Dr. Cindy Gordon covers the report in more detail in this article - Gartner Highlights the Need to Deploy AI-Driven Sales Capabilities to Maximize Every Deal. 2 .
Artificial intelligence (AI)-driven selling is the buy Phone Number List application of machine learning (ML) and natural language processing (NLP) techniques to analyze sales conversations and historical data to generate forecasts and recommendations that can help salespeople and sales leaders. As we noted in a previous blog post, 15 Ways AI Can Help Your Salespeople and Sales Executives, AI can help at every stage of the sales lifecycle, through leads, MQLs, SQLs, deals, and even after a successful close (to upsell).
But when planning to implement AI in your sales process, you should be aware that not all AI implementation projects are successful. 3 . AI projects in sales mostly fail for the following reasons:
Grand ambitions at the beginning
Bad connection
Lack of data
Learning about these reasons for failure can help us avoid these mistakes.
Step 1: Start with Simple Goals
What do you want to achieve with AI – To improve lead conversion? To improve deal win rates? To close deals faster? Or to train sales reps to do better openings or closings?
Keep in mind that unless sales reps benefit from it, the adoption of any new sales technology will be low. So, one of the main goals should be to empower sales reps. AI can help sales reps in many ways, from prioritizing leads to identifying actions to take on a deal, or alerting them to unengaged deals, or suggesting content to include when responding to an email, etc.
Step 2 - Communicate with all stakeholders
AI-driven sales may be met with skepticism by your sales team. We have noticed this in our own sales team. There are two main concerns for salespeople.
Prediction Accuracy : AI gets better with more data. So there are bound to be instances where predictions and recommendations aren’t accurate early on. Set expectations accordingly.
Fear that AI may limit their role : On the contrary, AI increases their success by being an intelligent assistant for them. Communicate to your sales team what you want to achieve by implementing AI-driven selling and how it will help them and the organization.
Step 3: Find a tool that lets you get started with the data you have
AI-powered apps require data to train predictive models. This includes not only the names and sizes of deals won and lost, but also deal touchpoints, associated accounts and contacts, and other similar attributes. This data may not be readily available if you’re starting over.
Tools like Vtiger Calculus can help you get started with limited data and get started on day one with features that don’t require historical data.
For example, your team may benefit from features like Best Time to Contact, Call Analytics, and Coaching Dashboards, Coaching Scorecards out of the box.
Step 4 – Collect feedback in the form of weekly reviews for the first 90 days.
Get feedback from salespeople and sales managers on what features are helping them achieve their goals and what are not. AI engines use different algorithmic data models to make predictions. These models may require some tuning to ensure the accuracy of the predictions and recommendations.
A weekly review will help identify deviations as early as possible and improve the accuracy of the predictions.
By following the suggestions above, you can put your sales team on the right track to take advantage of the benefits provided by AI and improve sales.