Uncover AI’s Hidden Potential for Revenue: Three Unexpected Strategies

For most consumers, generative AI is a relatively new concept. But in the blink of an eye, this technology has found its way into all aspects of our daily lives.

Today, a large (and growing) number of consumers turn to generative AI to simplify and streamline myriad tasks – from tailoring the perfect Spotify playlist to planning meals to writing wedding speeches.

One thing is certain: Generative AI has made its way into people’s everyday personal and professional lives.

In the world of sales, generative AI continues to be a leading topic of conversation given its ability to improve productivity. Reps and leaders are finding different ways to use AI to make their everyday work more efficient so they can spend more time doing what’s most important: selling. It’s time to go beyond the buzzword and identify practical ways to use this powerful technology to improve sales outcomes.

In 2024, revenue leaders and sellers alike must leverage AI to work better and faster – and think smarter. Here, we explore three unique ways sales organizations can tap into AI to drive revenue in 2024 and beyond.

AI application #1: Fueling expert deal execution

One-size-fits-all selling experiences simply won’t cut it. B2B buyers are more informed than ever, and they expect personalized, value-added experiences throughout the purchase journey. Yet, according to Forrester, just 34% of customers say their B2B seller adds value to their sales process.

AI enables sellers to be prepared for every call – without sinking a ton of time into doing so. In fact, AI is arguably the most critical tool for deal execution.

There are a few key ways sellers can leverage AI to fuel expert deal execution.

Learning more about prospective customers

Informed sellers are better equipped to consult buyers. However, conducting background research takes time.

In 2024, sellers can leverage AI-powered sales prospecting tools to learn all they can about a prospect’s business. That way, the seller can position their pain points, challenges solved, and solutions to speak directly to the current needs of the buyer. This level of knowledge of a prospect’s business increases the likelihood for an opportunity to progress, as sellers are focused on what matters most to their prospects and customers and can quickly demonstrate value. Not only is this helping sellers move deals forward, but it’s also saving them valuable time. HubSpot reported that 78% of sales professionals agree that AI can help them spend more time on the most critical aspects of their role.

Understanding historic interactions

Historical conversations provide valuable context for sellers. However, insights can be hard to come by. A rep may have difficulty remembering past interactions, not every interaction is documented, or interactions are dispersed among many different platforms – making it hard to connect the dots. Or the rep who interacted with the buyer in the past may have left the company.

With conversation intelligence, AI empowers sales teams to surface key insights from previous interactions with a buyer or customer. Sellers can review those previous interactions and quickly understand key moments – without listening to a lengthy call. This gives sellers more time to focus on their strategic task of forming their approach to this opportunity, how they will tell a compelling story of solving key challenges, and resonating with the personas involved in the deal.

In addition, sellers and managers can ask questions about a specific call. For example, a rep might ask, “What competitor was mentioned during this call?” or, “How can I differentiate us from this competitor?” That way, the rep can go into the next call armed with competitive intel, talking points, and content for the buyer.

Perfecting the sales pitch

Role-plays are a great way for sales reps and other revenue-generating roles to practice their skills before there’s money on the line. But traditionally, a seller would have to wait for a sales manager or peer to review their role play and provide feedback. And even if they are able to get feedback from their manager, it isn’t standardized, with room for human biases across managers or only getting generic, non-actionable feedback to check a box.

With AI, those sellers don’t have to wait around. Instead, they can submit role-plays and receive instant scoring based on a standardized rubric which allows for objective and actionable feedback. Sellers can then use that feedback to perfect their pitch and improve outcomes when they’re actually in the field.

Use case #2: Delivering self-enablement at scale

Enablement is key to sales success; that’s nothing new. In fact, it’s proven that companies with dedicated sales enablement programs are more likely to meet quota.

Of course, in-person and virtual training is important. However, reps also have questions and needs that arise outside of those training sessions. In 2024, innovative businesses will leverage AI to empower “just-in-time” enablement – whenever and wherever a need arises.

For example, a sales rep might have a specific question about how a product offering does (or doesn’t) solve a prospect’s challenges. In the past, the seller would pose this question via Slack or another communication channel – and then wait for a subject-matter expert to weigh it. All that downtime decreases their chance for success. With AI, the seller can pose their question and get an immediate response as well as the sources to back that answer. They may also be directed to relevant content and training related to their question.

With AI, reps can always find the information they need, when they need it. That means they always have what it takes to move any deal forward – driving higher rep productivity and high-quality customer and prospect engagements. This also uplevels the enablement function into best-in-class “just in time” microlearning.

Use case #3: Turning dashboards and analytics into impactful action

Most organizations have no shortage of data. Typically, each sales software program comes with its own set of dashboards and analytics. All that data can manifest as noise, debilitating GTM teams, with distraction rather than value. It’s key to understand how to identify key signals within all that noise. But few organizations have the time to dig through the volume of data available to them, much less identify actions to take based on that data.

AI empowers organizations to synthesize dashboards and analytics and then turn that data into meaningful action that boosts revenue. That means sales organizations can surface the most powerful data and know what to do about it. This is because AI can review and analyze mass amounts of data in a short amount of time. Now, organizations don’t have to rely on expensive business intelligence (BI) tools to make sense of their data.

For example, a sales manager might ask, “Who had the lowest scores on this particular training program?” The sales manager gets a list of the lowest performers and can deliver targeted coaching to these reps on this topic. Similar to reps, managers can use AI to equip them with the tools they need to be effective coaches to their direct reports and drive behavior change.

Tap into AI to supercharge your sales success in 2024

Driving predictable revenue and improving team performance are the primary goals of any sales leader. But this comes with a host of challenges. With the advent of AI, sales leaders have an opportunity to embrace technology that works for them in a meaningful and actionable way. In 2024, the most successful sales leaders will be those who leverage AI in unique ways to improve team performance and drive bottom-line results.