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11 Examples of Sales Teams Using AI (Successfully)

While some sales teams haven’t yet tapped into the power of AI in sales, many have. Read on to explore how sales teams in 2022 are using AI to close deals easier.

Artificial intelligence, or AI, has snuck its way into everyday usage across many industries. This means most people don’t even know when they’re using artificial intelligence, including sales development representatives (SDRs), or sales reps.

Sales teams are no exception to the explosive growth AI has seen in the past five years. From starting small with email automation to full-blown AI-managed CRMs, pretty much all use cases for using AI in sales lead to one of two results: better ROI or an overall better experience for leads and, eventually, customers.

The results are pretty hard to ignore: B2B companies that embrace next-generation capabilities, including AI, grow revenue at 2x the rate of GDP.

But don’t be discouraged if you haven’t started leveraging AI in your sales or product teams yet; today, we’re breaking down how eleven other sales teams are using AI so that you can start to get an idea of how to start using it too.

What is artificial intelligence in sales?

Artificial intelligence (AI) in sales is the use of technology to perform common sales tasks faster (and sometimes better) than a sales rep. But instead of stealing that SDR’s job in the process of becoming more efficient, that employee is now free to spend more time closing sales and doing higher-level tasks like customer-relationship building.

One of the first well-known applications of AI in sales was through the CRM Salesforce. With millions of users before most people were even thinking of AI, Salesforce was in a unique position where they could leverage the information inputs of so many users to train and build powerful models.

These early models helped Salesforce users with relevant insights, accurate predictions on anticipated lead behavior, proactive recommendations on the best next actions, and the automation of routine tasks, such as entering notes into the CRM.

Since then, artificial intelligence has been transforming sales as we knew it into something that is more data-driven and customer-centric.

11 ways sales teams are using AI

Gartner predicts that 75% of B2B sales organizations will use AI solutions by 2025. But what exactly will this look like?

Let’s talk about that next. Now that we’re on the same page about what AI in sales means, let’s explore its top use cases — some that may be obvious, others might surprise you.

1. Better sales attribution

Who should get credit for the sale: sales or marketing?

Determining which touchpoints have the most significant impact on closing a deal is no new point of contention between sales and marketing. Over the years, a bunch of convoluted attribution models have evolved, trying to determine how much credit each touchpoint should get for a sale.

Sales attribution may be easy with one or two touchpoints. However, B2B sales processes can commonly have 30+ touchpoints before a sale is made. Here’s where AI-powered sales and marketing attribution offers a lot of hope.

Machine learning models can be trained to analyze each touchpoint’s impact better. That way, credit is given where it’s due, and salespeople are better aware of which activities or sequence of activities improve the chances of a sale. More transparency around the impact of each touchpoint ultimately becomes a win-win for everyone and can lead to fewer tensions between teams and employees.

2. Upsell and cross-sell recommendations

Amazon nailed the art of upsells and cross-sells with their AI-powered recommendation system. Well, similar capabilities are available for your sales reps to recommend services or products based on what past buyers have been interested in. This way, your team leaves no money on the table.

Not only can the right upsells and cross-sells increase revenue, but they can also reduce customer churn when done effectively.

3. Reduce churn

AI tools can analyze records of customers who have churned and not churned to find patterns. Once a machine learning model is created, it can warn your salespeople about current customers who are at risk of churning. Likewise, it can tell you factors that increase a customer’s likelihood of staying a customer, such as if they buy certain products.

AI will help reduce churning by signaling to your rep that something needs to be done. For example, your SDRs can offer those who are at risk of churning a promotion on a product that has been linked to higher retention.

4. Real-time feedback

AI in sales can give your sales reps feedback fast, sometimes even in real-time. AI can pick up on things like if your sales rep is talking too fast, their tone of voice, the prospect’s facial expressions, and much more.

Regularly reviewing calls to provide coaching is a good practice, but it’s no doubt time-consuming AI software eases the burden by giving immediate feedback on every single call.

AI also can turn voice calls into transcripts immediately. That way, as a sales leader, you can quickly look for things to improve or recreate at a wider scale. Reading a 20-minute conversation is definitely faster than listening to one.

5. Train new salespeople faster

New sales reps can learn from AI-powered lead scores to develop their own intuition faster. Experienced SDRs often joke about leads they used to think were solid because they were so nice and reassuring.

Now, lead scoring can essentially help sales reps from getting blindsided by “promising” leads that disappear. Even better, lead scoring can save new reps from spending hours chasing a deal that so clearly will never close in the eyes of more experienced SDRs.

6. Gives you more time for sales activities

More than half of a sales rep’s day is spent on tasks that aren’t advancing the sales cycle any further. AI can automate time-consuming activities such as manual data entry, and sorting calendars, ultimately giving you more time to drive the sales cycle forward and close deals. For example, AI-powered CRMs automatically log sales activities like calls, emails, and text messages.

AI can even make customer research easier by going through specific websites and social media channels to gather key industry trends for you. Not only is this great for saving time, but it’s also beneficial in keeping a sales rep’s morale and momentum up. For example, if your sales rep just got off a good high-energy call, but has to take a few minutes to sort manual data entry, their momentum can slowly wane.

7. Shortens the sales cycle

AI can shorten the sales cycle in several ways, but the most common uses are:

  • It can help your SDRs with better timing. For example, it can identify signals that tend to indicate when a lead has moved from the research phase into a buying phase. That way, your team knows when their leads are hot and when it’s time to engage.

  • AI and ML can also help optimize pricing suggestions. By analyzing a customer’s past deals, location, and size, simple AI algorithms can come up with smart pricing suggestions, increasing your chances up upselling.

  • On top of making sure your sales reps aren’t leaving money on the table, AI can also reduce the back and forth of price negotiations with vendors, clients, and contractors.

The capability of AI we just talked about is perhaps extra useful for newer reps. Those with less sales experience tend to play it safe and drag out a sales cycle instead of asking for the sale or closing the deal.

8. Increases customer engagement

Customers value personalized interactions. We’ve all received emails that obviously have nothing to do with you. On the other hand, the few online interactions that were personalized to our interests or problems alone built our trust and loyalty.

AI gives your SDRs valuable insights that help them serve your leads better. With AI, your salespeople are better equipped to recommend personalized content based on their lead’s interests, preferences, and needs. Examples of what your SDRs can access include pages their leads have visited on your website, which solutions they use, and all their interactions with your organization.

AI also makes your team more productive by giving them a 360 view of their leads and customers at their fingertips. Before AI, SDRs would scramble and skim through multiple emails, social media chats, or even paper notes to prepare for a sales call.

Because AI helps compile notes into one place, your SDRs can spend this newfound time better engaging their customers with content and tools that AI suggests will resonate with buyers at specific moments in time.

9. Lead generation

One of the more popular use cases of AI in sales (and marketing, at that) is chatbots.

AI-powered chatbots do a great job of freeing your salespeople from answering common questions. With AI, you can create scripts that get better over time, completely on their own. (Sort of like a new employee.)

AI-powered chatbots can be trained to recognize signals that mean it’s time to escalate the call to a sales rep. These conversations can be automatically logged so that the rep who takes over can easily access what’s been said, qualifying the lead and moving the sale along faster. These conversations can then be used as sources of data to train more powerful chatbots.

10. More accurate lead scoring

Sales reps used to solely rely on their experience to determine which leads were worth pursuing. Over the years, their intuition became more developed. Although experience is important, being able to back gut decisions with data is a solid plan. AI analyzes many different factors of closed deals from various sales reps to identify trends in buying behavior.

AI considers factors such as whether a lead tends to convert after visiting a specific page on your website, how long they scroll through certain pages, and the number of content pieces they’ve gone through.

11. Increases sales forecast accuracy

Sales forecasting methods have been historically based on intuition. The power of AI turns sales forecasting into more of a science than an art. Because sales forecasts play a large role in informing business decisions and budgets, it’s important that they are as accurate as possible and updated in real-time.

Accurate sales forecasts can help sales managers identify the health of deals in their sales reps’ pipelines to help them know when deals are worth pushing or leaving.

Will AI in sales replace SDRs?

We’re no fortune tellers, but it’s extremely unlikely AI will ever fully replace salespeople. AI will undoubtedly replace low-level job roles in sales, but it’ll also create as many jobs as it eliminates.

AI will introduce sales roles that don’t even exist today. Those in these new sales roles will need to know how to leverage AI and data to close more sales.

So while lower-level tasks, such as typing notes into the CRM or scheduling meetings, will be offloaded to AI, responsibilities that require critical thinking are here to stay. In other words, sales rep roles in the future will focus more on developing relationships, strategy, and closing sales.

Final thoughts

The reputation of AI and machine learning has shifted in the last decade. It went from being an evil, faceless robot that was here to strip jobs from hardworking people to a technology that is here to support us and improve our lives.

When used to its utmost capacity, AI works alongside salespeople to make closing the sale easier. It’s just an added bonus that it also helps reduce the number of rejections your SDRs face. By equipping them with knowledge on how to best cater the sales process to each individual buyer, their likelihood of success skyrockets.

Perhaps the best part? You don’t need to be a data engineer or scientist to start using AI in sales successfully. There are many AI solutions that require little to no coding knowledge.

AI can play a valuable role in your company’s sales efforts. Consider it today.

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