Deploy AI in B2B Sales

Artificial intelligence (AI) has become an integral part of life. Devices are full of smart helpers that offer suggestions on when to wake up, go to sleep or take a nap. They recommend new artists for playlists or a movie for the evening. They remind users to be active, stay hydrated and eat healthy. AI technology has become a companion for our daily life with one notable exception: The B2B sales organization.

As soon as employees sit down at their desks, they have to make decisions about how to structure the day or when to call clients. Further, these decisions are being made with no data about the most efficient or effective way to do so.

“ AI augments sales staff, but does not replace them”

“AI technologies already impact the way we structure our lives as consumers, but there is hardly any AI support in professional environments,” says Ilona Hansen, Senior Director Analyst, Gartner. “B2B sales especially could benefit tremendously from AI support.”

Gartner predicts that by 2020, 30% of all B2B companies will employ some kind of AI to augment at least one of their primary sales processes.

Using AI in B2B Sales

Before introducing an AI program into the sales department, clarify what the new technology can do and where its limitations lie. AI finds statistical correlations hidden in data. It can automate repetitive sales tasks. It furthermore can offer insights and provide recommendations on what to do next or differently. However, AI doesn’t understand the business, nor can it make client-related decisions.

“AI augments sales staff, but does not replace them. What it will do is reduce administrative sales work to give sellers more time to prospect, find new revenue and upsell existing clients,” Hansen says.

How AI can improve the sales process

Before investing in a pilot project, meet with sales managers and look at the potential use cases to determine which will work best as a starting point. The most promising results for B2B sales organizations are based on three types of AI technology:

• Predictive analytics finds correlations between and among data points. Those tools automatically create the insights that managers and sales reps need. For example, they can determine a prospect’s likelihood to become a client or forecast sales.
• Prescriptive analytics supports guided selling. The AI suggests activities based on the sales methodology. This can be a next-best action to move a deal to the next sales stage or a pricing model based on a prospect’s known preferences.
• Natural language processing, text and sentiment analysis understands and analyzes the context of customers’ questions and their behavior. It can alert sales reps if signs of dissatisfaction are discovered.