I had several meetings recently with friends from “traditional digital agencies”. That sounds so oxymoronic!
The reality is that this new course of big data, gleaned from a wealth of unstructured information on the web, has the ability to turn advertising on its head–– at least enough to make media people rethink algorithms for maximizing performance.
Coming from the ad world, I have seen the banner ad rise and fall in a span of 7 years. The value of search marketing (PPC) has had its heyday and now even 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 rticle, “The Death Of SEO: The Rise of Social, PR, And Real Content”:
“Google is in the process of making the SEO industry obsolete, SEO will be dead in 2 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 this entails? Shares, comments and reviews.
I would argue that another factor will unseed 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 our 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:
Mary Brown searches for information about a future trip to Halifax, NS. 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.
Now we have not only recent behavioural activity where she’s been on the internet, but we also are aware of her conversations that validate her behaviour. It is safe to assume that Mary will “definitely” be going to Halifax.
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, 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 ie “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 .15% CTR?
The value of social data is the amplification value and allowing social strategies for outreach to augment the ad performance. This results in BOTH a higher response rate as well as word-of-mouth effects. It also allows the marketer to spend more wisely and opens the door to developing sustaining relationships with the consumer.
And that’s only going to make us all far more effective and strategic.
A version of this post originally appeared on Hessie’s blog.
Founder at ArCompany, and Director, International Council on Global Privacy and Security by Design Hessie is a seasoned digital strategist, and intelligence analyst having held senior positions for top ad agencies including Ogilvy, Rapp Collins, ONE and Isobar Digital. She also has extensive start-up experience in AI technologies, social tech, online publishing and artificial intelligence like Yahoo! Answers, Overlay.TV, Jugnoo and Cerebri AI. Hessie is the co-author of EVOLVE: Marketing (as we know it) is Doomed! She is also an active writer for Forbes, Cognitive World, Towards Data Science and Marketing Insider Group.