Closing the B2B | ad tech gap

4 ways the new age of ad tech fails b2b marketers and what to do about it

(An excerpt of this article ran in Ad Age on January 15, 2016.  http://adage.com/article/digitalnext/close-b-b-ad-tech-gap/302149/. Here’s full post). closing the gap

Recently, I saw an IAB B2B Programmatic study that revealed nearly half (47%) of B2B marketers don’t even know what programmatic buying is. That’s a staggering gap compared to B2C marketers where fully 62% of marketers use programmatic (Source: eConsultancy).  This gap is even more stunning considering that B2B represents $77 Billion in digital media with 66% of B2B marketers recognizing that programmatic is just as valuable for them as it is for B2C marketers, (Source: IAB: 2015 Programmatic and The B2B Marketer – Study – http://www.iab.com/news/programmatic-and-the-b2b-marketer-study-confirms-more-education-is-needed/

What’s accounting for this gap between B2B and B2C marketers?

IAB rightly believes education will help, but I suggest there’s something more fundamental going on.  Beneath the “cool ad tech veneer” lies a vast sea of ventures specifically designed to chase large consumer ad dollars but in the process, left B2B advertisers in the ad tech dust.

Here are the fundamental B2B gaps I see and what you can do to overcome them.

1) The great CPM/ CPA performance divide.

Unlike B2C marketing with well-organized branding/ promotion/ direct marketing buckets, B2B campaigns are a more fluid mix of CPM and CPA goals requiring tactics to be both thought leadership and demand generation.

Unfortunately, startups with their decided preference for CPM deals where generating a click is much easier than a qualified lead, created this artificial CPM/ CPA divide that B2B marketers have to live with. The result is that business marketers must patch together a crazy quilt of CPM ad buys along with CPA programs requiring lots of coordination between uncoordinated platforms and networks – a challenge all around.

To combat this issue, pivot from tracking typical metrics like “clicks” or “likes,” to KPIs like Cost Per Visitor. Not all networks will play with you this way – but the quality, “niche” networks will work with you to develop meaningful KPIs.

2) The confusing content marketing tech landscape is a kill joy

B2B revenue results rests on the back of hard working content – technical documents, white papers, thought leadership publications, case studies, reviews, social, PR on innovative new breakthroughs; making B2B businesses far more reliant on content marketing than their B2C peers.

The problem is that content marketing, as a category, is a fragmented, operational nightmare. Content creation platforms are walled gardens from buying platforms and social media is detached from targeting platforms. Throughout this chaos, “data” plays hit and miss trying to analyze these disjointed pieces. The complexity sucks much of the inspiration out of the process.

Salvation here means looking for operationally complete platforms that marry content-based data with ad buying capabilities and an integrated set of analytics that normalize the learning between the user’s topic discovery steps to a qualified lead.

3) B2B programmatic landscape is like blowing out a targeting candle with an impression hurricane.

One word sums up this problem: “scale.” The ability to deliver “billions of impressions” for a campaign is not something B2B ever needs unlike many consumer marketers.  Yet programmatic’s brute, muscly impression pushing machine grinds out any nuanced precision that is critical for B2B marketers.

Solving this issue requires some imagination for now until the programmatic system stabilizes (it is still in its infancy as platforms go). In the meantime, here are some stop gap measures:

  • B2B should think of programmatic as the opportunity to automate optimization efforts, not as a way to uncover lower cost CPM (though that might happen)
  • Over time, header bidding, while not new in itself, will bring many niche publishers into the programmatic ecosystem relatively quickly. Keeping up-to-date on this trend can give B2B marketers new programmatic inventory that’s very targeted.
  • Include “learning KPIs” in programs so that whether campaigns “win or lose,” the brand gained new learning to optimize the next round

4) The fallacy of audience targeting for B2B

No matter the ad tech platform, algorithmic targeting promises precision to deliver the “right time/ right place/ right message…” benefit to advertisers.

Who can argue with that until you start unpacking the core model for B2B and then the gaps become plain as day.

The basic structure of most targeting technologies (allowing for some oversimplification) rests on a demo profile using basic attributes like gender, geo, education etc. This target is then enriched with external data (usually via DMPs) to add “precision” like keywords or device awareness or “interest categories” – a fairly broad set of classifications that all keywords are categorized under. Optimization occurs as the algorithm learns which profiles do the most clicking and continue to go find more of those high clicking profiles.

There’s a lot to love about this tech if you are a B2C marketer, but unfortunately this model fails apart at the outset for B2B and goes downhill from there.

  • B2B audiences don’t fit into any “standard” demographic profiles such as gender or income. Even attributes like “title” are not easily applied to B2B
  • Using demographics as the basic targeting foundation does not reflect real time intent of users. This explains why we see so many ads for serious white papers on silly sites with cute kitties.
  • The ability to target by topic (not keywords mind you) is a proven strategy for B2B marketers, yet this capability is highly constrained to fit narrow “interest classifications” ala Google or the content syndication networks. The current level of “interest targeting,” quite literally, is “off topic” for B2B audiences given these categories’ very consumer orientation.

To solve this gap, the key is to look for content tech players who are integrating topics with programmatic ad tech and sentiment analysis with social publishing. Context for B2B is the inverse of B2C. Topics come first and then selected demographics – such as geo.

The new age for ad tech seems to have left B2B mired in an ecosystem that doesn’t fit them well. Yet, with $77 Billion in digital media spend, B2B deserves some serious respect.  Hey Silicon Valley – are you listening?

 

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