Analytics + AI: How Sales Can Get The Most From Data

AI put a spell on me. That’s how I feel every time I click to buy something I don’t need from a precisely placed Instagram ad in my feed. Somehow, AI knows exactly when I’m the perfect target to make a spontaneous or emotional purchase. It’s like magic. But anyone who’s placed an ad on Instagram or otherwise sought to create better curated leads knows AI isn’t a magic pill. In fact, it’s a lot harder to qualify leads—and gain new customers—than you’d think. Yes, sales teams need AI—that’s not the question. The real issue is how can they use AI to get more and better value from their data.

In today’s digital marketplace, it’s imperative that companies stop throwing spaghetti at the wall when it comes to AI. To get real results, they need a clear plan. Sales teams need AI, but AI also needs things from sales teams to be successful. The following are a few tips to get started.

Set Clear Goals

Like I said—it’s easy to start throwing AI at every sales issue in your pipeline and expect a miracle. But AI doesn’t work that way. Sales teams need AI to achieve certain goals, but AI isn’t here to establish those goals for you. AI needs sales teams to set those goals so it can perform and achieve accordingly. These goals could be anything from increasing sales of a certain item to improving your ability to cross-sell across divisions, improving your multichannel experience, or improving overall customer satisfaction. How is your company going to measure ROI? When you determine that, you can determine the type of data you want to collect—and more importantly—how you will use it to create the impact you’re looking for.

The Harley-Davidson dealership that I’ve written about many times before decided they needed more qualified leads from their data. They took their data and used AI to figure out who would be likely customers. Then based on their sales—which increased dramatically—they were able to tell if this goal was achieved.

Reach Across Departments

I want to stand on a rooftop and shout this: digital transformation requires breaking down siloes, especially when it comes to data. Sales teams need AI, but AI needs sales teams to actively recruit big data experts, data scientists, marketing executives—the gamut—to ensure that the AI is cross-functional, data is clean, and a functional execution plan is in place. Again, AI can’t do this for you. It comes down to the culture of your organization and how willing everyone is to work across boundaries and put a winning AI strategy in place.

Data and AI initiatives won’t work if data in the marketing department stays there. So grab a metaphorical hammer and knock down those walls.

Gather Different Types of Data

AI needs tons of data to do its job well. Even more, it needs different kinds of data. Pulling a bunch of data from social feeds won’t give you a full customer profile. You need to pull both structured and unstructured data from web use, purchase history, demographics, emails, audio recordings, customer service interactions, etc. Even more, this data profile needs to be constantly updated to get the full customer picture. Sales teams need AI to process this data, but AI needs sales teams willing to establish the processes that make pulling and processing this data possible.

At the same time, sales teams need to identify exactly what data they need. Sure you need different types, but you don’t want to collect everything just because you can. That will only lead to data swamps and failed AI initiatives.

Company Buy-in

If you don’t involve your internal stakeholders in the adoption of new technology, it won’t be used optimally—and sometimes it won’t be used at all. Sales teams need AI, but AI needs sales teams to do the legwork of involving the rest of the company. If you want everyone across the organization to be able to use the program, then key people need to be involved in the buying process. The C-suite also needs to work to convince employees of the why behind every AI initiative. Company buy-in is probably one of the most important steps if you’re going to get any value from your data.

Be Realistic

Yes, big data requires a lot of data. But don’t bite off more than you can chew. Start small. Set reasonable goals. Make sure you’re collecting a small set of data that is clean, reliable, and useful before adding in the rest of the kitchen sink. AI is amazing, but it isn’t a miracle worker. No amount of AI can sort through data swamps that are fragmented and make no sense. Be realistic when setting your AI systems in place, and your AI will reward you for it.

Yes, sales teams need AI. It has the power to be a transformative tool for your sales teams. AI has the power to increase sales, improve productivity, decrease down time (not to mention discouragement), and make sales more fun and enjoyable overall. Still, AI doesn’t replace common sense or good old-fashioned strategy when it comes to successful implantation. AI allows for hands-off data processing, but sales is still a hands-on job. To enjoy the greatest satisfaction from your AI in the sales department, be sure to keep your AI within arms reach and revisit it as needed to ensure you’re getting the results you need.

The original version of this article was first published on Forbes.

Futurum Research provides industry research and analysis. These columns are for educational purposes only and should not be considered in any way investment advice. 

Daniel Newman

Daniel Newman is the Principal Analyst of Futurum Research and the CEO of Broadsuite Media Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise. From Big Data to IoT to Cloud Computing, Newman makes the connections between business, people and tech that are required for companies to benefit most from their technology projects, which leads to his ideas regularly being cited by CNBC, Barrons, Business Insider and hundreds of other sites across the world. A 7x Best-Selling Author including his most recent “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor. MBA and Graduate Adjunct Professor, Daniel Newman is a Chicago Native and his speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
Daniel Newman