How to Sell More Effectively With AI Sales Tools

The sales profession is at a turning point. AI sales tools are now mainstream and available to help sellers improve their efficiency by reducing the drudgery of many manual tasks or scaling their efforts. The result of these efficiency gains is that sellers are able to put more time into core selling activities and less into data entry, prospect research, and other actions.

It’s also emerged as a way to help sellers execute key sales activities in a radically more effective way. That means that AI steps in to help sellers get more results from core actions like prospecting emails, discovery calls, objection handling, pipeline management, sales meeting management, and more. The result of this effectiveness boosting is that sellers can move more deals through the funnel to close. 

Let’s take a look at some of the new ways that AI and machine learning in sales have emerged to help sellers boost their efficiency and effectiveness. 

How To Get Started With AI Sales Tools

The foundation for any sales AI is data. If you don’t have a solid basis of information on which the AI can operate — ideally in your CRM with proper CRM data hygiene — you won’t get good results. It’s no different than we humans. If you don’t know anything about a topic like architecture, you’re not likely to build a skyscraper I’d want to be in. That’s why proper sales data capture and regular CRM data cleansing and contact management are critical if you want to take advantage of AI.

So, consider what your goal is for using AI. If you’re looking to increase your win rate and the velocity of your deals, you’ll likely want the AI to evaluate the calls, emails, transcripts, and other communications that you have with your prospects. After all, these engagements are the vehicle through which you advance a deal.

You’ll want your AI to evaluate the sales data, look for correlations between won deals and actual activities, and then identify the actions to take to move deals forward. When the AI is trained on your data, it’ll be much more effective. 

‍To Make AI More Effective, Tune it to Your Business

In addition to having great data to work with, it’s important that AI sales tools are tuned to your own business. If it’s not, you’re likely to get generic recommendations that won’t set you apart from your competitors. Or, it will simply be unusable because the AI is not familiar with your terminology and processes. Or, it won’t have context for what’s effective in your sales organization. Without that context, it can’t make suggestions on what “good” looks like. That’s why just using ChatGPT for sales or sales chatbots, without further tuning, is limited.

Tuning AI sales tools to suit your business needs means having an AI that is at home with what you call “middle of funnel”, or what prospect roles are the right ones to speak to, or whether you use MEDDIC, MEDDICC, MEDDPICC, or BANT. A properly tuned AI is going to be more useful to your organization. 

What are Use Cases for AI in sales?

There are so many different use cases available for sellers to leverage AI. In fact, that’s one of the challenges: how to decide on how to focus your AI strategy to maximize impact on your sales goal attainment. 

We’ve collected a set of the most common use cases we see for using AI in sales organizations. 

MEDDICC Deal Analysis and Other Methodologies

Sales methodologies and frameworks are helpful approaches that allow sellers and leaders to standardize deal analysis. They aren’t typically intended to be a checklist – that is, don’t walk into a sales call and start asking your prospect for each part of the framework! But rather they help a seller to think critically about what’s missing in their opportunities. And what can be done to advance them.

Common methodologies like MEDDICC, MEDDPICC, BANT, Sandler, and others have a structured approach to analyzing deals, which ultimately helps with sales pipeline analysis. Sellers can walk through the metrics associated with a buyer’s pain, who the economic buyer is, what the decision criteria are, etc. to fulfill the requirements of MEDDICC. 

The challenge, however, is that the key elements of these deal analyses are pulled from across many engagements. In even a modestly complex deal you might have dozens of emails, calls, and calendar invites across multiple stakeholders and teams. 

AI can be a boon to sellers here by assessing all of these various interactions, uncovering key insights into your deals, and grouping the information into the framework’s structure. AI excels here because of the siloed and unstructured nature of the activity data that’s being collected.

This is also a big benefit for managers. A challenge with using these kinds of frameworks is that, despite training, each rep will apply the methodologies differently. With AI, you can ensure that the completion of each, for example, MEDDICC analysis will be done in the same way for every rep and every deal.

‍How AI Sales Tools Can Summarize Calls

One of AI’s super powers is the ability to summarize large amounts of text. Sales calls are a great candidate for this functionality because they can be readily transcribed by tools like Zoom, Chorus, or Gong. And then those transcriptions can be consumed by AI to provide sellers with a summary and analysis of a call. 

Summarizing individual calls is a big win. But think about the last few sales calls that you’ve been on. Odds are these calls weren’t held in a vacuum. Rather, they were in the context of lots of emails and calls that happened beforehand. 

AI can help here too by digesting all of these previous sales situations and then providing a more holistic assessment of the most recent call. So, when the prospect mentioned they need to go through a security review, the AI summary should recognize that there already was an email communication between the sales rep and the security review team the day before, for example. 

AI will be able to return interesting insights like who was on the call, what was said and by whom. What the key objections and motivations are and much more.

How AI Can Help Sellers Prepare for Prospect Meetings

If your team is like most sales organizations, they are overwhelmed by the volume of meetings. Many of these meetings are the kinds you really want to have: with prospects, partners, and customers. Some are the kinds of meetings that help your sales organization to be more effective, like quarterly business reviews, sales pipeline calls, and board meetings.

For each of these meetings, you want your team to be ready with insight into what’s happening in each deal. For prospect meetings, that means knowing what objections exist for each prospect and what the best next steps are to keep the deal moving forward. 

AI can help here by using email and call summaries as a basis. It can then make smart inferences about what activities have been effective for other deals. And then make recommendations to sellers about what to do in the next meeting to keep the sales momentum going strong and make their meeting prep easier.

How AI Tools Can Help Sellers with Writing Better Emails

One of the “classic” use cases for AI with sales teams is to improve the quality of emails that are written by reps. Not every seller has great writing skills. And since email personalization has become increasingly important, it’s vital that your sellers’ emails are high quality.

Email AI sales tools help sellers by generating well written emails that are effectively (and grammatically correct). They can do that from just a prompt that a seller gives – like give me a prospecting email to directors of finance that highlight the benefits of my product. 

Or, they might use a LinkedIn profile or post, for example, as a prompt to generate content that will resonate better with the prospect. While you can automate the delivery of these emails, it’s often a good practice to have the AI generated emails appear as drafts that sellers can then edit and decide whether or not to use.

Sales Pipeline Analysis

As a sales leader, it’s vital that you have solid control over your sales funnel. That means knowing which deals are going to close and which ones are stuck. Too often, leaders are left to rely on their intuition or a rep’s best guess, interviews with sales reps, or some other error-prone methodology.

AI can play a major role in improving the quality of pipeline or sales performance analysis. It can do that by assessing the interactions between sellers and their prospects over email, calls, and calendar invites. By evaluating these sales activities holistically and in detail the AI technology is able to provide revenue intelligence about the current health of deals. 

Armed with this standardized insight, sales leaders and their teams can point to specific actions by their prospects that indicate whether a deal is advancing or not. They can come up with action plans to unstick deals. And they can walk into forecast calls with the executive team or board of directors with greater confidence.

Account Health and Alerts

Similar to the idea of sales pipeline analysis is the notion of churn analysis, which is made more powerful with the addition of account health alerts. Alerts geared to account health can be set-up to let sellers and leaders know when a certain activity by a prospect or seller causes a change in the real status of a deal. Or, on the flip side, if a lack of activity does the same. 

Say for example you’ve just had a call with a prospect. They casually mention that the functionality you offer is missing something that a competitor offers. They hadn’t previously mentioned the competitor. So now you might have a battle on your hands. 

Or, you might have a situation where pricing hasn’t been discussed at all and your deal is supposed to close this quarter. That’s a concern that the sales team should know about. 

AI can step in here for sellers because of its ability to constantly monitor and evaluate data as it’s added. So, when new meetings are held or emails received, AI tools can immediately parse this information and determine whether a real change in status for a deal has occurred. Then it can quickly update the seller who can take action.

Training and Coaching

There are few things that can have more of a positive impact than for sales leaders to train and coach their sellers. Even the best salespeople can benefit from the perspective of a seasoned leader. But what should the leader focus on for their coaching? 

AI sales enablement can help here as well. It can evaluate what are the behaviors that top performers do within your sales organization to be effective. For instance, by correlating rep behavior with closed won deals it might discover that multi-threading to VPs of finance and accounting leaders are critical. 

AI sales tools can then look at the behavior of individual sellers. If a seller is not executing on the kinds of activities that are proven in your sales process to be successful, then that provides an opportunity for coaching and training.

Similarly, during the onboarding process it’s important that sellers can see these kinds of best practices. It’s also important that they can quickly get up to speed on the deals that they are inheriting from prior colleagues. AI tools for sales can help via the summaries and deal analysis mentioned earlier. These kinds of analyses provide a foundation for sellers to get up to speed fast.

Conclusion

In summary, AI sales tools are a powerful agent for sellers to be more efficient and effective. With a “24/7 AI revenue analyst for revenue teams”, sellers and sales leaders can quickly determine where they stand with their deals and how to move them forward.