Conversational AI: Augmenting Account-Based Marketing Success
By David Greenberg, Chief Marketing Officer, Conversica
Marketers, picture this—you’ve adopted a new Account-Based Marketing (ABM) strategy. You’re identifying target accounts and contacts in hopes of nurturing them with personalized, relevant content to usher them towards conversion and someday a long-term customer relationship. Then when it comes time to execute and actually personalize your engagements—the very foundation of ABM—you simply don’t have the bandwidth to tailor every conversation to where each contact is along the buyer journey. Questions emerge: Which of these accounts are really ready for a sales conversation? Are marketing and sales teams both doing their part to personalize communications? Is this ABM thing working?
If this predicament sounds all too familiar, find comfort in the fact that you’re not alone. In a 227-person ABM study by Renegade Marketing, commissioned by Conversica, only 43% of the marketers surveyed said they use intent data from their ABM platforms to personalize contact communications. The reason for the lack of personalization? A challenge of scale. Many marketers and revenue teams can’t keep up with the dozens or even hundreds of accounts that require highly personalized conversations on a regular basis to achieve optimal success with an ABM strategy.
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The fact is, adopting an ABM strategy is one thing but having effective solutions for execution is another—solutions that can address the underlying difficulties of personalized engagement across a high volume and frequency of conversations and augment the work of revenue teams.
The Tools of the Trade
To unpack the challenge of personalization at scale, we must begin with the tools designed to help marketers execute an account-based program. ABM platforms like Terminus, Demandbase and 6Sense have gained huge popularity alongside the rising adoption of ABM as a strategy for converting target accounts and building customer relationships.
These platforms help by collecting extensive intent data on buyer behaviors as they interact with a brand, such as the content they’re consuming, the products or services they’re researching and how frequently they return to a website to learn more about a company. Intent data enables revenue teams to understand each account’s stage in the buyer journey, improve buyer qualification and predictively identify who is truly in-market. But how they execute the necessary engagement from this data is critical.
Unlocking the Scale of Engagement Challenge Among Revenue Teams
Actionable intent data is invaluable to any account-based program. From the Renegade Marketing ABM study, however, we see the old adage is true—you can have too much of a good thing. Among the survey respondents, 42% believe that sales teams in particular are overwhelmed by the volume of intent data coming from their ABM platforms. Beyond the amount of data, these revenue teams—like many industries currently—just don’t have enough manpower. Of the respondents, 33% noted they lack the staff needed to process, review and leverage their intent data for marketing and sales communications.
For the available marketing and sales talent—because there’s so much data to sift through for so many target accounts—they end up ignoring their ABM platforms and conducting independent research about their contacts through company websites, Google search or social media. In fact, only 40% of the respondents in the ABM study said they even look at intent data when researching contacts. All that manual research is unscalable and takes a lot of effort and time that instead could be dedicated to engagement.
Meet Conversational AI—Your Best Teammate
When you don’t have the time and capacity to complete critical tasks with your available human resources, technology can provide relief. Here is where AI comes into the picture. Conversational AI solutions today can augment revenue teams’ capacity for personalized engagement and scale up as the number of target accounts grows without requiring increases in headcount. Through breakthroughs in Natural Language Processing and Machine Learning, AI Assistants serving as digital representatives for a company autonomously engage with contacts in dynamic, two-way conversations. The interactions are so humanlike, most prospects and customers just assume they are talking to an actual person.
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Paired with an ABM platform, the AI Assistants will leverage captured intent data to personalize entire interactions with contacts according to what they’re researching and their current buying stage—just as a human marketer or salesperson would. They can communicate over the contact’s preferred digital channel—including email, SMS, webchat and even social messaging—and continue to deliver consistent follow-up and prompt responses with relevant content.
From these conversations, the AI is smart enough to qualify prospects and determine if and when they become a Conversation-Ready Lead (CRL), i.e., a lead who has truly been warmed up, is fully engaged with your organization, and is ready for a sales conversion. The AI will then route CRLs to a human representative to seal the deal. Once the account becomes a customer, AI Assistants can also augment Customer Success managers in maintaining communications and identifying opportunities to expand the relationship and product usage to drive continued revenue growth. From an account’s initial discovery stage to time as a long-term customer, AI Assistants can help attract, acquire and grow customers across the entire buyer journey.
Conversational AI solutions essentially take over repetitive, manual processes like interpreting intent data and personalizing engagements for sales-ready conversations, which are critical to ABM but consume the time and resources of revenue teams. Through automation, these solutions can deliver a scalability that would otherwise be humanly impossible. In turn, all contacts at target accounts are able to enjoy personalized interactions that solve their challenges and a better customer experience. Marketing, Sales and Customer Success teams gain bandwidth to focus on higher value tasks or accounts that require more high-touch engagement. By combining Conversational AI and ABM, you get Conversational ABM—a powerful way to realize the full potential of an account-based program with greater engagement rates and revenue opportunities.
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