It has always been expensive to thread the needle with the traditional business-to-business marketing funnel. In the last year, however, the systemic gaps in the data and the cost of each tactic have become even more apparent.
B2B marketing has evolved from its roots in direct mail and telemarketing to explore more cost-effective digital methods for reaching customers. Search, ABM, title and intender targeting have led the way. But with the COVID-19 pandemic and most employees at home, these tactics have become infinitely more fragmented and decentralized. In-store sales or reaching corporate buyers in their offices has become impractical –- if not impossible.
Consequently, favored digital B2B marketing methods have been put to the test. Some passed, some didn’t.
The Data Waterfall Challenge
The consistent issue with B2B marketing has been identifying actual decision-makers with both accuracy and adequate scale; SEO is usually the first step. Paying for leads offers accuracy, but it is often expensive and typically produces a limited number of opportunities.
Step two is paying a list broker for a pristine record of qualified decision-makers with titles such as “IT Manager” or “chief financial officer” to fill the top of the funnel.
Now the second road-block hits — you post your (expensive) list for onboarding and quickly discover that the number of unique users on that list is going to be reduced by 67% to 75%. There’s either no corporate email or no active cookie sync for the individual titles on the list to match to. When a match does happen, it often defaults to the “corporate modem” — the mobile devices in the building that have equal access to the ad traffic targeting the chief financial officer. The CFO’s closest friends now get to see your advertising -– from the janitorial staff to the marketing department.
In order to adjust to bad match rates and inaccurate targeting, B2B campaigns often apply step three: extrapolated intender data from media visits. This gets user counts up dramatically. It fills the top of the funnel but also increases the cost of a campaign by diluting the efficacy of the original target list. What remains of your expensive list buy is buried in the process — resulting in additional media spend on unworthy and unverifiable targets.
Too often, the need for a volume of leads across the three tactics rarely meets MQL and SQL goals without costly repetition and trial and error. But filling and refilling the top of the funnel with little to no notion of qualified measurement negatively impacts the performance of each tactic, increasing ad spend and systemically degrading the marketers’ ROI.
The Silo Effect
One of the structural shortcomings of B2B data for programmatic advertising is that most data providers in the market are specialists. SEO optimization focuses on keywords and what it takes to buy a visitor. List brokers who are offline data specialists produce lists that adequately represent the definitive target audience, but conversion to digital identifiers is inefficient. Intender lists track anonymous media consumption using anonymous cookies and device IDs rather than verified users.
Finally, more often than not, cross-device to a home is modeled. Finding people at work and home is promising, but like intender targeting, it is predictive. Every tactic has benefits and every silo is a singular process with its own limitations.
The Next Big Thing
The common goal of all B2B campaigns is the identification of qualified employees who are actual decision-makers. As marketers, we tend to jump at using the latest buzzwords to portrait our strategy: decision-maker, influencer, cross-device … when, in fact, all we’re trying to perfect is a way to reach those key employees who will move the needle.
How do you start?
Most B2B organizations have a fairly refined list of organizations they want to target, typically identified by the organization’s name, domain and industry. Coupling that with a data source containing extensive employee profiles is key. The ability to deterministically identify employees at the right level (decision-makers), with the right titles and at the right scale is key.
With employee-based targeting, the onboarding of key employees requires deterministic business to home targeting. A cookie-free match of the business and the consumer profile improves match rates, accuracy and provides further insight.
But where this starts to pay off is when employee profiles are personalized and merged with the messaging. Employee profiles show us that people can work across industries, organizations, revenue, degrees, schools and certifications in their career. They also live full lives as consumers. A full employee profile of historical associations gives you more than just a current job snapshot — it gives you the ability to personalize your most qualified B2B audiences through the algorithmic extension of employee profiles and media.
Employee-based targeting allows marketers to fill the top of the funnel with cohorts of qualified prospects matched to qualified media and this dramatically improves the quality and scale of marketing engagement, effectively bringing together title targeting, intender targeting and ABM tactics without putting the marketer through the pain of trial and error.
Ray Kingman is the CEO and co-founder of Semcasting, a data-as-a-service (DaaS) provider. He leads the company in the development and commercialization of its automated targeting and data offerings. As an experienced innovator in content management, analytics and data visualization fields, Ray directs the day-to-day operations of Semcasting. His extensive experience working in the marketing and advertising industry field allows him to speak confidently on matters of consumer data privacy, identity resolution, brand empowerment, customer acquisition and digital and online marketing.