AI and Machine Learning in B2B Sales

Tracey Halvorsen
Oct 12, 2020 · 5 min read

Most complex B2B deals take months or years to close. Along with every point in that pathway, there are human beings interacting. There are literally hundreds of thousands of micro-conversions happening within one large-scale B2B sales engagement.

These are the realities.

Once the bastion of in-person interactions, B2B engagements must now occur almost exclusively as virtual exchanges even though they’re still primarily 1-to-1 communications between buyers and sellers. They may be using technology to connect, and share information digitally via that technology — but it’s still the transference of information (issues and solutions, questions and answers, plans, and revised plans) back and forth between humans that make up the logistics of the path. And even when the necessity to work remotely (thanks to the Covid-19 pandemic) fades, we will likely see many of these interactions remain virtual and digital.

Machine learning and artificial intelligence systems are limited based on the data and statistics they are able to gather, and what value they have been predisposed to assign to each data point. On social media platforms, for example, the “user” is the product, and the data feeds amazingly complex algorithms that decide what to serve up next to give that user. However, in most businesses, we aren’t able to mine the prospective buyer or client because they aren’t spending hours a day engaging with us or our content or services. Yet there are factors that make a difference in winning or losing a deal, and these are things we definitely need to be gathering, analyzing, and feeding into our systems.

Most businesses need to know, “What was the magic combination of ingredients that led the buyer to ultimately choose that particular seller?”

That’s it. That’s all that matters.

Customers are engaging at specific times and for specific reasons along the buyer journey. And yet — we aren’t capturing that information, or even trying to measure it and use it to get smarter. Traditionally most tracking is happening when they are still leads, doing their own research online in “stealth” mode. Once they become an active prospect, the data and intelligence gathering drop significantly. We enter a black box where the one giant outcome we capture is simply the win or the loss.

The journey itself is never acknowledged in a way that would help the organization get faster, smarter, and begin to produce better outcomes. A CRM might measure the progress of a deal through stages, but the level of engagement happening, with whom on the buyer side, and with what collateral or content being generated and shared — is not often tracked at all. And when it is tracked, it’s often through the lens of marketing rather than sales. Marketing places value on clicks, engagement time, shares, etc. Sales care about what moves the actual needle forward, or not.

Sales is in a race of constant engagement and reaction — and this is where we aren’t using technology as effectively as we could be.

Software today ignores the messy reality that human interactions and collaboration within the organization’s sales teams holds the real valuable data necessary for forming insights, and becoming predictive. Not only that, these human-to-human interactions hold the data necessary for any enterprise sales team to scale effectively and re-use or optimize what has already been created and has performed well.

Just as most CMS systems don’t actually help people create the content, most CRM systems don’t help people evaluate the relationships and what is actually working. While they may measure engagement points like views, clicks, opens, etc. they miss the most critical data points of all — what “worked” in the deal stages?

What converted a lead to a customer — after they turned from a prospect into a lead?

How many phone calls are had between the seller team and buyer team that move the needle, and in what ways? How many custom decks are created and shared to address specific buyer issues? How many project specs, contracts, and planning documents are revised and refined along the final stages of the sales engagement to lock in the deal? And while one team might be aware of these pieces of connected content or communication moving the needle, what about all the other teams facing similar challenges within the company?

There is so much more information we could be gathering and sharing about these interactions, and better work we could be doing around indexing and organizing the connected content that is doing the heavy lifting. With the appropriate systems applied to these problems, businesses could not only optimize their sales processes, they could more effectively scale this effort across the enterprise. Distributed marketing and sales teams would be aware of critical newly-created content or approaches that were having a positive impact in similar opportunities within the business. And rather than reinventing the wheel each time a sales team needed to get something to a potential buyer (creating a huge cost center), or relying on outdated or poorly performing content simply because it’s what they know exists, they could count on intelligent workflows and systems to guide them to exactly what they need, when they need it, to use for a specific buyer situation.

Bain & Company predicts the organizations who thrive in the future are the ones who’ve adapted to the new turbulent reality the best. “As leadership teams dig into the complex process of recovery, one truth is abundantly clear: We cannot afford to go back to the old way of doing things. The companies that most aggressively adapt and extend new ways of operating will turn this crisis to their advantage.”

I believe this is where most SaaS systems that serve enterprise B2B organizations need to be focused. They must provide easy-to-use, powerful tools that leverage the interactions and connected content that actually moves the sales cycle forward, empowering businesses to scale their efforts, measure more efficiently, and close more deals.

Tracey Halvorsen is the Co-Founder and Chief Experience Officer at Return Solutions. Return is a SaaS application for sales enablement and real-time business intelligence. The Return platform empowers enterprises to fully harness the great work that is happening across the organization, allowing them to limit administrative tasks, get smarter and close more deals.

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