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Anne is finishing up her work week with a few last-minute emails. She confirms a client meeting for next Wednesday, then replies to a lead, promising to send a proposal before the end of next week.

The following Wednesday, Anne receives an Outlook alert that her meeting is in one hour, and traffic is a bit backed up. She should leave within the next five minutes to arrive on time. The next morning, another alert reminds her to finish up that proposal she promised to send.

This is artificial intelligence at work. By 2020, 30% of companies worldwide will be using AI in at least one of their sales processes, according to Gartner.[1] What’s more, by 2035, AI will boost profitability by 38% and generate $14 trillion of additional revenue.[2]

AI is already impacting our lives. It helps us surface data, gives us directions, and reminds us of upcoming commitments. When we use AI for relationship sales, we’re able to not only measure the health of professional relationships, but better manage those relationships in order to achieve the best outcomes.

Artificial Intelligence leads to actionable insights

AI built into workplace platforms, such as Outlook’s calendar, can provide useful insights sellers can use in their everyday work. For example, if a seller has a client meeting two hours away, and traffic is causing delays, AI will send an alert reminding them to leave soon, in order to arrive on time.

AI can also serve up alerts based on IM or inbox conversations. For example, if a customer mentions a competitor in an email, AI can send an alert to check into the details of that message. In another instance, a long subject line might signify a customer complaint ticket. In this case, AI might serve up an alert stating that a server is down, allowing a seller to address the issue immediately in order to keep customers satisfied.

AI powers relationship selling by helping sales professionals keep tabs on their commitments, prioritize communications, and juggle multiple tasks and deadlines.

Leading sales teams with AI

Before the advent of AI, sales forecasting was a bit like weather forecasting—hit or miss.  With AI technology, forecasting improves dramatically. That’s due in large part to removing the element of human error. Rather than asking sellers for their forecast, a machine learning algorithm, along with historical data, can provide spot-on insights. AI looks for signals, patterns, and trends in data. Not only does this provide better accuracy in sales predictions, but it keeps data secure and helps organizations remain GDPR compliant by respecting privacy boundaries.

With AI, sales leaders can keep track of how their team is doing, collectively and individually. The ability to pull up a report card on each seller provides an objective outlook of the health of client relationships and presents coaching moments through actionable insights. Imagine receiving an alert that the end of the quarter is just a few weeks away and the team is two deals shy of meeting quota. With AI, sales teams know where they stand with each client, and whether a relationship is at risk so that proactive steps can be taken to reach sales goals.

With new ways to leverage technology and analytics, relationship selling can reach the next level, giving sales teams the ability to create deeper, more meaningful connections that build trust and increase sales.

profitable sales relationship

[1] https://www.gartner.com/binaries/content/assets/events/keywords/cio/ciode5/top_strategic_predictions_fo_315910.pdf

[2] https://www.accenture.com/us-en/insight-ai-industry-growth#search