Hyper-targeted B2B marketing misses the bigger picture

As appealing as hyper-targeting may seem, relying on it limits growth and ignores essential stakeholders within the buying journey. If you run an enterprise resource planning (ERP) software as a service (SaaS) brand specializing in mid-tier companies, then targeting Heads of Operations at companies with an annual recurring revenue (ARR) of £100-500m might feel like a common-sense move.

But, to stay competitive and foster sustainable growth, B2B brands need to expand their audience reach, capturing both direct users and the broader array of influential stakeholders within a company’s decision-making chain. This is also common sense and is often agreed upon by anyone who has any sort of say in designing and implementing marketing strategy, but it is rarely enacted.

So, why is it so rarely enacted? Well, we can lay some of that blame at the door of the McNamara fallacy: the easiest things to measure quite often end up being the wrong things to do.

Hyper-targeting pitfalls

In the world of B2B – although not exclusive to the discipline; consumer-facing brands are guilty of this too – narrowing your audience down to a highly-specific segment, focusing efforts on maximizing exposure to them, and then reporting the outcomes of that exposure in the form of immediate actions (clicks/views/downloads, etc), is a trap marketers all too often fall into. Just because you can overlay something, doesn’t mean you should.

Hyper-targeting promises high relevance and engagement, but this efficiency often comes at a price (both in a budgetary and opportunity sense). When ads are designed to reach only those who are actively engaging, brands can unintentionally exclude other critical decision-makers – often in finance, HR, procurement, and C-suite: basically anyone who has any say in the purchase process whatsoever.

Key decision-makers

This overstated focus on the people who might hit download or fill in a lead gen form rather than the people who have the power to make or break a deal is misguided. These people might not engage with the content immediately. They may only ever engage with it passively. Yet, their awareness and perception of the brand will be influenced. This builds mental availability: a state where the brand is recognized, considered, and called upon at the moments that matter in the purchase process.

When hyper-targeting, you ultimately end up repeatedly serving content to the same small audience segment. Over time, the effectiveness of these hyper-targeted ads diminishes. You’ve basically harvested all of the 5% that are in-market right now, are over-exposing to this group, and therefore wasting budget.

As a double whammy, you’ve made no in-roads into the wider buying committee either as you’ve spent so much time and money trying to get your form fillers to fill in a form. Growth becomes much harder, limited to a narrow band of users, and stifles any sort of positive trajectory that brand equity was on.

And when you get into the latter stages of the sales process, those in-roads you have or haven’t made come back to either help or haunt you. The ‘hidden buyers’ emerge, and you don’t stand much chance of progression if they have no idea who you are.

Precision misleads

When it comes to paid advertising, the supposed efficiency of narrowing in on your audience to a highly targeted level often doesn’t hold up under scrutiny either. This great piece of analysis by the B2B Institute reveals that these campaigns tend to be disproportionately costly, as each layer of targeting drives up the CPM, resulting in a significant premium being paid to reach increasingly refined audience segments. This makes sense, you might think – why shouldn’t you have to pay extra to be more accurate? Well, because it’s not more accurate.

Step outside of the world of first-party data (still not a reason for hyper-targeting) and you’re into a world of farcically inaccurate data. If we take that quintessential B2B targeting segment, the ‘IT Decision Maker’, as an example, this brilliant piece of research by Nico Neumann, in partnership with HP, tells us that it’s only 14% accurate. That’s a low percentage, given the simplicity of the variable and the billions spent by advertisers in targeting that exact variable.

And HP acted upon this research, saving considerable sums of money in the process. They shifted their ad strategy away from third-party-based, instead focusing on timeless, ever-reliable, contextually relevant targeting, as well as developing and leveraging first-party data (1PD) relationships to craft a more efficient route to their IT decision makers (ITDMs).

Think big

It's important not to confuse broadening audience reach with a ‘spray and pray’ approach. The need for targeted comms, delivered to the right audiences with minimal wastage is of course paramount for all B2B advertisers. What happens though is that hyper-targeting can become a distraction: following the easy-to-follow data can lead you down a path to minimality and severely limited effectiveness.

It’s this, as strategic marketers, that we must avoid. But with this comes a requirement to think differently, to step outside of the relative safety of immediate digital key performance indicators (KPIs), and to ultimately lean a bit more heavily into the art over the science. The intangible parts of the discipline are the parts that truly deliver long-term effectiveness – the emotional connection, the mental availability, the things that mean you’re on that shortlist before the procurement process even kicks off.

We’ve known for decades that brands grow by reaching more prospective customers. The Double Jeopardy Law deals with this. Growth comes from reaching more people. And you can’t reach more people if you’re obsessing over hitting the granularities of an overly-segmented audience.

Marketing isn’t supposed to be a perfect science; if you’re doing it right, then you probably never will have an iron-clad set of irrefutable data points to support your idea. But that’s the reason why some brands are better at it than others. They step outside the relative ‘safety’ of hyper-targeting, and they follow the real data to make the leap towards a much bigger prize.

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