I had several meetings recently with friends from "traditional and emerging digital agencies." Where digital ad models have evolved from banner to engagement ads, and targeting has becoming increasingly sophisticated, and where paid search and SEO are getting less and less buzz, there is a fundamental shift happening that can turn the advertising space on its head. The reality is that this new course of big data, gleaned from a wealth of unstructured information on the web and its users is enough to make media people and publishing platforms rethink algorithms for maximizing performance.
Coming from the ad world, I have seen the banner ad rise and fall in a span of seven years. The value of search marketing (PPC) has had its heyday... or has it? I've seen content ad platforms emerge screaming the need to create "value" to get user attention only to be met by a "meh" response from advertisers. Real time bidding is the new buzzword for display advertising, where advertisers can now vie for a web user's attention, then overlay that with a complexity of user propensities. The latter is by no means dead nor dying. It's still a thriving business.
But where SEO and Pay-Per-Click (PPC) has ruled for the last five years, some of the search pundits are realizing an eventual downturn. Consider this quote from Adam Torkildson, one of the top SEO Consultants in the country who was quoted in this Forbes article, "The Death Of SEO: The Rise of Social, PR, And Real Content" who said,
"Google is in the process of making the SEO industry obsolete, SEO will be dead in two years."
A large part of this statement lies in the the fact that expectations of consumers have changed. In advertising. In content. In brand engagement. Social content is what largely makes up Google's search algorithm: relevance, recency. What does this entail? Shares, comments and reviews.
I would argue that another factor will unseat Paid Search as providing a more relevant prospect framework: social data insights.
The Traditional Ad Model: User profiles
Think back. Acquisition targeting parameters were dictated by marketers. Marketers did the consumer research, mainly expensive focus group testing with questions that largely served to benefit the "business," structured and moderated by the "business" and highly subject to group-think. To top it off, this "focus" group would provide the basis of "representation" of the target customer, so the results of the research were leveraged to inform the targeting strategy. So... my point: the research conducted was subject to false assumptions, questionable methodology and a strong reliance on the outcomes.
Now, these outcomes provided the demographic profile of the target customer, which was fed into the media buy. User profiles dictated where, when and the type of offer or content was served. At that time there were mediocre optimization opportunities.
The More Sophisticated Ad Model: Behavioural targeting
I was fortunate enough to work for Hunter Madsen, the Yahoo! guru who led the team that developed Behavioural Targeting for the company back in early-to-mid 2005. We were in awe as Hunter explained the mechanics of targeting users within the network, based on where they'd been, what content they consumed, what they searched for... also taking into consideration their geography, demographics and alignment with the target profile.
Aileen Hernandez Halpenny, a friend who heads up Rocket Fuel in Canada, reminded me of the "smart ads" -- the dynamic ad units that would be served up to you based on geography, profile, search propensity etc. These were seemingly intuitive ads that knew the right offer for you at the right time. Simply put, "Optimize each ad for each user -- right down to hyper-targeted local offers -- so that you can drive your objectives, from awareness to conversion."
Now, combine that with ad retargeting that cookies a user and serves up a similar ad when they show up elsewhere in the network. Now we're talking relevance! No longer do we have to rely on latent conversion and assume that an ad I saw 10 days ago contributed to my online purchase of that same product. Retargeting takes out that guesswork.
The Future Ad Model: Enter Social Data
Now imagine if you had the best of both worlds: behavioural data AND conversation data. Case in point: So Mary Johnson searches for information about a future trip to Taipei in Thailand. She also goes to travel sites, reads hotel reviews and has excitedly spoken to close friends on Twitter and Facebook about her plans and preparations. Don't forget, Google also scans Mary's email and captures the threaded discussion with her husband about the upcoming trip. Now we not only have recent behavioural activity where she's been on the Internet, what she's communicated via email, but we also are aware of her conversations that validate her behaviour. It is safe to assume that Mary will "definitely" be going to Taipei. Imagine what this information does for a travel company? They now have MORE information on that user that will allow them to not only serve an ad, or respond to that user with relevant offers, but DO so with a certain degree of confidence that Mary, will, at the very least click on the ad.
What excites me about social data is that it does the job of the marketer, for the marketer. No longer do we have to guess about "who" is right for our product. The conversation data alone is enough to verify the right target audience. But, coupled with recent/past web behaviour, the two variables will increase response lift significantly.
Caution: this may be a game changer but the way the advertiser needs to treat the user must also change. Ads alone may not be enough to increase response rates. Engagement -- I mean outreach to Mary through Twitter where she mentioned the activity -- may seal the deal.
Ads, for the most part, have become irrelevant. Even Facebook is realizing that low click-throughs (CTRs) on sponsored stories is not enough to drive conversion. They are now relying on "impression-based" ads i.e. "I saw the ad" vs. "I clicked on the ad" to determine whether this can be attribution factor with conversion.
How do traditional media people feel about this? An ad ops person put it this way: "Conversation data may yield us potentially top 20 people who have a higher propensity to buy. Is this enough? The client wants more volume."
...to which I responded,
"Social data allows you to target to very niche groups -- the tighter the targeting the better. After all would you rather have a much higher response rate, spending less on advertising, targeting a more finite group than doing a blanket campaign across a larger volume with a standard 0.15 per cent CTR?"
The value of social data is the amplification value and allowing social strategies for outreach to augment the ad performance. It also allows you to find "like individuals" by profiling users from social data results, and targeting them with similar content or offers. This results in BOTH a higher response rate as well as word-of-mouth effects. This is where you get your volume. It also allows the marketer to spend more wisely and opens the door to developing sustaining relationships with the consumer.
...after all, why should our work as marketers get any harder?
Follow Hessie Jones on Twitter: www.twitter.com/@hessiejones