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Stay afloat: use account selection techniques that prevent holes in your ABM program

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As B2B marketers, we’re rapidly waking up to the power of Account Based Marketing (ABM) alongside our Inbound Marketing efforts. Our collective ABM kindling developed in response – in part – to the waning effectiveness of Inbound marketing. The cause of which is content shock, a term coined by Marketing Strategist Mark Shaefer, suggesting there is simply too much content chasing thought leader status in every industry.

ABM has the capability to align our sales and marketing teams to accelerate the sales velocity for our organisations. This in turn increases the speed with which accounts close, allowing us to target more target accounts. Its effectiveness is clear – Sirius Decisions research shows 91% of B2B teams using it go on to see larger deal sizes than forecast.

ABM includes a set of well-defined steps, the most important of which is account selection. It is crucial to ensure that the accounts included in our ABM initiatives are worthy of ABM effort. These accounts need to have a high probability of converting and going on to become profitable accounts.

For ABM, the best measure of potential profitability is customer lifetime value (CLV). It is the present value of the total profits we expect to earn from the account over the full duration of the customer relationship.

Our choices should reflect this need for the overall account to be profitable. Budgets will therefore dictate how many of the three strategic approaches we choose and which accounts fit which strategy.

Choosing the right ABM strategies

Our choice will be governed by our ABM budget, the size of our accounts (and the number of stakeholders within them) and the value of the service/product we can sell into them and then decide which approach to take from the following:

i) Strategic ABM or one-to-one accounts

This is resource intensive, so accounts should be a substantial economic prize to justify the investment. Usually this consists of a small number of accounts based on available budget and the size of the sales and marketing teams.

ii) Industry ABM or one-to-few ABM

Each group has up to 15 accounts, with a focus on groups of identified accounts that share similar business attributes & needs.

iii) Programmatic ABM or one-to-many ABM

Moving to larger groups requires balancing messaging relevance within our target accounts. Otherwise you risk reducing the benefits of an ABM approach. This approach though is geared towards identifying accounts who in the future may well fit into either of the previous ABM strategies or move directly into a traditional account based sales approach.

Differing approaches to ABM account selection

There are three approaches to account selection: Manual Selection, Predictive Selection and Behavioural Selection.

Manual account selection

This is often the starting point for account selection and involves qualitative data gathered from sales and marketing teams. This is then combined with firmographic data based on perceived or ideally analysis of historic sales data.

Predictive account selection

Through the application of machine learning, predictive account selection gives us the ability to process a vast number of data signals from historic performance and external data sources. This selects target accounts based on more than just qualitative discussions between sales and marketing and firmographic data. Predictive account selection allows us to map account similarities in order to determine what makes customers a good fit for our business.

Predictive account selection allows us to look at a broad array of data points. These include traits like technographic history to continuously reprioritise account sets based on events affecting our target accounts.

Account selection is not a one-off exercise and the use of predictive technology can allow us to iterate on our target account sets continuously.

Behavioural account selection

Behavioural data can be obtained both internally and externally. Internal behaviour shows us how our accounts are interacting with our content both online and offline. External behaviour indicates if our accounts are researching topics connected to our products outside of locations we control. For example on third party websites.

Our account list is not static and should re-prioritise based on behaviour. Understanding how different stakeholders are behaving on our site and beyond supports this prioritisation.

Implementing the best approach to account selection

Clearly, manual account selection is time consuming and expensive to deliver over time within an ongoing ABM program. However it is useful as a first step to understand the key data points that support strong account selection.

Implementing this thinking within a predictive account selection approach combined with event based or behavioural based content allows us to then prioritise the accounts within our various ABM strategies. This allows us to spend valuable ABM budget in the right places.

At Radiate B2B, we automate not only the process of account selection, but also combine this with all three of the ABM strategies. We then integrate this into our Account Based Advertising platform, which targets the offices where our key stakeholders work. This creates awareness within accounts not aware of us or reaches invisible stakeholders who are not aware of our strengths because they are at arms length within the sales process. This in turn accelerates accounts through our sales and marketing funnel.

We’d love to share more – get in touch via chat or here.

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