21.11.2024

Sales & Revenue

Your guide to combining data and AI in sales enablement

13 min read

Matthew

Explore how AI in sales enablement transforms training and coaching with data-driven insights.

In B2B sales, the highest performing teams and salespeople consistently benefit from personalised training, coaching and feedback. These elements are essential for building skills, overcoming challenges and fostering growth. However, many sales development and training programmes still take a one-size-fits-all approach and focus on the masses rather than the individual.

The reality is that every sales rep faces individual challenges and fears, making personalised coaching a critical factor for sales success in 2025 and beyond. Unfortunately, traditional methods often fall short, leaving sales managers with the time-consuming task of manually assessing performance and providing individualised feedback - an approach that is both inefficient and difficult to scale.

A major change in the industry this year is the increasing use of AI in sales coaching. AI-powered solutions provide the flexibility and precision needed to cater to the needs of each individual team member, alleviating many of the challenges sales leaders face. By using AI, teams can develop smarter and more effective enablement strategies that empower their people to perform at their best.

AI adoption in sales has skyrocketed—with 76% of sales teams increasing their use of AI from 2018 to 2022. Why? Because high-performing teams are 2.8X more likely to use AI to enhance their sales processes.

AI in sales enablement can help organisations to use sales data to deliver personalised, data-driven coaching programs. AI tools can analyse various data points—from call transcripts to CRM activity logs—to provide actionable insights, helping B2B sales teams improve faster and more effectively.

Challenges of traditional sales enablement 

Sales enablement is not just a support function, but a sales accelerator. When done right, it has a direct impact on close rates, pipeline growth and the volume of new deals closed monthly and quarterly. Effective sales enablement equips your team with the right tools, customised training and actionable resources to consistently perform at their best.

Sales enablement is also about continuous optimisation - ensuring that every sales rep at every stage has the skills and insights to effectively approach prospects, overcome objections and close more deals. By focusing on personal development and strategically aligning enablement with your team's goals, sales leaders can achieve measurable performance improvements across the board.

Despite its importance, traditional sales enablement comes with several challenges:

  • Addressing individual weaknesses: One major issue is its inability to personalise coaching for each sales rep. This lack of customisation means many reps do not get the guidance they need to overcome their unique challenges.
  • Time-consuming for managers: Sales managers typically have to spend significant time manually reviewing performance data to provide tailored feedback, which can be an inefficient use of their time.
  • Lack of data-driven insights: Without robust data analysis, it’s hard to identify specific patterns and trends in a rep’s performance, making it challenging to offer actionable, objective feedback.

 

AI delivers personalised, efficient and data-driven training tailored to each salesperson - so they get what they need to succeed, when they need it.

How to use AI in sales enablement

Sales performance data for targeted coaching

One of the key benefits of using AI in sales enablement is the ability to process both structured and unstructured data quickly and accurately.

Structured data, such as CRM metrics and sales performance statistics, provide a clear basis for analysing patterns and trends. Unstructured data such as call logs, email traffic and meeting notes, on the other hand, offer deeper insights into the intricacies of customer interaction and sales rep behaviour.

AI tools can analyse various data sources, such as:

  • Sales call transcripts: AI finds themes and objections by transcribing and analysing sales calls. It can also spot where sales reps struggle or excel.
  • Emails and CRM activity logs: AI reviews emails, follow-ups, and CRM logs. It will assess how reps engage with prospects during the sales cycle.
  • Deal win/loss analysis: By examining what affects deal outcomes, AI finds patterns and best practices for successful sales strategies.
  • Behavioural data: Metrics like response times, touchpoint frequency, and time in sales stages reveals a rep's effectiveness and efficiency.

 

The power of AI in sales enablement is its ability to provide guidance and recommendations to sales reps that would not have been called out and highlighted if it were left to a rep to do a manual review of the data.

With AI, sales enablement moves from a one-size-fits-all approach to a hyper-personalised strategy that allows sales leaders to cater to the individual needs of each rep. Instead of treating all team members the same, AI identifies the specific strengths and weaknesses of individual sales reps and provides actionable insights to improve performance.

For example, one sales rep may excel at initial outreach but struggle to close deals after the proposal stage, while another may excel at closing simple solutions but falter at complex ones. AI analyses patterns in call outcomes, email engagement rates and deal closures to uncover these nuances. Sales leaders then receive customised coaching recommendations - whether to refine contact techniques, improve proposal strategies or boost confidence when selling complex solutions.

This insight allows managers to allocate their time and resources where they can have the greatest impact.

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Instead of just providing static reports, AI offers real-time, actionable feedback to sales reps after each interaction. This dynamic capability ensures that reps receive immediate guidance on how to improve their performance. 

After a sales call, an AI tool might suggest specific training resources, such as objection-handling techniques or role-playing exercises, based on the issues the rep encountered during the call. By leveraging data from similar successful deals, AI can tailor these recommendations to improve future sales interactions.

By using AI in sales enablement, B2B companies can provide more targeted, efficient, and effective coaching, helping sales reps to quickly address their specific challenges and enhance their overall performance.

Use cases of AI in sales enablement

1. Create customised sales training 

One of the biggest advantages of incorporating AI in sales enablement is its ability to create customised learning paths for each individual sales rep.

Rather than relying on one-size-fits-all training programs, AI analyses a rep’s performance data to identify their strengths and weaknesses. Based on this analysis, it can curate a learning path that focuses specifically on areas where the rep needs improvement.

If a rep struggles with overcoming objections during the sales process, the AI prioritises training content that addresses this skill gap, ensuring that the rep receives the right guidance at the right time.

2. Get relevant content at the right time

AI also excels at delivering just-in-time learning, ensuring that sales reps receive the right content exactly when they need it. By analysing a rep’s current pipeline, AI can predict potential challenges and recommend relevant content to help them prepare.

For example, if a rep is entering a critical negotiation stage with a prospect, AI can suggest materials on negotiation tactics or objection-handling strategies to help them close the deal successfully.

This timely delivery of targeted training ensures that reps are always equipped with the tools and knowledge they need to perform at their best.

3. Continuously improve with AI-driven insights

Sales enablement isn’t a one-time effort—it’s an ongoing process.

AI in Sales Enablement supports continuous improvement by constantly analysing performance data and adjusting the training program as needed. As reps advance in their skills, the AI can evolve the learning path to introduce more advanced techniques and challenges, helping to maintain their growth and prevent stagnation.

For instance, a sales rep might start by learning basic objection-handling skills, but as they improve, AI could introduce more advanced strategies for navigating complex objections or handling objections from high-level executives. This ensures that the rep’s training keeps pace with their growing skills.

4. Personalise sales training to drive better results with AI

Imagine a B2B company that implemented an AI-driven sales enablement platform to address gaps in their sales training. The platform analysed sales data and identified that several reps were struggling with closing deals, particularly in the final negotiation stage.

Based on this insight, AI recommended targeted training materials focused on objection-handling and advanced closing techniques. Over the next six months, the team may see a significant improvement in win rates, as reps became more adept at managing objections and closing deals. 

By personalising sales training through AI, companies can ensure that each sales rep receives the right coaching and support, maximising the impact of their enablement efforts.

How AI improves manager efficiency and team wide performance

Sales managers often struggle to balance coaching responsibilities with day-to-day management tasks. AI addresses this challenge by:

  • Reducing the burden of performance analysis: AI tools analyse sales data to provide personalised coaching recommendations. So, instead of manually reviewing calls, emails, or CRM updates, managers receive pre-generated insights. This enables managers to dedicate more time to strategic planning and advanced deal-making.

  • Enhancing feedback with objectivity: AI eliminates subjectivity in performance reviews, offering clear, data-driven insights. Feedback is based on measurable metrics, such as call success rates, deal win/loss patterns and response times. By grounding feedback in facts, AI promotes transparency and accountability while making evaluations more actionable.

  • Supporting team growth with scalable coaching: AI can scale personalised coaching to large sales teams, ensuring every rep gets tailored insights. For example, AI assesses performance, pinpoints skill gaps, and suggests targeted training for improvement. This ensures all team members—whether part of a small or global team—receive consistent, individualised support.

 

For example, a global B2B company can use AI to ensure their growing sales team receives consistent, individualised coaching. AI tools assess performance, identify improvement areas, and recommend specific training—empowering every rep to succeed while reducing managerial workload.

By using AI for performance insights, objective feedback, and scalable coaching, organisations can boost manager efficiency and elevate team wide performance.

Key benefits of AI in sales enablement for B2B companies

AI in sales enablement provides lasting advantages that go beyond short-term gains. Let’s have a look at the key benefits:

  • Individual skill development: Personalised coaching, powered by AI, allows sales reps to focus on their specific weaknesses and improve more efficiently. Instead of generic training programs, reps receive targeted coaching tailored to skills they need, such as objection-handling, closing techniques, or lead qualification.

    For example, a rep struggling to close deals might receive AI-recommended training in negotiation tactics and deal-closing strategies. With consistent, data-driven coaching, they can quickly develop these skills, leading to improved performance and results.

  • Enhanced productivity: AI helps reps work more efficiently by delivering real-time feedback, just-in-time learning, and personalised content recommendations. This preparation ensures reps are ready for every sales interaction, reducing trial and error and shortening the sales cycle.

    For instance, a sales rep using AI-powered coaching spends less time on ineffective strategies and more time focused on high-impact activities, resulting in higher conversion rates and faster deal closures.

  • Team wide performance improvements: AI elevates the entire team’s performance by analysing data to identify trends, best practices, and areas for improvement. These insights can be shared across the team, ensuring consistent performance and targeted support for underperforming reps.

    A team with varying levels of expertise can benefit from AI-powered insights, fostering a collaborative culture where reps share learnings and adopt successful strategies, driving continuous improvement and teamwide success.

  • Managerial efficiency: By automating performance tracking and data analysis, AI allows managers to focus on high-value activities like coaching and strategic planning. Rather than spending hours reviewing CRM logs, managers can use AI insights to pinpoint performance gaps and provide targeted guidance.

    For example, a manager can quickly identify which reps need additional training and dedicate their time to offering support, leaving administrative tasks to AI tools.

With AI-powered sales enablement, B2B companies can cultivate more skilled, productive, and cohesive sales teams. By enabling personalised coaching, improving productivity, and freeing managers to focus on leadership, AI ensures long-term growth and sustained success.

Best practices for implementing AI in sales enablement

1. Survey – build a strong data foundation to assess AI readiness

Before integrating AI into sales enablement, it’s essential to evaluate your current data infrastructure and assess how prepared your organisation is to use AI.

AI tools depend on high-quality, structured data like CRM metrics and unstructured data, such as call transcripts and emails, to deliver accurate insights.

Ensure your CRM and other systems are well-integrated and that your data is accurate and up-to-date. Poor data quality can lead to unreliable outputs and missed opportunities.

Steps to take:

  • Audit your data sources to identify gaps or inconsistencies.
  • Integrate key systems to provide AI with a complete and accurate dataset.
  • Regularly update and clean your data to ensure reliability.

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2. Plan – define clear metrics and goals

To effectively implement AI, start by defining specific goals and metrics that align with your sales priorities. Whether it’s increasing close rates, improving pipeline velocity, or growing quarterly revenue, clear objectives will guide AI deployment and ensure it delivers measurable results.

For example, AI can be used to identify bottlenecks in the sales process, recommend targeted coaching, or provide insights into win/loss trends.

Steps to take:

  • Collaborate with sales leaders to define key performance indicators (KPIs) that matter most to your team.
  • Focus on high-priority use cases to test small-scale AI implementations before scaling up.

3. Activate – implement AI for personalised sales coaching

AI enables a more tailored approach to sales enablement by analysing individual rep performance and providing targeted recommendations. By reviewing structured and unstructured data, such as call outcomes, email responses, and deal conversion rates, AI can identify specific areas where each rep needs support.

For example:

  • One rep might excel in outreach but struggle to close complex deals.
  • Another might perform well with simple solutions but falter when handling multi-stakeholder negotiations.


AI identifies these patterns and helps sales leaders create customised coaching plans to address individual needs.

Steps to take:

  • Use AI insights to develop personalised coaching plans for each rep.
  • Train your team on how to effectively use AI tools to support their development.

4. Realise – support your team through AI adoption

Introducing AI tools requires clear communication and hands-on support to ensure successful adoption. For many teams, AI can simplify tasks like lead scoring or deal forecasting, freeing up time for higher-value activities.

However, it’s important to guide your team in understanding how AI will benefit their day-to-day work.

Steps to take:

  • Provide practical training to show how AI tools improve outcomes like close rates and pipeline management.
  • Host regular sessions to address questions and build confidence in using AI tools effectively.

5. Keep improving – continuously evolve your AI-driven program

AI in sales enablement should be an ongoing process that adapts to changes in team performance and business objectives. Regular reviews of AI-generated insights allow you to refine your strategies and ensure continued relevance.

For example, if AI insights reveal a drop in proposal acceptance rates, you can adjust training or update processes to address the issue promptly.

Steps to take:

  • Schedule periodic reviews of AI outputs to evaluate their effectiveness.
  • Encourage team feedback to refine strategies and identify new areas for improvement.


By continually reviewing and updating your approach, you ensure that AI remains a valuable tool that supports long-term growth and success.

These best practices are based on Huble’s SPARK AI framework, designed to help businesses implement AI in sales enablement effectively. By following the SPARK process, we ensure AI delivers measurable results and drives continuous improvement. Learn more about the SPARK framework here.

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Unlock your sales team’s potential with AI in sales enablement

By using AI to analyse sales performance data, organisations can deliver personalised, data-driven coaching that helps individual reps improve faster and more effectively. This approach solves the usual problems of sales enablement, including a lack of targeted support and time-consuming manual tasks for managers.

The long-term benefits are clear: faster skill development, higher sales productivity, and better team-wide performance. Sales managers also benefit from enhanced efficiency, allowing them to focus on strategic initiatives rather than getting bogged down in administrative tasks.

With AI taking on much of the heavy lifting, sales teams can operate more effectively and consistently, driving better results across the board.

If you’re looking to improve your sales team's performance, explore how AI in sales enablement can help. Contact our team at Huble to learn how our AI-driven solutions can transform your strategies and boost productivity.

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