Sales enablement drives many key functions in a B2B sales cycle. From helping reps master sales tools to collecting customer insights, sales enablement supports building a frictionless buying experience.
But there’s a downside.
Traditional sales enablement processes involve very hands-on, manual tasks. Luckily, AI is changing this dynamic and making sales enablement less cumbersome.
This article will discuss leveraging AI in sales enablement with practical tips and insights for a smart investment.
Seismic’s 2023 Value of Enablement Report shows that 99% of surveyed 1200 modern teams believe sales enablement techniques and tools made their jobs easier.
Here are a few reasons for this high acceptance rate:
Traditionally, sales enablement processes ran on generic, one-size-fits-all strategies. Brands relied on limited customization and expected every sales rep to learn at the same pace, irrespective of their strengths and weaknesses.
Also, the B2B buying behavior has transitioned drastically. For example, buyers today expect branded content to meet their unique preferences, thus requiring a more insight-driven enablement strategy.
And with AI stepping in, the sales environment is slowly undergoing transformation throughout its processes.
Here are a few benefits of AI-led sales enablement:
Sales teams are overburdened with routine, time-consuming tasks, such as drafting and sending documents, creating custom outreach messaging, scheduling calls, curating sales forecast reports, and more.
But with intelligent AI tools, these tasks are easily handled, saving a large portion of the sales team’s time to spend on more strategic activities rather than menial work.
For example, your sales reps could use a LinkedIn-based AI tool to co-pilot outreach activities, such as researching prospects and writing personalized LinkedIn connection requests at scale.
Multiple studies point out that it takes about 300+ days to train a new sales rep, making training and onboarding a costly affair in terms of money and effort.
This can be changed with smoother onboarding and strategic training with AI.
AI tools are trained to understand, transcribe, record, and analyze sales calls and customer interactions. They can help sales managers identify strategies based on individual sales rep’s strengths and weaknesses. This information can be used to develop better onboarding and training programs and let sales reps be their productive best in no time.
For example, AI tools can analyze conversations to identify customers’ frequent pain points. Next, the tools can guide sales reps in curating a custom product demo to address those pain points.
Delivering relevant content to prospects and customers during sales conversations is essential for a smooth sales pipeline.
Additionally, on-time responses to customer queries cut down the otherwise long sales cycle. Generative AI tools play a significant role in improving customer engagement and moving prospects quickly down the conversion funnel.
For example, a Generative AI tool like Docket acts like your team’s virtual sales assistant by learning from your data and delivering real-time assistance via conversational chat. It can help with quicker sales rep onboarding, accelerating RFP/RFI creation, and timely Q&A assistance.
Unlike humans, AI can analyze huge amounts of data in less time. The analysis reveals key trends and patterns that sales managers can use to improve their overall sales enablement strategy, optimize sales tactics, and improve marketing efforts.
For example, some AI sales tools track the kind of content buyers engage with the most and offer GTM teams actionable insights into what content they must concentrate on to improve sales process efficiency.
Curious about the exact application of AI in sales enablement? Here’s a look into some core concepts in AI for sales enablement and how they benefit your sales workflows:
Machine learning (ML) is a branch of AI typically trained on data and algorithms to make accurate predictions and decisions. Its most noteworthy capability is imitating human behaviors, such as interacting with customers, sales forecasting, identifying trends, and more.
Machine learning in sales enablement can be a part of tools like:
Generative AI is a type of AI that can create new text, images, visuals, video, code, and a few other elements based on the data it’s trained on.
From the sales enablement perspective, Generative AI is of utmost help in personalizing content across sales processes, such as outreach, presentations, calls, document generation, etc.
For example, sales teams can use a Generative AI tool to help auto-draft sales proposals or outreach messages and generate follow-up emails based on each prospect’s preferences and unique use case.
This is another key AI concept that involves analyzing sales conversations, such as messages and calls, to identify objections, trends, and other key moments.
AI-led conversation intelligence tools can:
For example, conversation intelligence AI tools can analyze recorded sales calls and identify coaching opportunities to improve sales reps' performance.
NLP is an AI subset that helps systems interpret human language and communicate effectively.
Sales enablement tools running on NLP can identify buyer intent and assist sales teams in recognizing the emotions behind customer or prospect actions.
For example, some AI tools use NLP-led sentiment analysis to interpret customer opinions about a brand’s products or services. NLP for voice search is another great application where sales reps can use voice commands to find answers to customer queries.
AI-powered sales enablement can have five components:
Sales analytics helps gather in-depth data-driven insights, identify roadblocks and improvement areas, and boost team productivity.
For example, an AI algorithm trained on real customer data identifies the common path prospects take before making a purchase and highlights it to sales reps. Insights can also include prospects’ frequent or most active touchpoints like email or call, and the time taken at each stage.
Sales analytics and insights tools can include:
AI-powered tools guide smoother onboarding and pinpoint training opportunities by analyzing sales calls and tracking sales rep performance.
AI can be used for coaching and training to:
A predictive lead scoring model assigns a numerical score to each lead based on their likelihood of conversion. The score is calculated based on historical and real-time data.
For example, AI lead scoring tools calculate a score by analyzing the lead’s behavioral and engagement patterns with the sales or support teams and indicate if they are pursuable.
No two prospects or customers are the same. So, the best way to improve engagement and conversions is to use AI to analyze customer data and provide hyper-personalized experiences via content, such as:
Integrating a sales enablement tool with your internal CRM software makes way for improved recommendations, insights, and AI-assisted tasks like automated outreach and proposal creation.
Since customer data is prone to constant changes, CRM’s integration with AI tools lets you manage data better, as AI can enrich it from time to time. For example, enriching customer profiles by tracking their job changes on LinkedIn and re-engaging with them based on this change.
Considering the many components of AI in sales enablement, it’s natural for you to be confused about adopting AI into your workflows.
Since the ultimate goal of sales enablement is speeding up your sales reps’ work and making them productive, we suggest you choose a conversation intelligence and sales assistance AI tool like Docket.
Docket makes critical information accessible to your sales and GTM teams in real-time. They can be brought up to speed in under a few hours and help move prospects rapidly toward conversion.