Marketing Automation Buyer's Guide

3 Ways AI Will Change the Revenue Technology Landscape

AI Will Change the Revenue Technology Software Market

AI Will Change the RevTech Software Market

As part of Solutions Review’s Contributed Content Series—a collection of contributed columns written by industry experts in maturing software categories—Latané Conant, the CMO of 6sense, shares insights into how AI technology can (and will) change the revenue technology (RevTech) marketplace.

Artificial intelligence (AI) used to be the stuff of science fiction, but now we can barely make it to lunchtime without interacting with it half a dozen times. It tells us what weather to expect before we get dressed in the morning, reminds us about the appointment we almost forgot, and warns us about road closures on our way there. In our personal lives, AI is an ever-present companion, whether we realize it or not. And it’s becoming an increasingly significant part of our professional lives.

For the past 15 years, B2B revenue teams have been generating enormous volumes of data that track the digital transformation of B2B revenue teams. But effective use of that data has, until now, lagged far behind. There are two big reasons for this: First, while most B2B buyers, sellers, and customer interactions are digital, the collection and storage of interaction data have been inconsistent, leaving significant blindspots in the collected data.  

Second, the capabilities required to derive insights and action from the data had yet to be productized and made available for the masses of B2B organizations. AI is changing that—and more—in the revenue technology landscape. That will mean significant advances in what revenue teams can accomplish in the coming year.

1) AI will unlock insights and illuminate blind spots

AI is now making it possible to collect and log nearly every buyer interaction, revealing blind spots and enabling a more complete, high-definition view of the B2B buying process. With this will come new insights about the volume and intensity of buyer interactions, the length of solution research, decision-making processes—and more. Plus, AI is now embedded in various B2B go-to-market tools. That means improved decisioning and insights across everything from content management systems to sales engagement platforms. So all that data they’re collecting? It’s about to get a whole lot more actionable.

2) AI will make emails infinitely more effective

There have been plenty of developments in how revenue teams email their prospects and customers. Even as we’ve seen countless new tools for the deployment of emails, we haven’t seen much tech that makes the emails themselves better. What does “better” mean in terms of email? It’s all about relevance. Relevance is the difference between spam and helpful communication that advances the customer journey. But deploying relevant emails at scale has been more than most teams can manage.  

Email outreach has the potential to be an incredibly effective tool, but it’s often ignored because it’s irrelevant. In some cases, the problem is targeting (i.e., it’s sent to someone who doesn’t care about the message). In other cases, the problem is timing (i.e., it’s sent to the right person, but not at the right time). Organizations have long focused on honing subject lines to grab attention and improve open rates. While the best subject lines may get someone to look, they won’t engage that person if the timing and targeting are off. The best way to improve email response rates is by improving the timing and targeting. AI is poised to help with both. 

In 2022, AI will help revenue teams shift away from generic email cadences delivered to broadly targeted accounts and contacts. Instead, they’ll be able to target much more relevant emails to audiences identified as the right people inside the right organizations and those for whom now is the right time. And they’ll be able to do it at scale—no spam required.

3) AI will make forecasting more sophisticated, accurate, and aligned across the revenue team

In B2B, sales leaders have long been held accountable for their sales forecasts. In recent years, the accuracy of these forecasts has been improved by AI-based data capture and analysis techniques. In 2022, these expectations and the AI-driven capabilities to support them are migrating up the funnel to the first forecast—the pipeline creation forecast. Applying the same forecasting techniques to the top of funnel marketing interaction data, marketers will be able to plan and forecast pipeline creation, enabling even better longer-term revenue forecasts. 

AI will take the guesswork out of pipeline prediction for CMOs, which will help them future-proof bookings and work more collaboratively with their counterparts in sales. 

AI and the Future of Revenue Technology 

In the next five years, the world will create more than twice the amount of data created since the dawn of digital storage.  

As data becomes exponentially more prolific and available, the challenge and the opportunity for B2B revenue technology teams will be to turn all these terabytes of data into a strategic advantage that will give them a leg up on the competition. AI is the key to making that happen. AI is already delivering benefits in terms of optimization, insights, cost efficiency, and more. But in the coming year, forward-looking B2B marketers and sellers will take advantage of solutions that take AI to the next level—and accelerate returns across the whole organization.

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