Author: William Vorhies
Summary: Sales is supposed to be an area that is more immune to replacement by AI than many others because of the high level of impromptu and improvisational human contact required. That remains true. But AI is showing that it can be a valuable augment to B2B sales and some early adopters are scoring big gains.
It will come as no surprise that AI works best where there is a great deal of available data to train and analyze. In the world of sales, the most data is available in B2C selling. Ecommerce and interaction with retail customers via email, phone, web, and text generates the huge volumes of data that makes AI a slam dunk tool for improving these channels.
But what about B2B? Almost by definition B2B involves a sales person face-to-face with a prospect and the limitations of physical presence keep these most important of interactions to a fairly low frequency and limiting available data. Not to mention that we are relying on the rep to accurately and sufficiently enter the details of the call in your CRM.
While the very nature of B2B sales seems to limit the volume of data and therefore work against applying AI, there are any number of ways that AI is being applied to improve this most fundamental sales process.
Not All B2Bs Sales Processes are the Same
As you consider the capabilities and product categories of B2B-AI it will be important to keep in mind the very wide differences that exist among B2B business models. We’ll try here to nail down the two extreme ends of the spectrum and provide one useful reference model in the middle:
This isn’t meant to be extensive nor to pigeon hole your business model into one of these three, but rather to help you think about the characteristics of your sales process and how AI may or may not work for you.
Spoiler alert. The closer you are to the left or at least the middle, the more opportunities for AI to improve your sales process. The reason should be obvious, to the left and center there is more data that can be captured and analyzed.
The core issue is that reps don’t see your CRM as a tool to help them do their job, and more as record keeping. The overall objective of B2B AI is to leverage that CRM data and more to become a true sales helper.
In the sections below, we’ll provide descriptions of the major categories of AI applications that are available and their benefits and constraints. We’ll also mention some vendor names for each category. These are meant as examples and not necessarily recommendations.
Keeping Your Sales Team Up to Date with Facts
Different sources report that 60% of buyers prefer to get their information about your product or service on line, and NOT from your sales rep. Leaving aside the psychological dynamic of this preference, it means that when contact does occur your prospect expects your rep to be fully up to date on their industry, organization, and probably the relationships of decision makers within the buyer organization.
Forrester calls this the move from ‘always be selling’ to ‘always be prepared’.
Providing information without context to the buyer’s specific situation is a non-starter. And tasking sales reps with doing this research themselves is minimally productive time at best. So consolidating information about prospects, industries, and individual decision makers is both important and something AI search is well prepared to do.
Sources should include not only standard industry references but also breaking news, and information culled from social media, sources like LinkedIn, and internal sources including your CRM and even prior email exchanges. Sample providers include dataminr.com and Crystal Knows which will also provide personality profiles and personality-driven email templates to improve the quality of communication.
You can also cooperate in data collectives like the one run by Collective[i]. They use data from anonymized organization similar to yours to identify correct influencers and decision makers, and use AI to recommend next best activities.
Eliminating Other Low Value Sales Tasks
It’s common wisdom that a great deal of available sales time is lost to repetitive lower value tasks and there are a number of providers who have moved to fill this space.
In environments where many face-to-face or even screen-to-screen meetings take place, there is the automated personal sales assistant. X.ai and Clara Labs will schedule meetings between sellers and buyers eliminating the need for attention to the back and forth messages inevitable in negotiating mutually convenient times. Conversica goes a step further to automate routine business conversations with a human touch and handle basic requests for scheduling, information, and the like.
Recording Conversations and Mining for Insight
One of the most popular areas in B2B AI bridges the low value activity of making detailed notes in your CRM with mining those notes for intent and next best steps.
Gong.io, TalkIQ, and Chorus.ai are just a few of the vendors using advanced NLP to automatically record and transcribe phone conversations with customers in your CRM for analysis. Some like Chorus.ai go further, breaking down a call into 5 minute segments and creating a summary focusing on actionable items.
Other providers take the next step of developing personality profiles of prospects based on their spoken and written record to match them to your internal sales reps with personalities most likely to mesh and result in sales.
If you are on the far right in our B2B sales continuum and most of your important conversations occur only face-to-face then you won’t be able to benefit from this automatic capture. But if your reps spend a significant portion of the effort in phone conversation, this can save time and improve results.
If you are in a B2B environment that generates quantities of leads you know that qualifying those leads can be a huge time sink. Filling that void are a variety of vendors like Conversica, a customized online persona that automatically contacts, engages, nurtures, qualifies, and follows up with leads via natural, two-way email conversations until the lead converts into an opportunity.
Follow up is faster and no lead is ever dropped until the sales rep directs. The system will separate the visitors from those that are truly prospects.
Infer.com analyzes sales and revenue data along with sales activity to predictively score leads by quality. ZipRecruiter reports very substantial improvements in deal size from this tool, according to Forrester.
Other providers are using AI to score leads so that reps are guided to pay attention to those perceived most valuable.
Selling and Closing Strategies
One of the most advanced applications of B2B AI are vendors providing a horizontal view of each in-process sale and advising on a variety of selling strategies. They come at the issue from slightly different directions and with different levels of integration.
The granddaddy of this group is Salesforce Opportunity Insights Einstein that uses AI to identify sales patterns, anomalies, and risks. The output is recommended steps to get the sales back on track. Salesforce consulting partner Silverline focuses on identifying overlooked opportunities.
Nudge is principally a platform to provide up to date information at both the individual and account level by aggregating data from the web, your CRM, and other internal sources. Its value add is showing sales teams who has best access to decision makers at a particular account.
People.ai collects sales activity information to identify slack deals, and then creates an activity-based success roadmap to focus on best opportunities. People.ai also claims to establish a behavioral analytics solution which determines which sales rep’s behavior is most likely going to close a deal.
PersistIQ uses AI to analyze sales activity effectiveness and provides suggestions to sales reps to help them tailor their work. It automatically clones successful workflows and refines the sales process to lead reps to success.
TalkIQ integrates with phone systems to analyze phone conversations between sales pros, customers, and prospects. It identifies key differences in approaches that directly affect success and assesses the effectiveness of sales tactics on sales KPIs.
The B2B AI field is still relatively fragmented. None of the major rating organizations is yet reviewing vendors in a comprehensive manner although Forrester took the first step with its report “How AI Will Transform Sales”, which focuses on B2B.
Expect rapid consolidation in this field and the emergence of platforms that provide most of these services in a single vehicle. Until then, evaluate where you are on the B2B sales continuum and begin to explore which of these capabilities would improve your sales success.
About the author: Bill Vorhies is Editorial Director for Data Science Central and has practiced as a data scientist since 2001. He can be reached at: