Conversational ABM: A Solution to the Personalization at Scale Challenge
As account-based marketing (ABM) gains popularity, personalization at scale may become a challenge for marketers and sales reps. Here, Sonny Dasgupta, Vice President of Product Management, Conversica, discusses how conversational AI can solve this challenge and help realize the full potential of ABM.
Account-based marketing (ABM) has emerged as THE go-to-market approach for sales and marketing teams looking to convert target accounts into active opportunities and, ultimately, grow their pipelines. In fact, in a 227-person study by Renegade Research, commissioned by Conversica, 87% of sales and marketing professionals surveyed stated they believe in ABM’s efficacy. Moreover, 86% said they believe in its ability to help their organization close more deals.
What makes an ABM strategy so successful? Simply put, it flips the script on previous “Spray and Pray” approaches to lead-based marketing, where marketing teams would cast a wide net and send generic communications to everyone (and anyone) to fill up their funnels with leads with only a few expected to convert to customers. ABM instead necessitates teams to identify target accounts that fit their ideal customer profile along with the buying groups within these companies to deliver highly personalized engagement to drive them towards a sales conversation.
But imagine trying to manually personalize every single email, online chat or text message to multiple individuals within multiple buying groups and verticals, according to where each account is in the buyer journey across hundreds or even thousands of accounts. It would be practically impossible to scale for even the most well-staffed sales and marketing teams. It’s a very real struggle that marketers and salespeople face daily when executing ABM. Personalization quickly becomes a double-edged sword, as both the inherent reason behind ABM’s success and ultimately its biggest challenge: scalability.
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Personalization at Scale: A Challenge of Time and Capacity
ABM works well in today’s digital age because buyers have come to expect a consistent omnichannel experience with quick and personalized engagement at every touchpoint. ABM tools, such as 6Sense and Demandbase, help generate intent data to facilitate sales and marketing teams when personalizing engagement. Such data capture the recorded behaviors of prospects online — what are they researching? What problems are they trying to solve? Coupling this intent data with additional first-party data about the buyer, predictive scoring provided by ABM tools, and value-driven statements can help teams deliver a positive experience at every touchpoint to elicit increased engagement from potential buyers and improve the accuracy of buyer qualification.
However, Renegade’s ABM study also found that an alarming number of marketers and salespeople aren’t actually leveraging the intent data from their ABM tools. Among the survey respondents, only 49% of salespeople and 43% of marketers said they use intent data to personalize their buyer communications. Moreover, only 38% of salespeople are sending personalized communications to top prospects on every single touch. And yet, the findings also show that 41% of marketers believe that their salespeople are personalizing their communications, while only 23% of salespeople think the same. This indicates a clear disconnect between marketing and sales teams on the execution of their ABM strategy — the level of personalization that everyone agrees is necessary is simply not happening.
From the study, we can point to several reasons why marketing and sales teams are struggling to collaborate and deliver personalization to their target accounts:
- There’s too much data: 42% of the respondents believe their sales teams are overwhelmed by the amount of intent data available from their ABM tools.
- We don’t have the manpower: When asked what’s preventing their teams from realizing ABM’s effectiveness, 33% echoed sentiments that they lack the staff needed to efficiently process, intelligently interpret, and effectively use all the data to deliver personalized communications.
- Personalization takes too much time: On average, each salesperson in the Renegade study spends 16 hours a week just researching prospects for personalization. But despite the heavy time investment, that data isn’t being used to consistently personalize communications, a costly missed opportunity both from the perspective of wasted resources and outreach effectiveness.
Given that the challenges of manual personalization are largely tied to time and human capacity constraints, an ideal solution would be to automate these communications so that every account and buyer receives the right amount of attention while maintaining high-quality levels of personalization. Conversational AI is one solution in the market today that fits the bill and can complement ABM programs to augment sales and marketing teams’ outreach capacity.
When Conversational AI Meets ABM
Conversational AI is powered by a combination of natural language processing, AI, and machine learning. AI Assistants act as an organization’s digital marketers and salespeople to automatically engage buyers in human-like, two-way interactions at speed and scale across the entire customer revenue cycle. The result is a transformative solution approach that can deliver on the promise of even greater revenue and higher returns than ABM alone: Conversational ABM.
How Conversational ABM works is the AI Assistants will recognize and utilize the intent data from prospective buyers from target accounts. Leveraging this data, the AI Assistants deliver personalized interactions according to their needs and place in the buyer’s journey. For instance, the AI Assistants can answer questions and offer high-value content relevant to their challenges over email. From the email exchange, it’s possible to identify if a buyer is truly in-market. And if they are, the AI Assistants will continue to follow up and nurture the relationship with more helpful information, just as a human employee would.
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Conversational ABM will keep sales teams updated on when these buyers read and reply to emails and/or visit your site. Sales will know when buyers are ready and can jump in, run the last mile, and close the deal. The AI Assistants essentially alleviate human representatives from demanding tasks like interpreting intent data and tailoring communications, which require significant time and work capacity, as noted in the study. The outreach is completely automated and therefore scalable even as your number of target accounts grows. Prospects benefit from an enjoyable experience from their very first point of contact.
As more companies are adopting ABM, they are also discovering the double-edged sword of personalization at scale. It’s simply impossible for human-powered engagement alone to deliver the same levels of promptness, personalization and persistence to every buyer across every target account. But when marketing and sales teams can lean on AI Assistants to make optimal use of intent data, engage in real two-way conversations with buyers and improve prospect qualification, the results are no more canned interactions and a higher conversion rate. You can realize the full potential of ABM: increased engagement, accelerated deal cycles, and better experiences for every account.
How are you using conversational AI to overcome the challenges of personalization at scale in your ABM efforts? Let us know on Facebook, Twitter, and LinkedIn.
