Adopting an Account-Based Marketing (ABM) strategy is one thing; having effective execution solutions is another. These solutions can handle the underlying challenges of personalized engagement while augmenting the efforts of revenue teams.
ABM platforms have become very popular with the rising adoption of ABM to convert target accounts and build customer relationships. These platforms aid in the collection of significant intent data on buyer behavior as they interact with a brand, such as the material they consume, the products or services they study, and how often they return to a website to learn more about a firm. Revenue teams may use intent data to understand each account’s buyer journey better, improve buyer qualification, and anticipate who actually in-market is. However, how they carry out the engagement based on this data is crucial.
Achieving the scale of engagement challenge among revenue teams
Any account-based program benefits significantly from actionable intent data. There is a shortage of marketing and sales personnel because of the huge amount of data to sort through for numerous target accounts. As a result, they abandon their ABM platforms to complete independent research on their connections via corporate websites, Google searches, and social media. All of that laborious research is unscalable, and it takes a lot of time and effort that could be better spent on the engagement.
The best teammate: Conversational AI
Conversational AI solutions can complement revenue teams’ capacity for personalized engagement today, and they can scale up as the number of target accounts expands without necessitating headcount increases. AI Assistants working as digital agents for a company autonomously engage with contacts in dynamic, two-way conversations due to advancements in Natural Language Processing and Machine Learning. Because the conversations are so humanlike, most prospects and customers believe they speak with a real person.
When combined with an ABM platform, the AI Assistants will use collected intent data to customize entire interactions with contacts based on what they’re investigating and where they are in the buying process.
The AI is clever enough to qualify prospects based on these conversations and identify whether and when they become a Conversation-Ready Lead (CRL), i.e., a lead who has been thoroughly warmed up, is completely engaged with the organization is ready for a sales conversion. After that, the AI will direct CRLs to a human person to complete the transaction. Once the account has been converted to a customer, AI Assistants can assist Customer Success managers in maintaining communications and discovering opportunities to enhance the relationship and product usage to achieve revenue development. AI Assistants can help attract, acquire, and grow clients across the buyer journey, from the account’s initial discovery stage to time as a long-term customer.
Also Read: Efficiencies of Customer Journey Mapping
Conversational AI solutions essentially automate repetitive, manual operations like understanding intent data and tailoring engagements for sales-ready conversations, which are vital to ABM but drain revenue teams’ time and resources. These technologies can provide scalability that would otherwise be impossible to achieve manually. As a result, all target account contacts can benefit from personalized interactions that solve their problems and provide a better customer experience. Marketing, Sales, and Customer Success teams get more time to focus on higher-value projects or accounts that require a higher level of high-touch involvement. Conversational ABM is a strong technique to fulfill the full potential of an account-based program with higher engagement rates and revenue opportunities by merging Conversational AI and ABM.
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