by Andrew Frank | June 13, 2013 | 1 Comment
In 1849, the year of the gold rush, the city of San Francisco had about 1,000 inhabitants. By the end of 1850, its population had grown to 25,000. To accommodate the massive influx of prospectors, self-contained gold mining towns sprouted up around the region. As the surface gold vanished, deep mining became industrialized and capital-intensive. Rivalries grew and power centers developed. The winners were best equipped, best organized, and knew the territory.
Today, digital marketing seems to be reaching a similar turning point. The days of a thousand point-solution venture-backed vendors are giving way to a period of complex consolidations, in which providers from different regions of marketing are converging on a common terrain of integrated, multichannel, data-driven, cloud-based digital marketing solutions – tied together by a central digital marketing hub. But they are challenged by a diversity of divisional buying centers within organizations struggling to connect the many marketing silos they’ve built while preserving a common sense of brand.
My colleague Bill Gassman and I wrote in a recent report (subscription required):
“There are many worlds of marketing: from online to offline, from inbound to outbound, and from agency to indigenous. Each faction has a role to play in the overall marketing efforts of an organization, but often each works in an isolated world of business goals, functions, metrics, tools and cultures. Even the lingo is different, to the point that discussions are difficult when different constituencies try to communicate or compare performance metrics. This is particularly true of the divide between advertising and marketing operations.”
The ad tech world, which has enjoyed a long run of investment inspired by the lucre of media and the success of Google and Facebook, would now recast itself as marketing tech and apply its programmatic solutions for advertising to a broader range of communications and decision support. Consider this speech, given at AdExchanger’s Programmatic I/O conference in April by John Nardone, CEO of [X+1], titled “The Programmatic CMO,” in which he presents the case for why DMP-like tools will move beyond advertising to marketing.
On the other side of town, in the web ops region tag management has taken root as the natural heir to web analytics, and companies such as Tealium have announced their own Tealium Data Cloud and Tealium Digital Marketing Hub products. In the data ops world, cloud-based providers like Anametrix are challenging big data incumbents with solutions positioned as universal marketing data hubs. And from marketing ops, lead management providers such as Marketo and Neolane have also staked rich claims, launched marketing hubs, and found new homes with buyers such as IBM and Teradata. Finally, social marketing and email marketing players are the latest groups to find favor with large software incumbents like Oracle and Salesforce.com who see gold in the application of their big data to marketing.
All of which begs the question, how do the natives – that is, digital marketers – cope with this influx of gilded fortune-seekers? They need a guide – someone who knows the changing territory. And perhaps some sort of map.
Category: Advertising Cloud Data-Driven Marketing Disruption Media Strategic Planning Uncategorized Tags: Advertising, Data-Driven Marketing, digital marketing
by Andrew Frank | May 28, 2013 | 3 Comments
Each year around this time the analysts at Gartner go to work on a series of widely read reports called Hype Cycles that summarize the maturity and velocity of a staggering number of technologies. Spoiler alert: this year, we will introduce a new profile called “data-driven marketing” with a “transformational” benefit rating.
Which is not to say that current expectations don’t suffer from inflated hype, some of which was on parade at last week’s OMMA data-driven marketing event at Internet Week in NYC (see MediaPost’s Big Data Swagga coverage). But it’s not so much the hype we’re interested in as the reality, which is that there are large variations in adoption of data-driven marketing techniques among marketers. Last month Gartner released a survey (highlights available) that showed marketers, on average, allocate 21% of their marketing budgets to marketing analytics. But averages can be deceiving: only about a quarter of the panel reported spending near the average; at the extremes we find 21% spend less than 10% while 15% spend over 40%. That’s a wide range. Similarly, when we asked what percent of the marketing analytics budget was allocated to digital marketing analytics, 24% said less than 10% while 17% said over 40%.
A recent survey from IBM compared the activities of top performing marketers with others, offering some evidence that greater involvement with data-oriented activities was correlated with marketing success. The activities that showed the greatest gaps in involvement between top performers and others happened to be extremely data-driven: “uses optimization technology across all channels” topped the list as top performers were 5.6x more likely to do this than the norm. The next three were “adjusts real-time offers based on context” (2.6x), “applies advanced analytics to determine media spend” (2.2x), and “detects transaction struggles and takes action” (2.2x). Lest you think the activities were all data-centric, least differentiated were “integrates inbound/outbound and online/offline” and “identifies/remedies execution gaps in brand promise” (that may still use data, but presumably not big data).
We’ll be sharing more findings about the true state of data-driven marketing in a webinar on May 30 titled “How Data is Transforming Marketing.”
Category: Data-Driven Marketing Tags: Data-Driven Marketing, digital marketing, Market modeling, Marketing
by Andrew Frank | May 7, 2013 | Comments Off
Last week’s Customer 360 conference in San Diego provided a good opportunity to sample what’s on the minds of marketers, and one question I heard a few times was, do you anticipate companies (like ours) shifting their ad budgets to big data initiatives in marketing? In fact, there is plenty of evidence of a long-term value shift from media to data, and earned media is emerging as a disrupter of paid media (see, for instance, VivaKi’s launch of Contagion with Visible Measures). Yet, a number of savvy marketers I spoke with also expressed skepticism that marketing was about to raid the media budget in a big way.
A good deal of ink has been devoted to writing advertising’s obituary of late. One such book project (currently in Kickstarter) comes from Joseph Jaffe and Maarten Albarda and is titled “Z.E.R.O. Zero paid media as the new marketing model” (see MediaPost coverage here). Jaffe’s earlier book, Life after the 30-second spot, took aim in 2005 at TV advertising, which has since stubbornly refused to die, although its future can still launch a healthy debate. But setting the goal post at zero for all paid media is a much more radical proposal. Even Jaffe seems to hedge a bit:
“Z.E.R.O. is proof positive that you don’t need to ‘pay’ for customers or media if you have enough to start off with and/or a core of passionate advocates who would go to bat for you.”
For most companies today that’s a pretty big if. Gartner’s recent marketing spending survey shows that, looking only at digital marketing budgets (which average about 25% of overall marketing budgets), digital advertising still claims the biggest share of spending at 12.5% (followed by content creation and management at 11.6%). (Results are based on a survey of 253 marketers from U.S.-based companies with more than $500 million in annual revenue.)
But predictions are about the future, and at Gartner we’ve often wondered about the future of paid media. Last year, I wrote in our Hype Cycle for Advertising about, “the ‘dark cloud on the horizon’ for ad-supported media as marketers beginning to openly question whether alternatives to paid advertising — earned media and advocacy in social networks, direct data-driven targeting, one-to-one conversational tactics, and branded content and applications, to name a few — might soon lead to substantial secular cuts in media spending across the board.”
Yes, there are plenty of reasons to imagine that paid media faces a rocky future, so lest we all assume its demise is a foregone conclusion, I’d like to offer five counterarguments that suggest otherwise.
- Scarcity of attention. Although always-on access to a glut of media options (including social) is fragmenting audiences and driving down digital ad prices, reaching the right person at the right time in the right context is still both difficult and essential to marketers, which is all that’s really needed to create demand. Media is about the cultivation of attention so, although its form will change, its basic model of aggregating and selling eyeballs will not. New competition from companies like Google and Facebook will raise the bar on just how attention is cultivated, and refined with data (to select the right eyeballs), but these companies depend on advertising for revenue, so they’re in the media business. Just ask Sir Martin Sorrell.
- Scale and Risk. Earned media enthusiasts like to point out how viral content can exceed the reach of paid media across all channels, while generating much more buzz and engagement. This is certainly true, but it fails to account for the fact that virality is rare and highly unpredictable. The industry’s tendency to focus on exceptional success stories can skew perception on this point, but most mature marketing organizations recognize this and still prefer to pay for predictable results rather than gamble against long odds with pure viral content.
- Lack of Perfect Information. An oft-repeated fallacy is that “today’s consumer exists in a world of perfect information.” (Jaffe) There’s no doubt that consumers have access to a lot more information than they used to, but perfect? Gartner estimates that 2-6% of existing ratings are fake or deceptive (subscription content), and an entire industry has sprung up around gaming ratings and recommendations. Most consumers understand that information in social networks is not necessarily dependable, and that advertising, while not the most trustworthy source of information, at least has some public accountability for truthfulness.
- The Ad Tech Revolution. Paid media is hardly standing still. A great deal of monetary and intellectual investment is going into measuring and optimizing the effectiveness and efficiency of advertising, and making it real-time. A comparable market for earned and paid media doesn’t exist. This observation is sometimes used to support the straw man argument that it’s not media but “old media” that’s doomed. And this is surely true, so media companies better figure out ways to be new. It won’t be by tossing out the idea of selling ads.
- Even the revolutionaries wind up buying TV. Not only are Google and Facebook dependent on paid media for revenue, but both of them, along with Apple and Microsoft, have seen fit to heavy-up on old-fashioned TV (see Facebook’s first TV commercial for Home at AdAge). These are companies with more data and high-tech analytic skills than anyone else. ‘Nuff said.
So, yes, media is in for a bumpy ride as big data pushes its way into the marketing picture, but marketers will need to think twice before they raid the ad coffers. And media companies need to find their role in the data picture, which is a plug for upcoming research.
What do you think?
Category: Advertising Data-Driven Marketing Disruption Media Tags: Advertising, Data-Driven Marketing, digital marketing
by Andrew Frank | April 16, 2013 | 2 Comments
As revolutions go, the Big Data Revolution is a tough one to get really passionate about. Revolutions work best when they rally around simple, inspiring principles: freedom, equality, really handy devices…. But Big Data, which Gartner defines as ”high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making,” is often about a dry new way to predict human behavior, and, in the marketing department, influence it based on those predictions. As David Brooks writes in the New York Times, “the theory of big data is to have no theory, at least about human nature.” In other words, suppress all your instincts and explanations about what makes people tick and search for patterns in the data ocean instead. The wonky distinctions involved in this discipline – among things like correlation and causality and inference, for instance – remind us that it takes a certain kind of personality to get fired up about this – one that doesn’t get fired up too easily.
And yet, marketers are getting fired up about it – at least fired up enough to devote an average of 21% of their marketing budgets to marketing analytics. That’s one of the findings of a recent survey Gartner conducted of marketing analytics professionals (promotional excerpt available here). But does their commitment really match the hype? When we asked about sources of data, we found that over half (58%) of the data they used in their analytics still comes from internal sources. On the surface this is not surprising – after all, internal data is more available, less costly, more reliable, and arguably more relevant than data from external sources…but Big Data sees things differently.
Companies can surely generate lots of data from internal systems – so you might call it “big” – but the trouble with this from the perspective of Big Data is that this data is, in the doctrinaire parlance of analytics, a biased sample. It’s data about your customers and how they interact with you – it’s not data about the world – so strictly speaking the scope of its predictive capabilities is comparatively limited. This biased view is further reinforced by our finding that customer analytics top the list of activities considered most essential by marketing analysts.
This is not to say that these analysts are off track, or that all their data is not valuable or useful. It just means that adoption of that true Big Data perspective in marketing analytics – which would tend to favor the broadest data sets available – appears to still be a ways off. And so is the thinking that goes along with it. Most marketing leaders, while extolling the virtues of data in general, are simply not prepared to relinquish the instincts that got them as far as they’ve come in their careers, or grant extensive decision-making power to processes they find opaque. They will remind you that data is only useful when you know how to ask the right questions, and the data can’t tell you what to ask it.
Still, there are a few marketing pioneers who are taking the Big Data philosophy very seriously. We’ll be examining some of these in upcoming research. They’re putting the Big Data theory of no-theory to the test, and if it works, the results will start to speak for themselves. And that should get folks fired up.
Category: Data-Driven Marketing Disruption Uncategorized Tags: Data-Driven Marketing, digital marketing, Market modeling, Marketing
by Andrew Frank | April 4, 2013 | Comments Off
“We were reprimanded by management for casual tone and conversational voice,” reports one respondent to Gartner’s latest social marketing survey (free excerpt available here).
“We locked down employee participation because it didn’t reflect our brand values,” reports another.
Internal conflicts like this used to be minor matters, but the inexorable rise of social marketing is escalating them into real threats that demand c-level attention. Gartner’s 2013 U.S. Digital Marketing Spending Survey (also publically available) found that investments in content creation and social marketing claimed 21% of digital marketing budgets, which have swelled to 2.5% of company revenue…and will increase 9% in 2013. Yet even at these levels, social marketing appears underfunded compared with the impact it can have on brand perception and, ultimately, sales, as consumers flock to social networks to share opinions on everything.
Gartner’s social marketing survey reveals that one of the biggest – and most underappreciated – challenges of social marketing is achieving consistent, authentic brand communication at scale. 47% of our survey respondents see content creation and curation as the most important role of their social marketing teams (more than any other category), yet they struggle to come up with a consistant stream of relevant and compelling “on-brand” messages. So they look to agencies for help. Content and social engagement tops the list of ways that marketing service providers are helping clients with social marketing. But, if authenticity is the key to building trust and loyalty in social networks, you have to ask yourself if paying outsiders to do it for you is always the best approach. On the other hand, social media is giddy with examples of what happens when authentic employee tweets go unbridled.
The bottom line: social marketing is putting new demands on organizations that go beyond the kinds of problems you can solve by shifting budgets and issuing restrictive guidelines. It’s forcing organizations to confront basic, sometimes uncomfortable questions about what they stand for and how they communicate, and to internalize and socialize a consistent tone and message among employees, partners, and the public. Agencies can help both bring this into focus and scale it up once it’s established, but values have to come from within – and, frankly, not all organizations have them.
Read about these findings from our latest social marketing survey and let us know if it rings authentic to you.
We’ll share more findings in our Social Marketing webinar on April 25th – What’s Next for Social Marketing and Social Marketers?
Category: Data-Driven Marketing Media Uncategorized Tags: Data-Driven Marketing, digital marketing, Social Media
by Andrew Frank | March 4, 2013 | 2 Comments
Reviewing email on my iPad, I get a message from LinkedIn reminding me that I have important invitations waiting. I’ve been remiss! Fortunately, LinkedIn totally gets convenience: there’s an “Accept” button right here in the email, which I tap thankfully. Being a web link, it takes me to a LinkedIn URL in Safari which, detecting I’m on a tablet, informs me that “Opportunity is tapping” so I should get the LinkedIn app for iPad. Frown. I already have the LinkedIn app for iPad, but there are no choices on this page other than “Get the app.” So I tap and I’m transported to the app store, where I learn the LinkedIn app has a mere three stars and I’m due for an update. Again I have only one choice, so update it is. Next comes the challenge for my Apple ID password, which fortunately I’ve committed to memory – such is Apple’s rarified role – and, after a brief 30 second delay while the update downloads and installs, I’m finally invited to open the app.
But here comes another challenge: I need to log in to LinkedIn to use the app. That’s a problem. Although I’m extremely fond of LinkedIn, I have not committed my LinkedIn password to memory since my PC browser knows it, and I’m the kind of paranoid who actually keeps separate random time-based passwords for all of my websites, generated automatically by a program I use for this purpose. So I leave the LinkedIn app and load my password app, find and copy the password, go back and paste it into the app, but, alas, the password is not recognized.
Now I’m down the rabbit hole: there’s no way to reset the password from the app on my tablet. Determined to prevail, I put down the tablet and head for my laptop, where I open my browser and go through a simple five-step process to reset my password (“resetting your password is easy!” reminds LinkedIn helpfully) and, returning to the tablet, at last I’m in. Success! What was I trying to do again?
I don’t mean to single out LinkedIn here. This sort of pattern is repeated across so many sites. As the debate pitting mobile apps against websites continues to rage, it often seems to me that the attraction of superior app-based user experience hides the usability costs of going native: the loss of simple web linking (with parameters to establish context); browser-based security and authentication; ease of distribution and updates; universal standards-based implementation; search-based discovery…these are not virtues to be taken for granted.
This is not to say mobile apps don’t have an important role to play, but the essence of customer-centric design is to understand the entire customer experience, from impulse to fulfillment. Consider that as you plot your native app strategy.
Category: Applications Media Tags: Add new tag, digital marketing, eCommerce, LinkedIn, Marketing, User Experience
by Andrew Frank | February 28, 2013 | Comments Off
If there was any doubt that social media and big data are joining forces to revolutionize marketing, this announcement from Facebook should put it to rest:
“Today, we’re expanding custom audiences to allow businesses to use Datalogix, Epsilon, Acxiom, and BlueKai to further enhance the ads they run on Facebook.”
In other words, marketers will now be able to use the same third-party big data sources they’ve used elsewhere to create and target Facebook campaigns. To protect privacy, the four big data partners will use the hash-encrypted anonymous matching process that Custom Audiences already employs to protect personal information exchanged among Facebook, marketers and third parties. Details and debate are available elsewhere, but marketers already have the capability to upload customer databases in order to target existing customers on Facebook using such privacy protection technology.
This news has broader implications than just improving the efficiency and effectiveness of Facebook ads. It shows how far we’ve come in the consolidation of data from all available sources – both online and offline – to drive marketing processes. If you use a loyalty card, then you may soon be reading sponsored stories based on your shopping habits. Whether you find this creepy or cool, it’s the new reality of data-driven marketing, and social media, once considered off limits, is now becoming the main stage for these data-driven experiences.
The larger issue for digital marketers is how to wield this newfound power. If you play solely by the numbers, you’re likely to find that, broadly speaking, targeting works: if you can constrain your cereal ads to cereal buyers, you’ll save money and boost ROI. But there are risks. Your models are not likely to be able to predict when too-personal copy will elicit a negative reaction (yet), nor will they forecast when you might be likely to face criticism for lack of transparency in your data collection practices, or lack of authenticity in your pitch. These are judgment calls. But one thing is certain: where restraint was once imposed by law and the difficulty of connecting the dots between disparate data sources, it will now need to come from the instincts and principles of marketers themselves, who will need to hone them with first-hand experience.
Category: Advertising Data-Driven Marketing Media Tags: Advertising, Data-Driven Marketing, digital marketing, Facebook, Privacy, Social Media
by Andrew Frank | February 22, 2013 | Comments Off
Last fall, my colleague Stephanie Baghdassarian and I found ourselves in an interesting situation. We were working on our annual mobile advertising forecast (subscription required), and the data was telling us that mobile advertising revenue worldwide was growing almost 60% faster than we had predicted the previous year – a difference that amounted to almost $3 billion in 2012 – and it looked like 2012’s North American revenue would come in 90% higher than we thought. This was ironic for two reasons: first, our 2011 prediction was widely received as aggressive, and second, we also knew mobile display ad rates were only 20% of online and most of the mobile publishers and developers I spoke with didn’t seem to be experiencing an ad revenue bonanza. Even more curious, our surveys showed little indication that advertisers were shifting significant media ad funds to mobile from other media. If demand was this weak, how could growth be so strong?
After further analysis, we developed a theory that this discrepancy was largely due to:
“…a situation in which a significant portion of mobile ad inventory is taken up by app developers paying for ads to promote their apps and get them more downloads, a category known as “paid discovery.” While the revenue basis of paid-for app store downloads provides some economic justification for this category, for many developers the outlay for ads is close to their maximum ad income or even exceeds it.”
Based on this, we forecast that in-app display advertising growth would nearly stall in 2013 as the app paid download economy ad bubble deflated.
Enter Millennial Media, by many measures the leading independent mobile ad and data platform, which, in its latest earnings call, attributed revenue below guidance to its decision not to participate in what it called “lower end performance segments” – and, elsewhere “lower value incentivized downloads.” We have confidence in our forecasts; still it’s relatively uncommon in my experience to get a signal this clear so close to a non-linear prediction.
But what does this mean to mobile marketers and developers? First of all, the good news for publishers is that mobile ad prices and fill rates are both rising, a sure sign that brands are starting to take the medium more seriously. For marketers, the good news is that mobile ads still look like a bargain compared with other media, and the availability of desirable features like location-based targeting and real-time bidding is on the rise. One source tells me that supply of location-targeted ads is growing at 36% month over month, while real-time inventory is growing about 83% per month. The combination of these two capabilities gives marketers a great deal of flexibility in structuring agile targeted campaigns that really do get the right message to the right individual at the right time.
We’re still in the early stages of the mobile marketing revolution, but it looks like 2013 is shaping up to be the year that quality apps and premium advertising start to displace a lot of incentivized pitches for more app store downloads.
Category: Advertising Data-Driven Marketing Media Mobile Uncategorized Tags: Advertising, Data-Driven Marketing, digital marketing, Marketing, Media
by Andrew Frank | February 7, 2013 | 1 Comment
Google’s announcement that its new “enhanced campaigns” upgrade to AdWords will soon eliminate (or at least limit) the capability of its customers to specify explicitly whether they want to include mobile devices or desktops only in their campaigns is generating a predictable range of responses, from anger over loss of control to praise over simplification and improved access to mobile opportunities. Adobe argues that Google’s changes may result in lower ROI for advertisers as Google seeks to raise its revenue per search on mobile devices.
There are valid points on both sides, but the simplification argument bears repeating: the complexity of having to manage unique campaigns for every device-location combination is clearly an impediment for digital marketers, and Google is removing much of this burden with smarter context-based automated adjustments.
A central detail here is Google’s treatment of tablets. “Enhanced campaigns” (scheduled to roll out in mid-2013) will no longer distinguish between tablet and desktop/notebook searches. From an ad format viewpoint, this is rather natural since tablets tend not to require resizing of ads, and Google points out that tablet computing is replacing desktop and notebook computer usage in the home, and that they both have a pretty similar mix of search terms and ad performance. But there’s more to it than that. First, many advertisers have formed an impression that targeting tablets is better for their brands. More on this in a moment. But, second, the thorny issue of whether to count tablets as mobile devices for media measurement purposes just got thornier. If, as a result of Google’s accounting, the universe of mobile devices shrinks from smartphones and tablets to just smartphones while tablets join the PC side of the ledger, the tremendous growth rate of mobile advertising might appear to have stalled. This could have major implications for investors and innovators, but don’t be fooled: mobile adoption is still way ahead of marketers, and we can thank Google for encouraging us to think beyond devices to contexts and multichannel relationships.
But back to that tablet branding thing. The great success of PPC advertising has been its appeal to direct marketers, who are squarely focused on the hard economics of ROI. In that world, it doesn’t really matter if click rates are lower on smartphones or higher on tablets; since they only pay for clicks the only things that matter are click-to-conversion ratios and revenue-per-conversion. Knowing these, the value of a click is clear and the device it comes from is hardly relevant. Brand marketers still tend to disdain this engineering approach to marketing and feel that context and experience matter a lot, even if they’re harder to measure. This is one reason they’ve been wary of smartphones for advertising – the units are so small, the contexts so brief and lean-forward. This was part of the promise of the tablet: a hi res, lean-back experience made for brand discovery and impact. So will Google be able to sell an undifferentiated AdWords channel to brands? …or will Google’s Invite Media solution remain a better answer for them? It’s nice to have choices.
Category: Advertising Data-Driven Marketing Disruption Media Tags: Data-Driven Marketing, digital marketing, Google
by Andrew Frank | January 23, 2013 | 1 Comment
Here’s a riddle.
A marketer is using an attribution modeling tool to analyze how her digital display, search, and social campaigns are working. The tool looks at all the conversions on her web site and, for each conversion, determines which touch points were present in the customer’s path to conversion. It then uses this data to determine each touch point’s independent lift in conversion rates (a technique you may recognize as “algorithmic attribution.”) As you might expect, some touch points had zero effect on conversion rates – it made no difference whether a customer saw the ad or didn’t. A few were moderately effective, adding a point or two, but one in particular stood out: when this ad was seen by users, on-site conversion rates almost doubled from 6% to 10% (this is based on a true story). So, the marketer is happy: she knows where to cut her media spending, where to hold, and where to double-down.
Here’s where it gets tricky. She also uses an ad verification service (possibly from the same vendor) to ensure that all of the ads she buys are visible on the pages where they’re placed. (You might recall that the problem of marketers paying for ads that users never see because they’re below the fold or failed to load reached a fever pitch last fall.) To her great surprise it turns out that most of those ads with the highest conversion rates were identified by the ad verification service as never having actually been seen by users! How is this possible?
Was one of the systems simply mistaken? Were the higher conversion rates some kind of strange coincidence – or some sort of fraud? An anomaly with cookies perhaps? If you’ve guessed the answer then congratulations: you’re a bona fide student of marketing data science.
To understand how this is possible we need to consider two things. First, the algorithmic attribution model as described doesn’t actually measure causality (although it seems like it should) – it just measures a correlation between events. Second, the touch point it’s looking at isn’t actually an ad exposure – it’s an exposure to the page that ad is on which causes the ad server to be called and the user’s cookie to be credited with a view (whether they saw it or not). So, what the attribution model is actually telling us isn’t that the ad had any effect – it couldn’t have – what it’s telling us is that people who bought our product are likely to have visited a certain web page in the days leading up to the purchase – perhaps because it was relevant to our product category and had good search traffic among people who were in market doing research and likely to buy.
But wait – there’s more.
Duly enlightened, our marketer kills the ad buy on the page where the ad was invisible and, lo and behold, her conversion rates drop! How can this be?
It turns out that page was such a good predictor of intent that her intelligent bidding system had learned to use it to bid on ads on other sites those visitors were found on. When she killed the ad buy, she also cut off an important source of predictive data that was responsible for improving the effectiveness of those other ad buys.
So, are we led to the absurd conclusion that marketers should happily pay for ads that people never see? No. First off, attribution modeling generally works better than this example suggests. Second, the real conclusion is this: sometimes, data is more valuable than media. So, perhaps an ideal sponsorship arrangement between an advertiser and a publisher might consist of nothing more than placing an invisible pixel (a.k.a. beacon) on relevant pages – reducing clutter while increasing inventory! (Yes, privacy needs to be addressed, I hear you.) This is what data brokers do – but their data is available to everybody in the market so it’s harder to use it to gain a competitive advantage – and, they take a cut. Maybe it’s time to consider some private exclusive data arrangements….
The moral of the story: don’t just measure the media, analyze the data too! …and you might need to hire a data scientist.
Category: Advertising Data-Driven Marketing Tags: Data-Driven Marketing, digital marketing