For the past few years, when the sales industry discusses sales technology trends, artificial intelligence (AI) rises to the top, although it has yet to take a foothold in the industry. In fact, the topic inspires confusion and hesitation across the marketplace, with concerns ranging from AI taking over jobs to worries about the quality of an organisation’s data.
These concerns may explain why the industry has shown so much reluctance to embrace AI. The 2nd Annual Sales Operations and Technology Study from Miller Heiman Group found that just more than 5% of sales organisations deploy AI with their sales technology stack, and the majority—66.2% of sales organisations—have not used the technology at all.
But fear not: AI offers quite powerful opportunities for those sales organisations ready to invest in it. Read on to understand the top scenarios where AI can make a significant impact on sales success.
Four Areas to Use AI in Your Sales Technology Stack
To start, many sales organisations struggle to define and understand AI. We define it as technologies that process massive amounts of structured and unstructured data to develop actionable insights, then self-modify their underlying algorithms based on data inputs and results.
The other key to understanding how AI works best in sales is to think of it not as robots taking over jobs or functions but as tools that can augment sales intelligence, improve planning and performance and reduce repetitive tasks to open up selling time. We asked survey respondents to share the most common use cases for AI. Here’s what they told us:
- Lead Generation and Prospecting More than half of respondents to the 2nd Annual Sales Operations and Technology Survey cited lead generation and prospecting as a priority use case for AI. By combining the intuition of salespeople with a comprehensive, accurate dataset on their activity, AI can assist sellers by bringing them automated account intelligence and lead scoring.
- Sales Performance and Planning Another area where AI can assist is in sales performance and sales planning tasks like forecasting, territory management and compensation planning. Again, implementing AI to improve these processes requires a strategic approach to data strategy, open communication and executive support. But for those orgs that invest in the right tools, this can free up significant time and boost results.
- Sales Enablement In our annual Sales Enablement Study, we saw that adoption of sales enablement has plateaued, with 61% of sales organisations indicating they had some type of formal sales enablement. Yet many organisations struggle with meeting seller expectations for sales enablement and implementing formal programmes to provide coaching, training and content that sellers need to move forward. AI can assist in training, content management and coaching and bring up both quota attainment and win rates.
- Sales Cycle Management Although fewer than 40% of sales operations leaders indicated this as a leading use case, it can play a pivotal role in improving sales success. AI can use CRM data to advise sellers on the activities they need to take to move a deal faster through the pipeline, shortening sales cycles and helping sellers better plan account management. Tools like Scout, Miller Heiman Group’s predictive analytics platform, use a sales organisation’s own data to guide seller behaviour toward stronger, shorter sales cycles that drive more business.
An important sales operations best practice is to clearly define the use case for investing in AI. Too often, sales operations leaders feel pressure to explore new sales technologies like AI because of pressure from executives without understanding how the technology advances business goals or frees up seller time. It’s also critical that sales operations leaders invest in a strong data strategy to ensure they have not just underlying data but a clear data strategy to power these tools.
The sales organisations that get the investment right can see powerful performance improvements from an investment in AI. The 2019 World-Class Sales Practices Study named that having a strong data strategy as one of its top 12 sales practices, meaning it correlates strongly with sales success. AI can also free up a seller’s time from administrative tasks, something critical in a world where sellers only spend about one-third of their time selling.
Want to learn more about how sales operations can lead the way to a stronger data strategy and implementing AI successfully? Download the 2nd Annual Sales Operations and Technology Study.