With AI-powered guided selling, reps get real-time insights and guidance on their sales process based on machine learning (ML), natural language processing (NLP), buyer engagement, content relevance, and personal insights.
Gartner first announced the rise of algorithmic-guided selling in 2019. As AI and ML have matured over the past few years, this is finally becoming a reality today. What is the impact of AI-powered guided selling on revenue enablement as we know it?
Forrester’s Winter 2022 Sales Survey revealed that reps ranked sales playbooks as one of the least effective methods of learning – despite their widespread use. Their success has been limited for the following reasons:
An effective way to improve seller enablement is to replace bulky and rarely used playbooks with contextual and dynamic AI-guided sales plays.
Gartner predicts that “75% of B2B sales organizations will augment traditional sales playbooks with AI-guided selling solutions by 2025.” Due to the low adoption of sales playbooks, revenue leaders and enablement teams are embracing AI-driven guided selling to help reps respond to buyer questions promptly, identify the right actions to move a deal forward, and provide best practices and insights in real time.
Reps can use AI-powered guided selling to accelerate deals, conduct pre-call research, address objections, ensure CRM hygiene, and share the right information. Here are five ways AI-guided selling can benefit revenue organizations:
1. Next best actions. During a long sales cycle, reps may forget specific opportunity details. AI-driven guided selling can summarize the entire history and suggest specific actions to advance the deal. Next best actions can include:
Unlike sales playbooks, next best actions are personalized and data driven. They not only increase rep performance and productivity, but also improve the quality and consistency of sales execution.
2. Call preparation. Most sellers lack the time to prepare systematically for sales calls. A number of factors contribute to this, including time constraints, difficulty locating information, and knowledge gaps.
Imagine that, 30 minutes before a sales call, an AI assistant suggests the five most critical pieces of information a rep should know. By analyzing the context of the deal and reviewing the entire sales library, the AI assistant can deliver valuable information to boost rep performance.
Recommendations may include customer evidence, competitive insights, product knowledge, and FAQs. As a result, reps would have greater confidence going into calls – resulting in a more compelling buying experience.
3. Buyer objections. Objections can be about your solutions, competition, pricing, or case studies. Additionally, buyers may have questions on integrations, security certifications, implementation processes, and support services.
A significant part of your rep’s time is spent handling buyer objections. Reps who are unable to handle a buyer objection must wait for their colleagues to respond or waste time searching their content library.
AI-powered guided selling can read an email thread and automatically respond to buyer objections. It can help a rep answer questions during a live interaction by reading the call transcript. By responding more quickly and accurately, reps can increase buyer confidence and speed up sales velocity.
4. CRM hygiene. Keeping your CRM up to date is crucial to accurate pipeline visibility and revenue forecasting. AI-driven guided selling can automatically update a rep’s open opportunities and provide pipeline health reports to improve deal performance.
Reps can spend less time updating their CRM records and more time closing deals. Managers and sales leaders can rely on CRM data to inspect deals, coach reps, and create revenue projections.
5. Recommend right information. Using signals from the deal context, buyer engagement, and appropriate content in your sales library, AI-driven guided selling can help reps share the right content to revive a stalled opportunity or propel a deal forward.
AI can analyze prior content a buyer has engaged with, identify the right content to share at a particular sales stage, and assess deal context before recommending specific content. As a result, reps will be seen as trusted advisors who understand prospects’ challenges and provide valuable information that can help them make informed purchase decisions.
According to Gartner, by 2026, 65% of B2B sales organizations will move from intuition-based to data-driven decision making, using technology that integrates workflow, data, and analytics. AI-powered guided selling will accelerate data fluency across revenue organizations and make it easier for them to keep up with empowered buyers.
Chandramani (Mani) Tiwary is a co-founder of GTM Buddy, where he leads the AI efforts for building a just-in-time sales enablement platform. Before GTM Buddy, he was a founding member of the data science team at Gainsight.