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How AI Helps Sales Understand the Buyer Journey

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Revenue teams spend a good deal of time and money budgeting for and trying new technologies in the hopes of seeing an uptick in ROI. We all want more closed deals and repeat business. What silver bullet will help us get there? Well, predictive analytics isn’t a quick fix, but it is a competitive advantage to help your business cut through the noise and see the forest for the trees. Done right, predictive analytics can make it easier to get to know and cater to the diverse individuals within buying teams.

Personalization is still the crown jewel in your shining sales strategy, and today’s companies have the means to do it well. You see it in consumer-centric email campaigns, pitch decks, smart LinkedIn ads, even promoted tweets… Everywhere people look, they’re being marketed to. But it only goes somewhere if they like and need what they see — if they’re the right type of buyer and it’s the right time for them to purchase.

The power comes with knowing not only who your audience is, but also where they are in the buying journey and what they want next. The harder, more important part is identifying, measuring, and supporting individual buyer journeys in a way that’s scalable.

What is the AI-based buyer journey?

You slap “AI” on the front of anything and it garners attention… and sometimes confusion. An AI-based buyer journey is a more personalized, proactive buyer journey rooted in extensive data. Simply put, you want real-time, individualized information about your buyers so that you can engage them and increase the likelihood of closing deals.

In fact, 6sense is the only account-based platform that uses AI to orchestrate dynamic journeys based on real-time buyer behavior. With the right capabilities in our account engagement platform, your teams can quickly gain the insights needed to build campaigns and outreach strategies that engage target accounts and contacts, create positive brand awareness, and help them move through the buying journey.

The value of knowing your ideal customer profile

But data alone isn’t enough to go on. In order to make the best use of your resources and align sales and marketing on the best accounts for the business, you need AI-based predictions to understand which accounts are a fit for your ideal customer profile (ICP).

Most businesses have a good understanding of the specific industries, company sizes, and perhaps general buyer personas that typically make prospects a fit, but those factors don’t give you a full, or up-to-date picture of your true target accounts — or how to engage them. AI picks up where human learnings leave off, analyzing past sales history to uncover the patterns and characteristics that make up your ICP. Because the more you feed AI the more it can learn and deliver, AI can continually refine this model as conditions change across your data, company, customers, and the market.

Catering to the contact level of a target account

Account engagement is about exactly that — engaging accounts. More importantly, your teams need to be able to build relationships with the right contacts within a target account. AI can help you evolve to a point of knowing which contacts and personas to prioritize, as well as identifying whitespace in the buying center where additional contacts should be acquired. Digging into the contact level of an account can help your team make the most of their budget and outreach strategies, especially when combined with other predictive capabilities that allow you to scale your engagement efforts.

Predicting the future depends on knowing the past

In order to predict future account engagement and growth opportunities, you need to study past opportunities. Consider a contact’s current level of engagement. Are they highly engaged, as were contacts from previous successful opportunities? Or does your team need to focus their energies on engaging key contacts in the buying center?

An AI-based buyer journey is rich with past information that dictates, or at least discerns, likely future behavior. That includes the ability to predict who and when to engage next based on buying center activity. 6sense’s predictive models can tell you where there’s low or no buying center activity and what to do with that information.

Piecing together a fragmented buying journey

You can stand outside an account’s window with a boombox in the middle of the night proclaiming products and services they might need and hope it works out… or you can use AI to pinpoint and engage the right contacts at the right time. That’s what our customer Cumulus Networks did.

Cumulus provides open networking software for the modern data center, and with 6sense they’ve been able to improve visibility into the entire buying team and prospect, enrich contact data for target accounts, and ensure adequate contact coverage in geographic regions where there used to be whitespace.

You can’t make an account buy based on a midnight concert on their front lawn, but you can become more targeted, personalized, and intuitive in your approach. B2B buyers remain anonymous through 70% of the buying journey today, and each person on the buying team takes their own unique journey. That’s a lot of serenading. But with the right account engagement platform, you can leverage predictive, intent, behavioral, and other account data to dynamically engage the right accounts at the right time with relevant, consistent, unique experiences.

Need help determining the right AI-driven solution for your account engagement strategy? Check out our report ABM Buying Guide: How to Choose the Right Solution for You.

The 6sense Team

6sense helps B2B organizations achieve predictable revenue growth by putting the power of AI, big data, and machine learning behind every member of the revenue team.

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