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Always Be Computing: How Sales Teams Need to Adjust to AI Reality

My dad was a foundry equipment salesman. He spent his adult life driving to small towns across the Midwest and meeting with foundry owners. He conducted his business with instinct and trust building: with a lot of sharing goals and plans, discussing pricing and features, and handshakes. What my dad did for a living was not new. Much of what he did came down to trust and communication, and that has never changed.

While the core of sales has never changed, technology has always created advantages for the salespeople ready and willing to adopt it. As a classic example, the Tang Dynasty (618–907 CE) introduced paper money, which made trading easier. Merchants no longer had to rely on cumbersome barter systems or heavy bags of coins. In our time, the shift to customer relationship management (CRM) systems and the internet allowed salespeople to do more business in a better way. In a sense, the Rolodex and legal pads my dad used are the coins and barter of the Silk Road era of history.

What AI Can Do for Sales Today

What a sales team needs from technology in order to succeed depends a lot on the type of product they are selling and the sales cycle that fits their market. Businesses with high-volume sales can most benefit from lead scoring. Leads typically come in from many sources, like trade shows, web forms, or social media. AI can help sort through those leads and find which are most likely to turn into a sale.

Lead scoring, though, is only half the story. The workflow that comes from the lead score is just as important. This involves routing a lead to the right person or queue with actionable information as efficiently as possible. Typically leads are put into well-worn queues, using rules that were created when the CRM was implemented. AI, however, can find the hidden connections that can accelerate the successful closing of leads.

Another AI sales function that can move leads through the pipeline is the idea of a Next Best Action. That is, based on the customer’s profile, what can a salesperson do next to improve the chances of a sale. Does this customer need more information on the product? Do they need a personal phone call? An email? A gift basket?

How Sales Can Prepare an AI Sales Strategy Now

The promise AI holds for sales teams is great. But with that there is a large potential for disappointment. Technology alone doesn’t solve anything — it’s the adoption of technology that makes a difference.

AI depends on data. Victor Antonio, writing for the Harvard Business Review, suggested that teams first “identify the different types of data sets that exist within a company that can be combined to give a more complete picture of the customer base.” Businesses and organizations are usually awash in unusable, siloed data. The first step to giving an AI tool meaningful data is in surveying the stashes of data in an organization, categorizing, organizing, and cleaning the data. Salesforce’s Einstein Lead and Opportunity Scoring use an organization’s sales history to win more deals. While this is a great tool that is embedded in their industry-leading CRM system, feeding it better data will lead to better results.

Another way to get better results from an AI-infused sales system is to better understand the users. Sales can be a brutal side of business. In situations I have seen (I was a struggling sales professional for a time), sales teams can be broken down into star performers, average performers, and those struggling to keep up. Typically, the star performers will excel no matter what technology is put in front of them. To this group, an AI tool will have to work to gain parity with them. The average performer, however, can most benefit from an AI sales tool by filling them in with suggestions and information as they build confidence. Those on the sales team who are struggling can also have their game raised by using AI as a learning tool to start finding ways to win deals.

Understanding Motivations and Frustrations Within Sales

To gain these advantages sales teams need to understand how their people work. What are their motivations? Money is the most obvious, but there are things like career advancement, recognition, and work-life balance. What are their frustrations? How do they spend their time and what tools do they use to get their job done? The answer to these questions can often be surprising. The more groups of salespeople can be categorized into personas, the more technologists can aim and hone their solutions to best support their mission.

Finally, the effective use of AI often requires organizations to change their attitude and methodology. Contracting an AI-focused professional services company, no matter how great they are, cannot set up your AI sales strategy once and for all. Models need to evolve and change over time. Gaining the internal ability to iterate and experiment on models will produce dividends in the end.

Need help fine-tuning your AI approach and solutions? Learn more about Elevate, and see how we can monitor, manage, and extend your systems.