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Salesforce customer, Armstrong Steel Sales Director Brooke Gerhardt wrote this article.
As a sales leader for the past ten years, I’ve spent hundreds of hours listening to calls and searching for the best examples to use in training. It’s impossible to listen to every call, though, so sometimes valuable best practices go undiscovered.
Here at Armstrong Steel, we sell pre-engineered steel buildings. Our sales reps are sometimes asked very technical questions about our products. Those questions change over time, so our coaching and training needs to adjust to reflect that and address our prospects’ current needs.
That’s why using conversational intelligence has been a game-changer. It works with artificial intelligence and machine learning to transcribe and analyze sales calls. Then it identifies key moments, highlights useful topics, and delivers insights that help me understand reps’ knowledge gaps and improve my coaching.
Here are four ways sales leaders can use AI to help reps make better calls.
Staying on top of trends is important in every industry. In our business, steel building designs can be very complex, with a multitude of design options available to our customers. Understanding what customers are frequently requesting, helps us focus our training, and coaching on what is relevant.
To track these trends, we use Sales Cloud’s Einstein Conversation Insights, a feature that uses AI to surface frequently discussed topics in sales calls. Sales leaders work with their Salesforce Admin to choose which keywords to pay attention to, such as specific buildings and design options. Einstein Conversation Insights then uses natural-language processing to analyze the call transcript and flag moments in conversations that may be of interest. Then it presents this information in an easily digestible format.
Dig deeper into relevant calls by reviewing keyword mentions,
talk-listen ratios, speaker tracks, participants, and duration,
to personalize coaching for every sales rep
Through this keyword tracking, we’re able to see which buildings and design options are popular among potential customers, and sales leaders can train on those specific topics. For instance, maybe AI shows a quarter of customers are interested in adding a lean-to to their building. Armed with that information, we can focus our onboarding and training by making sure our reps understand how to properly write their notes for a lean-to when requesting a quote from our estimators. With so many possible design options available, it’s crucial we focus on those that are more common. We can also train them on when it makes sense to offer it as an option or loop in a manager when it gets too complex.
A lot of customer objections are related to what competitors are offering prospects. Keeping track of your competition’s pricing, processes, products, promotions, or policies will help you avoid getting blind-sided while on a call.
AI can make this process faster and easier. Einstein Conversation Insights uses the keywords we’ve set to comb through calls with customers for mentions of our competition. That leaves us with more time to research. What types of warranties are they offering? Have they changed the materials they’re using? What’s making them more competitive? Can we improve in that area, too?
Tracking competitors also shows us which companies are falling off the map, so we can make sure we don’t follow suit.
Everyone makes mistakes. For sales reps, that might look like overpromising on what the product can do or selling below cost. AI helps our team avoid these costly errors. We’ve set up keywords tracking common mistakes, so sales leaders are immediately notified when they come up in conversation.
If the rep misspeaks, we can adjust customers’ expectations and correct errors before they’re put into writing. It’s much harder to correct a mistake after the customer has purchased, in which case we end up absorbing the cost of the mistake.
So far, we’ve caught several mistakes, saving us around 8% of our overall revenue. We expect to reduce errors by 40-50% over time, as we improve our training and coaching processes to address common mistakes and train reps to avoid them.
Call reviews are when sales leaders listen to sales call recordings to see where reps might need improvement or where they deserve kudos. Key performance metrics, such as conversions or contract value, only tell part of the story. These call reviews provide useful context on why our reps may, or may not, be hitting their numbers.
Now, AI makes the call review process faster and easier. The Einstein Conversation Insights dashboard shows highlights of recommended calls to listen to. We can also skip over less important parts or drill into the keywords that matter most.
Simplify call reviews by focusing on conversation trends
about competitors, products, and custom mentions to know
where to direct your coaching efforts
By using AI, our sales leaders have saved roughly 60% of their time by clicking on keywords, rather than listening to every sales call. It’s also reduced the number of calls sales managers have to sift through by 40%. The less time sales leaders spend reviewing calls, the more time they have to focus on training and coaching reps to succeed.
To learn more about how Einstein Conversation Insights can help sales managers coach reps and teams to maximum performance, take our free training on Trailhead.
Sean Andrews, Salesforce Developer at Armstrong Steel, also contributed to this article. He shares more about how the company approached implementation here.
