Artificial intelligence can be a helpful tool when implementing an account-based marketing strategy, argues Demandbase’s Jessica Fewless
Jessica Fewless, VP of ABM strategy at Demandbase, is disappointed artificial intelligence (AI) hasn’t created a world like the ‘The Jetsons’, complete with flying cars and dinner that falls out the sky. Aside from AI’s association with virtual reality and poor email automation, Jessica believes the technology can have some application within account-based marketing.
She explains the landscape of AI within B2B reflects most marketers’ negligence of it regarding ABM. “In the B2B space, it’s been a little bit tougher [than B2C]. We’ve purchased a lot of technology, but unfortunately, marketers don’t use it properly. They use it to mass blast a message anywhere they can on what they think are contextually relevant sites, and then getting excited about a 0.1% click-through rate.”
Jessica argues that AI’s ability to quickly process a flood of data can accelerate the scale of ABM as well as its benefits. “Some say ‘isn’t that just good marketing?’. Yes,” she admits. “But ABM at scale is still looking through the lens of a target account list.”
During her talk at the
B2B Marketing Conference: Account-Based
Everything
, she outlined how AI can be manifested into an ABM plan:
1. Identify account intent
AI can be a helpful tool during the account selection process as it’s able to gauge intent. Firstly, you’ll have a total addressable market that will meet basic criteria such as revenue threshold, headcount and sector. From this, a company must whittle down its account list according to how well it fits with the business. From a resource perspective, forming a relationship with all accounts that meet basic criteria would be wasteful.
Refining your target account list concentrates success rather than limits opportunities. Jessica revealed this method of account identification was something Demandbase implemented a few years ago and realised there were companies that met basic requirements but weren’t suitable to sell to.
“We’re a stats-based company and if they churn from us in less than a year we lose money on them. So, we took the elements that made those customers churn and removed them from our [criteria] model,” she explained.
AI is most useful in the third filtration stage when deciphering timely intent. Although a prospect may align with all basic and intermediate criteria, it may have just signed a new two-year contract with your competitor and, therefore, isn’t worth your investment at this stage. By using AI, an account’s timely intent can be discovered quickly, which is particularly useful if there’s a small timeframe in which to initiate ABM.
2. Optimise the buyer journey
The buyer journey and its existence is something that’s been discussed many times; Jessica summarises the journey as having the same trajectory as a bumble bee. “Everyone likes to draw a graph that looks very linear, but in reality, it’s very hard to humanly predict.”
AI is able to build an idea of an account’s individual online behaviour, which will allow you to predict the right time to close the deal.
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3. Personalise website content
What the audience wants to see and read is at the heart of content planning and AI can improve this accuracy. By using data, AI software is able to build a profile of interests on individual accounts and pull the most relevant content to the front of the website.
“We make a lot of guesses as to what someone might be looking for on your website and AI can bring a little more intelligence to that,” Jessica said.
4. Hyper-target ads
Jessica admitted that having hyper-targeted ads is a similar benefit to that of personalised website content – but while in essence it is the same, it still has some value. Using data, AI can see what prospects are researching and which areas they are looking to invest in – this will allow ads around these topics to take priority, in turn reeling in stronger engagement.
“Ensure you’re getting the right information into your ads so you grab someone’s attention,” advised Jessica, making a case for AI’s place in ABM.
5. Develop an account-based sales team
A key element and benefit of ABM is the alignment of the sales and marketing team – and AI is able to boost this correlation further. AI tech is able to provide sales with activity and behavioural information, which they can then act on in a unique case-by-case manner. This approach receives better reception than the usual generalised ‘smiling and dialling’ rhetoric from the sales team.
“The sales rep can sit down with a whole dossier of information, so when they pick up the phone instead of saying ‘I have a thing you might buy’ they can say ‘I’ve researched your company, I know these things about you, you probably have this kind of issue and here’s how we can help.’ You’re much more likely to get a meeting off the back of that kind of conversation,” Jessica elaborated.
Programmatic ABM is distant from the origins of one-to-one but arguably personal interaction remains unscathed. Artificial intelligence’s primary area of action exists within the research stage, processing actions and behavioural recordings at an inhumanly fast pace. This gifts ABMers time to uniquely interact with prospects, their actions bolstered by AI-enabled assets such as hyper-targeted ads and personalised web content. However, the existence of AI within ABM remains ambiguous, while some stay away, others embrace it as a tool that allows, what Jessica coins as, ‘intimacy at scale’.
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