AI in b2b Sales: WHat you need to know
AI 101: The basics of Artificial Intelligence
Early adopters of artificial intelligence, for B2B sales, are already reaping benefits. By collecting and rapidly analyzing vast quantities of data related to pipeline velocity and sales rep performance, AI can deliver insights into what deals to focus on, how and when to support reps, influence sales training and improve forecasting – all in real time.
Can Artificial Intelligence Solve All of Your B2B Sales Problems?
Artificial intelligence has great potential, especially in B2B sales, but it’s not a silver bullet. It certainly won’t replace your sales team anytime soon. In fact, AI is best used in laser-focused ways to analyze data and extrapolate information well beyond human capacity. Yet human decision-making must still play a significant role to define organizational goals.
AI in the sales context should be used to augment the sales teams decision-making ability, rather than replacing it entirely. Augmented Intelligence provides comprehensive insight and analysis that:
Incorporates human-AI decision making customized to an organization’s specific needs
Provides targeted insights that sales leaders need to drive towards performance goals
Improves accuracy for complete and transparent forecasting, coaching and training
The universal truth of sales.
Buyer engagement is the only predictor of conversion throughout the entire buyer experience. Why is measuring the buyer’s engagement a better predictor of a sale or conversion point than measuring strictly sales activities? Because responses or reactions to stimuli are intrinsic to the person and generally cannot be faked or misinterpreted. Either there is a reaction, positive or negative, or there is none.
Many AI vendors have taken a data-focused, predictive approach (or in other words only look at historical data tracking the sellers activities).
The problem with operationalizing a solution based on the requirement of cleansed and enriched data is, quite simply, the cost: 6+ months of incentivized or mandated CRM adoption, resources to develop and regulate sales process, time spent operationalizing methods with no insight into effectiveness, selling time lost due to unexposed inefficiencies, or the cost of ineffective and/or non-integration selling tools.
Additionally, the model needs to be trained to support every conversion point in order to get the value of the prediction. So put simply, our sole focus is not the action of the seller – we include the reaction of the buying team. This provides insight into your most effective sales plays and the deals most likely to close without requiring a full history of cleaned data.
The buyer engagement approach is a much more complicated avenue; however, we felt it was worth the 4-year investment. Even buyer engagement by itself is not the end game, you must:
Real Solutions for Real Problems
VP of Sales
Further reading on Sales Ops from SiriusDecisions:
Find out how these companies have enabled their sales teams to sell smarter, better, and faster using Accent’s solutions.
INCREASE IN OPPORTUNITY CONTACTS
“The only thing I would change about the CRMSupercharger rollout is that I would’ve done it sooner.”
Director of Sales Enablement, CDK Global
INCREASE IN SALES PRODUCTIVITY
“Best sales enablement platform in the industry for our needs.”
Sales Enablement Manager, Analog Devices
FASTER REP RESPONSE RATE
“Accent has allowed our organization to more easily manage our repeatable and predictable tasks, allowing the team to focus more of their time on high impact, value-add initiatives.”
Marketing Manager, Columbia Threadneedle
5 Key Components of Sales Transformation
Every organization wants to generate more sales revenue, but getting there isn’t always simple. At Accent Technologies, we have identified 5 key components that lead to sales success.
Platform Data Enrichment
Sales reps don’t like to spend time entering data into their CRM. It takes away from actual selling time. Automatically capture rep activities and map to them to opportunities with greater accuracy.
Only 24.9% of participants in a CSO Insights survey expressed high confidence in the quality of the data in their CRM system.
High-performing sales teams are 1.5 times more likely to base forecasts on data-driven insights.
Visibility into sales activities
Having a complete and accurate data set within the CRM gives sales leaders a complete understanding of opportunities throughout every stage of the sales cycle.
Actionable sales analytics
Visibility is great, but managers don’t have time to sift through raw data. Artificial intelligence should refine this data and make it actionable. This analysis lets reps and managers alike know if efforts are effective.
44% of sales organizations list increasing sales effectiveness as a top sales objective.
80% of high-performing sales teams rate their sales training process as outstanding or very good.
Insight into coaching & skill development
Visibility into sales reps’ effectiveness gives sales leaders a better understanding of which reps need additional training and in what phase of the sales cycle. Sales leaders are able to accurately pinpoint where they need to spend time to improve sales effectiveness and ultimately, close rates.
More sales revenue
Targeted coaching means that sales reps can increase their performance dramatically. By maximizing sales performance across the sales team, organizations will be able to realize increased sales revenue.
Firms that provide an optimal amount of coaching realize 16.7 percent greater annual revenue growth.
SALES MANAGEMENT ASSOCIATION
AI for Platform Data Enrichment
One of the biggest problems in Sales Analytics of any kind is a lack of data from which sales leaders can extract insight. CRM systems, for example, are usually sparse and incomplete, and that makes it nearly impossible for any human or machine to draw conclusions. In the past, data integrity across an organization often came at a substantial cost—it required heavy training, strict governance policies, and constant cleansing and refinement.
AI for Executing Sales Strategy
Traditionally, organizations have formulated and operationalized sales strategies through a top-down approach. In this context, sales leaders have evaluated their Sales related Business Intelligence (reporting dashboards, market research, etc.) with their stakeholder peers, synthesized their strategy’s blueprint, and done their best to communicate that plan down the chain of command all the way to the front line. The problem is that humans, and specifically sales reps, are creatures of habit. Until these reps have support from the bottom-up to execute that change in strategy, the organization will struggle to pivot.
AI for Evaluating Sales Strategy Execution
In the past, Sales Performance management has been centered around Sales rep compensation plans. Inherently, this meant the focal point of SPM solutions were financial results—quota attainment, total revenue generation, etc.– and how those results translated to OTE earnings. While results maintain their importance in the present landscape, technological advancements have made it practical to begin evaluating sales performance from different angles.