Account-based marketing: Data-driven selection for ABM success
ABM (or account-based marketing) is not a new topic. A simple web search will yield hundreds of thousands of results, yet many of them only scratch the surface as to the true power and potential of ABM done right.
Diving deep into the strategic capabilities of ABM raises numerous questions, which can often serve as a bottleneck for many marketers and businesses trying to make sense of the multiple ABM options available, such as:
- How do I decide which ABM approach is right for me?
- How do I go about selecting the right accounts to market to?
- How do I group my chosen accounts into different sets of data and select which to prioritise?
- How can I upscale my target accounts through the ABM pyramid?
Answering these critical questions can propel businesses up both the ABM Pyramid and ABM Maturity Scale, empowering marketers with the tools and expertise to do what, arguably, they should have been doing all along: creating and delivering personalised and targeted experiences that build deep, long-lasting customer relationships.
ABM Pyramid: Data-driven selection
On the face of it, account-based marketing is just good marketing. It’s all about building good relationships with businesses, fuelled by effective marketing/sales activities and an excellent customer experience. The critical consideration, and what often holds businesses back, is through their use of data — and that is where we, as marketers, must improve if we are to make ABM (or marketing in general) and success.
Ultimately, marketers want to increase revenue and prove their worth to the business, but when it comes to ABM, obsessing over the cash isn’t a practical starting point. Start with the basics and ask the fundamental questions, such as: “Are we looking to run a pilot, or are we looking to overhaul our entire revenue business?” The answers to these questions will inform which accounts sit where on the ABM Pyramid.
The key objective for marketers is to push the right accounts further up the ABM pyramid, and this goes hand in hand with improving the maturity of marketing’s ABM approach. Of course, not every target account will be suitable for the holy grail 1:1 approach, but if it is, there are a number of ways marketers can get them there.
This is where advanced data-driven selection really shines, pulling together historical and current sales data, along with both qualitative and quantitative insights. For example, not only comparing engagement between two accounts, but also the data coverage of each account (i.e. how many contacts you have within this account versus another), along with other variables such as pipeline, pipeline volume, number of opportunities per account, or even anecdotal feedback from colleagues).
The ABM Maturity Scale: Advanced technology to upscale accounts
With such an overwhelming amount of data to crunch, high maturity businesses possess a robust marketing tool or system — a database that’s capable of running sophisticated searches and analysis of accounts, pulling together data from multiple marketing and sales sources that, ultimately, gives everyone across the business a single, centralised view of each key account.
More than that, in order to really get the answers they need, high maturity businesses are hiring dedicated analytics experts to sit down, ask the right questions, and provide the answers via detailed data analysis. With this level of maturity, marketers will possess a much higher degree of success when closing opportunities with high-revenue businesses.
ABM can get even more advanced with the right tools at a marketer’s disposal. Market intelligence tools add even more detailed insights to an ABM database, such as average deal sizes in particular industries, or which competitor a target account is currently using.
Another area also worth exploring is propensity modelling, whereby particular traits and attributes of successfully targeted ABM accounts are added together to create ideal pathways and scenarios, tried and tested for maximum chance of success.
Predictive analytics can add even more sophistication to an organisation’s ABM approach. Using modelling tools, teams can insert an ideal customer profile into one end of the system, and be served a number of suggested accounts that match that profile. Critically, these suggested accounts hail from outside your existing database, helping you tap into new prospects that were not even on your radar.
I doubt there is any company in the world that is exploring every single one of these approaches, or at least doing it perfectly. Ideally, businesses need to approach ABM with an open mind, and be willing to adopt a mix of all the different approaches. But, ultimately, the key to running successful ABM lies in the data, and the sooner businesses realise this — and do all in their power to go data-driven when it comes not only to account selection, but also nurturing and upselling — the sooner marketing will able to prove its place at the table.
Learn more about Adobe Marketo Engage on the ABM resource hub here.