Since it was codified in 2004, ABM has grown into a practice that combines several sales and marketing techniques to create a theory revolving around the collective decision-making process characteristic of B2B buyers. This practice allows companies to focus on funneling strong lead generation, lead scoring and lead qualification processes.
Once considered a potential addition to B2B marketing approaches, ABM has become an essential concept, as more and more companies are producing successful results from it.
1. Striking results
The current reality appears to live in the results, or more specifically, sales revenue. Sales alignment remains high for companies that practice ABM, with 60% of companies saying they are “somewhat” or “tightly” aligned with sales, compared to 34% in 2015, according to SiriusDecisions’ 2016 State of ABM Study.
More than 70% of B2B organizations have staff that are either completely or partially dedicated to ABM, the study says. In addition, 58% of those companies have ABM pilot programs, and 41% have full programs in place.
2. The B2B digital experience
“Today’s consumer, or buyer, is incredibly reliant on digital channels as they navigate through a purchase process, and they expect instant access to information,” says Bruce Swann, senior product marketing manager at Adobe Campaign. “To keep up with this empowered and always-on consumer, marketers need an approach that goes beyond managing sales and leads, to one that helps manage interactions across channels.”
We’re not talking B2C here. As much as 67% of the B2B buyer’s journey is done digitally, with online searches being the first course of action.
These trends have evolved to impact vendor positioning, marketing campaigns, and even product roadmaps in the B2B space, by establishing positions for vendors that provide contact and account data, predictive analytics vendors, content delivery tools, and marketing analytics vendors.
3. The value of personalization even for business accounts
One aspect of ABM getting increased attention personalization, a tactic that is often referred to as “marketing to an audience of one.” In the case of ABM, this presents the challenge of personalizing messages for the different decision-makers involved in a purchase.
Today’s B2B buyers, like any other consumers, share a great deal of information about themselves via digital, mobile and/or social media, especially professional networks like LinkedIn. This information can be integrated automatically into systems via interfaces with major networks, whereby marketers can sift through the information and personalize ads in real time. Communications can be more targeted as a result: It’s important in an ABM context to know when you’re messaging an marketing executive and when you’re messaging a stakeholder in IT.
Activating this data is one of the primary reasons the ABM stack, as some call it, is constantly being redefined. What was once done for a few important accounts, using spreadsheets, can now be done for large numbers of accounts.
4. It gets sales and marketing on the same page
The future of ABM may hinge on its ability to create alignment between sales and marketing.
On the marketing end, ABM practices have the capability to generate leads and sales throughout the funnel. Sales, on the other hand, can utilize ABM practices to target a person, or the prototype of a consumer, to start conversations about how to develop a message, and when and how to get a prospect to the next stage of the purchasing decision.
In aligning marketing and sales, brands are able to know what accounts to target and what an optimal prospect looks like for the company.
“Absolutely, [successful B2B marketing] does mean collaboration and alignment between sales and marketing,” says Vicki Godfrey, CMO of Avention. “One of the key trends for 2017 will be the ‘smooshing together’ of B2B and B2C.”
5. There’s an AI angle too
As technologies evolve so do the possibilities for B2B marketing. The AI industry has barely scratched the surface, yet there are several approaches for B2B marketers to utilize the technology to create a network of relationships between companies and consumers.
“Think about applying the data about your customers, accounts, and web traffic, and then go outside the four walls to the internet and look at what are those accounts doing, that’s when you have much more scalable information about who should I be doing business with and when,” says Chris Golec, CEO and founder of Demandbase.
AI does not only have the capability to pinpoint B2B consumers, but the culture of the consumer as well, such as whether targets do business with start-ups or only with established companies. In order to do this, according to Alan Fletcher, former CEO and co-founder of Spiderbook, AI needs feedback to refine the model.
“We start by building a profile – who are the company’s current customers, what do they sell, what markets are they in? And then we use that to start servicing new recommendations,” says Fletcher. “But as you engage with them, the feedback from that refines the model.”
This ever-evolving model is also powered by predictive analytics – enabling companies to accurately predict which leads are most likely to convert, and prioritize resources accordingly.
The level of highly-polished accuracy makes AI perfect for powering ABM through functions such as lead-to-account matching, a technique that allows matching of new and existing leads to their proper accounts; and more advanced site-level matching, which not only matches leads to the right accounts, but also creates an account’s “family tree” to pinpoint exactly where a lead fits into the company hierarchy.
The future is always uncertain, but if marketers and brands want to remain successful in this ever-evolving B2B landscape, ABM practices are going to be key.
