant inventory.

Q: You say that agencies have a “perverse incentive” to embrace efficiency in buying. It would seem counter to everything that is happening in the programmatic space at the moment. How do demand side business models need to adapt for programmatic direct to become a reality?

A: Agencies make money when plans take 400 hours to create. Manually trafficking line items in an ad server, and cutting and pasting publisher insertion orders pays the bills for agencies who charge on a “cost-plus” basis. Digital media agencies have been operating that way for years: hire cheap, work the “23 year old media planner” hard, and earn a mark-up on their labor. Nothing wrong with work-for hire, but the RTB phenomenon—and marketers experience with easy-to-use programmatic platforms in search and social marketing—have changed the dynamic entirely. Agencies have to do more than heavy lifting now to survive. They need to hire fewer, smarter, people to leverage systems—and more great creative and analytical people to make sure they are driving digital messages that inspire—and meet KPIs. The days of getting paid to traffic ads in MediaVisor are over. That’s a big time cultural change for agencies. A lot of shops won’t survive the transition, and that’s a good thing.

Q: What are some of the things—beyond cultural change—that need to happen to create this new era of programmatic direct efficiency? What’s missing?

A: We tend to think of digital as this highly advanced form of marketing, but it’s really the most backwards. Direct mail costs something like $750 per thousand (CPM) to put a catalog in the mail—and marketers like LL Bean make that number work consistently. Digital struggles to make $10 CPA goals work on $5 products. That’s really lame. Part of the problem is the lack of basic information available to the marketer. If I want to buy a direct mail list, I can find out how many folks in the list live in San Francisco, and have purchased a product by credit card in the last month. I can find out how much it costs to by that list—and who sells it. Until recently digital media has had no such directory. Not only that, but the industry lacks even the most basic set of electronic ordering protocols, that can enable systems to understand each other in electronic transactions. The good news is that more work has occurred on this front in the last two weeks than has happened in the 5 years the IAB has been promoting “eBusiness” initiatives. Look for some significant announcements in this area soon.

Q: Who benefits most from adopting programmatic direct strategies? Publishers? Agencies? The marketers themselves? Are there winners and losers if this new tactic sees adoption at scale?

A: It’s easy to say that “everyone’s a winner” with programmatic direct adoption at scale, but that’s not entirely true. I think publishers are the big winners, because they are starting to take some control back over the procurement process from the demand side. I think longer tail sites that depend on RTB revenue streams will continue to be able to get access to demand at scale through RTB systems, and still get their AdSense money. But what really excites me is seeing high quality publishers that own high quality real estate on category specific properties finally get more control over pricing and partner selection. This will be even more critical as publishers expand their offerings cross-channel, into video. Publishers need a programmatic way to sell their higher classes of inventory, and not be so dependent on prevailing procurement methodologies which overvalues biddable, commoditized inventory. Agencies who value higher class inventory also win, of course.

Q: Right now, the conversation (and action) seems limited to display media. How does “programmatic direct” impact cross-channel buying?

A: Everything digital will be bought “programmatically” in 5 years. Some will be RTB display, and some will be display, native, and video inventory purchased through “programmatic direct” platforms. Addressable television, digital out-of-home (DOOH), and other channels will also factor in. Once we can get a true unique identifier that makes sense from a technology and privacy standpoint (big question, obviously), then marketers will really be living in programmatic heaven.

Q: You’ve been working in the “programmatic direct” space for a long time (staring at TRAFFIQ in 2008), and yet there seems to be fairly little adoption of the concept among agencies. Are you crazy? Why keep doing it? Will there be a big payoff in the end?

A: Change is really hard, especially when the pace of change is as rapid as in digital ad technology. When I was on the publisher sales side, there was always something that bothered me about getting a $200,000 insertion order for digital advertising through a fax machine. That stuff still happens today. Ultimately, I so believe that true process automation will happen in digital media, and that we can free people in the space to stop doing a lot of manual grunt work, and start being truly creative. I was watching a documentary the other night, and an engineer was talking about why he loved his job. He said he spent the last three years building a bridge that eliminated 10 minutes from the commute for some 20,000 people a day. “I saved people over 50,000 days of productivity last year,” the engineer explained, adding, “I wonder what those people are doing with all that extra time.”

There are a lot of young people who go into an agency thinking that they are going to help make the next kick-ass viral ad, but they end up working until 10 o’clock at night pasting line items into an ad server. I really think that, if we can change that, great things will happen.

[Originally published 12/5/2013 on the Econsultancy blog]

Aside

We’ve Got it all Backwards (Guest Post)

IntendersDigital Display Can Create Customers, Not Just Close Them

The large majority of marketers put a ton of money into traditional marketing channels, using “branding media” to drive interest in their products. Later, they allocate digital budget for “scooping them up” with retargeting and other cookie-based targeting tactics. After all, “intenders” have already raised their hand digitally, making them easy to find. They already have expressed an interest in the marketers product by visiting the website, leaving something in a shopping cart, or just “looking like” the typical customer. In the classic “AIDA” funnel, the “Awareness” budget at the very top of the funnel rarely gets any digital allocation.

Maybe this is 100% backwards.

Television advertising is about creating enough buzz to drive customers towards Interest, Desire, and Action. TV, radio, and print do this fairly well at scale. Media is easy to buy, has mass reach, and relatively standard creative formats, which lower the cost of broadscale market penetration. But that is changing. Traditonal media is losing people’s attention, which is becoming increasingly divided between mobile, tablet, and desktop screens. Folks are using the DVR and Netflix to avoid marketing altogether, and forget about the kids. You have to basically trick them with “native” ads or actually produce a buzzworthy YouTube video to get their attention. That’s impossible to scale.

What about digital approaches to branding? Can you actually create customers in digital, rather than just scooping them up with retargeting and other lower-funnel tactics? The answer is yes…with the right way to measure. Cookie-based measurement will always fail to give the progressive marketer the right answers. Common issues (deletion, do-not-track, multiple-device, etc.) mean we can only see 30% of online conversions from a particular campaign—never mind the offline sales digital receives 0% attribution for.

What if we used the right metrics, which could reveal the real impact digital branding has on new customer creation? One of those metrics is profit optimization: the concept of understanding what a products optimal sales should be in one geo-targeted area. In other words, understanding how many ACME widgets are selling in Huntington, New York—and how many it should be selling, based on its profit potential. If you understand those numbers, even at a basic level, you can actually start to measure digital success and uncover the “invisible” digital customers you might have. They are the people you can’t see online—because they don’t actually exist (as cookies) yet.

It’s a pretty simple equation: more and more time is spent online. But more sales occur offline. Looking at the graphic above, the concept is to try and pull the digital line backward, and engage the customers you can’t see online, leveraging digital media tactics for branding. By taking a pure digital approach in discrete markets, and measuring by nothing but profit optimization, you will be able to quickly see the hidden power of digital branding—and start creating more customers with digital, rather than marketing to those who have already expressed interest in your products.

[This guest post was authored by christopher Skinner, and appeared on Econsultancy on 11.25.13]

Every Marketer Needs to See this Napkin

Recently, I had a cup of coffee and a macaroon with a guy named Christopher Skinner. Christopher has spent the last dozen years or so running a company called MakeBuzz after selling his old company, Performics, to Doubleclick. Lately, he has been keynoting some of Google’s “Think” conferences. Google likes what his company does for them—after using his software, marketers start to spend a lot more money on branded display. In other words, instead of just loading up on keywords and obvious AdSense display inventory, marketers are leveraging data that says digital display works to build a brand’s customer base. Without getting too specific, the software offers geo-targeted media recommendations that aim to optimize profits in specific areas—helping a company go from selling 100 widgets a month in Poughkeepsie to 150.

When I asked what the secret sauce was, I was surprised at the answer. Christopher drew me something on a napkin that looked like this:

Napkin

The problem, he told me was that marketers weren’t striking the right balance between branding and direct response, and focusing too much on capturing customers they already had. In other words, if your business was like a lawn, and the profits were grass clippings, most folks were spending too much time cutting and not enough time fertilizing. To get the grass to grow, you want to fertilize it (branding) and get plenty of new blades to pop up as often as possible. When you cut it (direct response), you want to do so in a way that ensures it won’t get burnt, and lose its ability to sustain itself. It’s a delicate balance between growing demand through branding, and harvesting those efforts through direct response.

Looking at his crudely drawn chart, the line represents reach, going from a single user to the entire population. Most marketers stop 20% of the way through, and put all of their focus on their customer base through search and programmatic RTB display efforts—using data to ensure they are reaching the right “intenders,” but missing the opportunity to create new ones through branding. On the far right (dotted line), you have all the potential customers that are addressable; these users are still “targeted,” but so widely that hitting them with messaging is fraught with waste. This is the digital equivalent of advertising to “the demo” on television. Sure, it creates demand for BMWs, but only a certain portion of the audience has enough dough to afford a 5-series.

The simple message that many marketers continue to miss—either by focusing way too much on DR, or over indexing on untargeted branded efforts—is that a balance is critically important in the digital marketing mix. While it sounds simple to find the right balance, it actually requires a strong base of knowledge to execute properly. This is what I mean:

  • Measure Differently:  Before you can understand the mix you need to achieve between branding and DR, you need to agree on a meaningful metric. Far too many digital campaigns are judged by three-letter performance acronyms that are proxies for success. Great CTR and CPA are positive signs—that you are doing all the right things to reach the audience you have already earned. They are poor indicators of your success in building new customers. Thinking holistically about your marketing efforts yields new benchmarks: If your company typically sell 200 widgets in the Upper West Side of Manhattan, why shouldn’t you be able to sell the same amount in San Francisco’s Nob Hill? In other words, how about using “profit optimization” as the primary metric? This requires a relationship with the advertiser that goes beyond the agency, and plenty of first-party data, which is why such simple yet effective metrics are not used frequently.
  • Spend More on Branding: Sometimes, what holds good marketing back is a reliance on known metrics. In another year, the banner ad with be 20 years old. While the banner ad ushered in an era of “measurability,” it also took marketers on a path to thinking that anything and everything could have its own success metric, and we went from a dependence on soft, panel-based, attitudinal metrics to today’s puzzling array of digital KPIs. Did Absolut vodka worry about CTR on its way to becoming the dominant liquor brand of the last quarter century? Or did they just design great packaging and put big beautiful ads on every magazine back cover they could find? At the end of the day, TBWA made a decent vodka into a great brand, and the only metric anyone ever worried about was case sales. They did it by spending LOTS of money on branding.
  • Find the Sweet Spot: Spending more on branding is obviously important for “growing the grass,” but not every product is one everyone can afford. While it made sense for Absolut to advertise to the broader population of adults in magazine, most marketers have a more limited audience and budget. Finding the sweet spot between branding and DR has a lot to do with knowing your potential customer and how they make purchase decisions. If you believe (as I do) that word-of-mouth is the most powerful medium, then it makes sense to apply as much granular targeting to a campaign—without restricting it with too much targeting data. Neighbors talk to and influence each other—and the Smiths and Joneses tend to chat on the soccer field about cars, vacations, and even the latest medical procedures. Your sweet spot is where you can faithfully blanket ads in a neighborhood or larger area that has a built-in predilection to purchase. It’s not a broad as city targeting, which wastes messaging on customers that can’t afford your products, and not so targeted as “intender” targeting, which limits your addressable audience to people who already love your brand.

Today, it seems like digital marketers are limiting their reach to their existing customers—spending lots of lower-funnel effort dragging “intenders” across the finish line, so they can attribute lower acquisition costs to their campaigns. Although the real customer growth is grown through branding efforts, most marketers are scared to open up the spigot and deliver large amount of impressions, and especially hesitant to migrate marketing to cookie-less mobile devices and tablets which are harder to target. But to grow customers, you need to introduce them to your brand—and find them where they live. When you water the lawn religiously, there is always plenty to cut.

[This post originally appeared in AdExchanger on 10/7/2013]

Leveraging the Influence of Neighbors

Neighbors-family-guy-15674073-638-483Christopher Skinner sold a search marketing company called Performics to Google as part of its Doubleclick acquisition. He now runs a software company called MakeBuzz that is on track to spend almost $100 million in media this year. Clients include Google, Target, and Oreck.

Its premise is simple: People buy the stuff their neighbors buy. By starting wide with media that builds a brand halo and then, optimizing into specific geographic areas where buyers are found, MakeBuzz optimizes against profit only.

Most marketers are obsessed with reaching individuals, but Skinner’s concept is almost contrarian: Spend more media up front, target by neighborhood and city, and be completely media-agnostic. The MakeBuzz code guides the optimization process until profitability KPIs are met. I recently sat down with Skinner to learn more.

The CMO Site: What’s the big idea here?

Christopher Skinner: Most people online today can measure a brand, but they can’t grow it. The methods to measure are not the same as those used to grow. You need a different framework and nobody is talking about that online.

Digital media agencies today are being handed money — money from traditional budgets — and asked to perform and hit the business targets but they don’t know how because they’ve lived inside the efficiency world for so long. It relates to neo-classic economic thinking: What you can’t measure, just ignore it.

On average we increase media spend by six times or more because we install a framework and technology that justifies the complete customer journey. We tie marketing to the economics of the business.

The CMO Site: Is profit optimization real, or are you just adding some process to what should be the CMO’s primary KPI?

Skinner: Both. It’s real and it is a formalized process. The software shows you how to tip the scales in favor of revenue by spending the right amount on media directed to the right group of customers. It helps you achieve maximum profitability on a market-by-market basis.

The CMO Site: You take a rather contrarian view. Most folks are buying audience by the impression, but you carpet-bomb geo-targeted areas with impressions. Which method is right? Can they be used together?

Skinner: Hyper-audience targeting based on cookies will deliver incredibly efficient sales, but you’re not going to see massive volume from this. You’re not going to move the needle on the business. I wouldn’t call what we do “carpet-bombing.” We’re delivering a large volume of impressions to areas that have a reasonable volume and high density of the target customer. We are looking at real social circles and matching media to these audiences, down to small pockets when needed. This is going to get you a little less efficiency but a lot more sales — a lot more profit volume. And isn’t that what matters?

The CMO Site: So, if I find the right neighborhood for a certain type of vehicle, I should just buy lookalike neighborhoods. How does that scale?

Skinner: Instead of drawing circles around virtual groups online, we draw the circle around concentrated groups of people that we know are likely to be interested in what we help market. And the fact that they are influenced by each other — they see what their neighbors wear and drive and what kinds of phones they use — means they are more likely to be influenced by media that reinforces and re-suggests those choices.

Scalability is about testing your way in. Identifying high-value areas, testing media to discover your profitability, then scaling to similar areas.

The CMO Site: What kind of media works best? It would seem that the more granular the geo-target, the better the performance.

Skinner: You need media that addresses the entire customer journey, from early awareness branding media to direct response purchase phase media. Most businesses are fine with the direct response online media, but they are missing brand-creating media. Our methods do a really good job of justifying media that helps drive direct response. The earlier phase media tends be display, mobile, and video, but can also be search (SEM).

As far as geo-targeting granularity, as long as the density of our target segment is good in each area and we’re hitting them with the right media plan, it works great. Think of each step as a filter: 1) Choose the right segment, filtering out all the less valuable potential customers; 2) Choose an area they live in high in density and volume, filtering out the neighborhoods they don’t live in; and 3) Pick the media they’re likely to be engaged with, filtering out wasted impressions. You can’t pull this off without a platform and it will not work unless the manager has a fast and simple way to buy in.

[This post was originally publisher in The CMO Site, on 4/11/13]

Stealing Some Of Microsoft’s 76% Ad Tech Market Share

downloadWhen you think of advertising technology in the display space, the first names you’re likely to think of are Google, PubMatic, Adobe, and AppNexus. But Microsoft? Not really top of mind, unless you are thinking of its disastrous aQuantive acquisition in 2007. Sure, every now and then MSFT will pick up the odd Rapt or Yammer, but is it really having a huge impact in the ad tech space? Even if you’re a regular AdExchanger reader, you’d be justified in thinking it’s not.

But you’d be 100% wrong.

Microsoft has been quietly running the inner ad-technology workings of digital display since the first banner ad was purchased in 1995. According to some recent research, the company’s ad-planning software boasts an amazing 76% market share among agency media planners. MediaVisor ranks a distant second with a measly 9.7 Almost nine in 10 planners who use Excel spend more than an hour a day using its software, while almost 35% use it for more than four hours per day[CO1] . [l2]

That software is called Microsoft Excel.

Released in 1985 (originally for Macintosh), Excel is nearly three decades old and has been powering digital-media planning since its inception. Combined with Outlook, Word, and PowerPoint in the Office suite of products, Microsoft tools have been central to the digital-media planning process for a long time. Planners plan in Excel, publishers pitch in Excel and PowerPoint, contracts are made in Word, and everything is communicated via Outlook. And then there are the billing and reconciliation tasks that occur inside spreadsheets. Nobody ever seems to wonder why more than $6 billion in digital display media transactions (representing nearly 70% of all ads sold) use Microsoft tools and the occasional fax machine.

While innovative companies have challenged the dominance of these systems in the past, early efforts fizzled. The complexities of modern digital-media planning, combined with the reluctance of agency planners to change their behavior, have hindered innovation. Looking at past and current “systems of record” for media buying, it’s no wonder planners are scared of change. If you have ever seen legacy agency operating systems, you wonder if a single dollar was ever spent on user experience or user interface design.

Why Programmatic-Direct Planners Use Excel

As an ad technology “evangelist” of sorts, it is my job to show agencies the future of digital-media planning. This is starting to be called programmatic buying, a term which encompasses both “programmatic direct” buying, which targets the transactional RFP business that accounts for the bulk – 70% – of digital display ads, and “programmatic RTB,” which accounts for the impression-by-impression purchases that represent another $2.4 billion, or 25[CO3] % of the pie.

Companies like MediaMath and AppNexus have made the latter category wildly efficient. Buyers don’t use Excel to create an audience-buying campaign across exchange inventory. Instead, they log into a web-based RTB platform.

For automating guaranteed display buys, though, Excel has become the default for media planners, even though if it doesn’t have the features of many web-based systems available. For example, Excel doesn’t track your changes. When planners change something, multiple files are created, and it’s easy for two people to work on a plan at the same time, duplicating work and botching it up. Excel isn’t Sarbanes-Oxley compliant, either. Agencies end up with thousands of Excel sheets on hard drives and servers, and a complicated file versioning and access system that makes replicating and tracking plans really difficult. Excel doesn’t integrate easily with other systems. At the file level, Excel is great. You can import and export Excel files into almost anything. But Excel can’t send out an RFP, or accept an order. Excel can’t automatically set an ad placement inside an ad server like DFA or MediaMind, or get Comscore updates. Excel is amazingly flexible, but it wasn’t built for media planning.

Today, the average digital-media plan costs nearly $40,000 to produce and takes as many as 42 steps to complete. That’s why, according to a recent Digiday survey, more than two thirds of agency employees will leave their jobs within the next two years. Digital-media planning should be fun and innovative, and young, smart people should want to be spending their time influencing how major brands leverage new technologies and media outlets to sell their products.

The reality is that young media planners are finding their days are filled with reconciling monthly invoices and ad delivery numbers. Have you noticed media planners’ eyes glazing over during your latest “lunch and learn?” That’s today’s young agency employees’ way of calling bullshit on ad tech. Our technology has been making their lives harder and their hours longer, rather than ushering in a new era of efficiency and performance.

How We Can Finally Beat Excel

I believe that dynamic is rapidly changing now. Buy-side technologies from innovative software companies, combined with offerings from sell-side players that are plugging into publisher ad servers are creating a programmatic future by building web-based, easy to use, and extensible platforms.Here are a few reasons these types of systems will start to get adoption:

  • Pushback on agency pricing models: Big agencies have been getting paid by the hour for years, but their clients are starting to push back on cost-plus pricing schemes. After exposure to self-service platforms and programmatic buying, they are getting used to seeing a larger percentage of their money applied to the media, and that trend is only likely to continue. Brand advertisers are demanding more efficiency in direct-to-publisher buys, and that means agencies must start to embrace programmatic direct technologies.
  • User interfaces and user experiences are improving: Young people plan media. They are used to really cool web-based technologies, such as Snapchat and Twitter. Today’s platforms not only centralize workflow and data, but increasingly come with something even more critical to gaining user adoption: a nice interface. When we start building tools that people want to use and a user experience that maps to the tasks being performed online, adoption will quickly increase.
  • Prevalence of APIs: Today’s platforms are being built in an open, extensible way that enables linkage with other systems. Since there are so many phases in modern digital media planning (research, planning, buying, ad serving, reporting, billing) it makes sense for platforms to be able to talk to one another. While some legacy APIs are not the best, they are getting better. Servers-to-server integrations make a lot more sense than 23-year-old planners updating spreadsheets. As David Kenny, CEO of The Weather Company, once remarked, “If you are using people to do the work of machines, you are already irrelevant .”

Because of these factors, I expect 2013 will be the year that programmatic direct buying changes from a fun concept for a planners’ “lunch and learn” to a reality. It’s time for us to finally get cracking on stealing some of Microsoft’s ad technology market share.

[This post was originally pushed in AdExchanger on 4-23-13]

Getting in the Conversation with Social TV

t1larg.tv.ipad.fastI was recently at a conference, and took a picture of a PowerPoint slide that I thought was pretty interesting. It showed the growth of tweets about television from Q2 2011 to last quarter. Basically, nobody was tweeting anything a few years ago, and then there were over 18 million unique people tweeting about TV in Q4 2012, representing a 182% year-over-year growth rate. If you are a modern marketer that spends money on television advertising, there are some implications in this data worth looking at.

Are you in the conversation?

Back in the 1980s, I would sometimes go to Times Square to see horror movies. The theatres were uniformly crumby, but the people were the best. Times Square movie theatres always featured an audience willing to give Jamie Curtis’ Halloween character plenty of advice in each scene. In fact, between the chatter and screaming, you could hardly hear the film. That was what passed for “social viewing” in the old days. Today, we are discovering that people still like to share viewing experiences together, and Twitter and other social tools lets you make every television show an Oscar party you can attend in your pajamas. Brand advertisers backing a particular show want the glow of good comedy or drama, and now extending that association may mean inserting yourself into the conversation via a Sponsored Tweet. What’s really interesting about that is your message can be received during the action, without interrupting.

Less TV, More Tweet

The rise of “Social TV” gives brand marketers yet another dimension to ponder as well. With a show’s active and engaged community just a Tweet away, how much media should you allocate to thirty second spots, and how much should go towards the social element? Moreover, social TV means that every consumer seeing your ad can get the chance to interact and talk back socially. We are seeing marketers hashtag their ads and drop into the social stream of conversation. Although this is still a form of “interruption marketing,” it’s the closest that brands have gotten to being a part of, rather than disturbing, the entertainment in a long time. These digital “native advertising” opportunities are proving effective, and starting to take market share away from commoditized 300×250 display advertising units.

Can your company dunk in the dark?

The latest test for marketers is The Oreo Challenge or, more simply put, do I have a social strategy for taking advantage of news and events? Although it seemed like a no-brainer during the Superbowl, “you can still dunk in the dark” was the result of a contemplated strategy. Oreo’s very responsive tweet is a phenomenon that digital marketers are still talking about—the kind of lightning on a bottle that produces tens of millions of dollars  in “earned” media. But getting there requires your marketing team and agency to truly understand everything about the brand they are promoting. If your team can’t automatically speak in the brand’s “voice” and doesn’t truly understand the brand attributes and values, you can’t automatically respond to opportunity in the social space. Teams that live and breathe their brand—and, more importantly, their brand’s key constituency—must be trusted to speak socially…and sometimes loudly, if the occasion warrants it. Of course, there is a good chance your joke will go flat, but that’s okay when you are among your television “friends.”

[This post was originally published on 4/3/13 on The CMO Site]