The consumerization of B2B is well underway. Eighty-two percent of business buyers want B2B sellers to provide the same personalized and relevant experiences they receive when buying for themselves. Keeping...
The consumerization of B2B is well underway. Eighty-two percent of business buyers want B2B sellers to provide the same personalized and relevant experiences they receive when buying for themselves.
Keeping up with these slick B2C-like experiences means that change is coming to the way you go to market.
We’ve already explored how this revolution is impacting the makeup of your revenue team. It’s also transforming the technology your team relies upon to run successful revenue programs.
At the center of this shift is a migration away from sales and marketing automation software toward AI-powered platforms.
So why doesn’t automation cut it anymore? And how can AI fast-track your journey to becoming a winning revenue team? Let’s take a look.
The exodus from automation to AI began with big data.
These days, buyers conduct nearly all of their research long before they ever visit a vendor website or speak with a salesperson. And they’re conducting this research using channels that sellers have historically been unable to track (such as blogs, trade publications, SaaS review sites, social media, etc.). This invisible “digital breadcrumb trail” lives in what we call the Dark Funnel™.
But platforms (like 6sense) use technologies that capture, de-anonymize, and analyze these intent signals, helping identify which accounts are most likely to buy … and therefore which to prioritize time and resources.
To be effective, however, these technologies must sift through thousands — sometimes millions — of data points to make their highly relevant deductions.
Traditional rules-based sales and marketing weren’t designed for this data-abundant world. They can’t handle the quantities of data it takes to offer great B2B experiences at scale.
Most automation relies on software moving data from one place to another. In contrast, AI thrives on big data to provide precise insights and actions. Rather than simply moving data, AI understands and uses it — learning, predicting, and recommending what action to take next.
It’s this intelligence that has made AI the go-to technology for growing revenue teams.
But don’t cancel your automation subscription just yet. It still has a place in your go-to-market playbook.
It saves your team time, labor, and money by doing the straightforward tasks you don’t want to perform over and over. Not to mention potential cost savings of 40% to 75%.
Automation works well for tactical tasks such as your nurture programs and newsletters. But when it comes to the strategic elements of modern marketing programs, it’s no longer smart enough.
Because, like the MQL before them, Marketing Automation Platforms (MAPs) haven’t kept up with the times. They were designed for linear, one-size-fits-all customer journeys. That’s not how customers buy today, with 10 or more stakeholders on buying teams, and countless paths to purchase.
And this is reflected in the data. 50% of organizations report that their MAP’s lead scoring capabilities do not accurately surface the best leads. And only 40% report their MAP’s journey mapping capabilities are effective in helping them create engaging customer journeys.
The reality is you can’t rely on automation to identify and reach your buyers today. For that you need AI.
Seventy-nine percent of marketing and sales teams have achieved year-on-year revenue growth thanks to AI adoption. But it’s not as simple as plugging in an AI platform and “hey presto, more revenue!”
Because AI depends on data to work its magic.
To make the most of AI, you need a complete data set which includes historical data points, not just recent interactions. Healthy data sets are also accessible and organized. This means you have to look after your data by continually cleansing, de-duplicating, and merging it.
All of this means your customer data platform (CDP) plays an essential role in laying the foundation for AI. (We’ve written more about this here.)
Once your data’s in order, AI can start creating remarkable customer-first experiences.
From identifying business to winning deals and maximizing revenue, AI plays its part across the customer journey. Here are three ways you can put it to work:
One in three account-driven organizations fail to align on targeting the right accounts. Rather than playing target account bingo, align your revenue team by using data and AI for your segmentation and targeting.
AI can find in-market accounts (aka accounts that are ready to buy right now) and prioritize target accounts based on factors such as anonymous intent activity, ICP fit, and current buying stage.
This empowers you to focus on the right accounts and personas to drive higher conversions using AI-powered behavioral and fit scores.
On average, sales and marketing teams that engage accounts at the best times in their journey experience a 120% improvement in revenue generation.
AI helps you drive this timely engagement. It powers suggested actions based on where accounts are in their buyer journey. That way, your team knows which action to take —- and when’s best to do it —- for maximum engagement with your customer.
Eighty-four percent of customers say being treated like an individual is key to winning their business.
AI takes all the intent data your buyers unwittingly leave behind as they conduct product research and uses it to personalize the customer journey. Instead of relying on broad segmentation and basic personalization, AI lets you target customers at a more granular level.
You can then use personalization at key moments across your customer journey, such as personalized web experiences, content hubs, and chatbots.
AI isn’t some futuristic concept, or a tool reserved for tech giants like Amazon, Facebook, and Netflix.
By leveraging big data from all over your organization and making it actionable, AI helps you predict, prioritize, and proactively prime customers for conversation and conversion.
With results including 2x higher average deal value, a 10% better win rate, and a 25% reduction in cycle time, winning teams are already using AI to take their revenue programs to another level.
Read our Business Impact Framework to see the impact an AI-powered revenue platform could have on your business.