Why You Need an AI Workbench

Picture of Joel Shapiro
Chief Analytics Officer

Can you afford to buy technology that solves just one or two business problems at a time? Probably not, which is why you need an AI workbench - a flexible AI tool that you can tailor to your own data, your own people, and your own business needs.

AI Tools Build Profitable and Efficient Operations

It’s no secret that today’s best sales leaders are using AI tools to build more profitable and efficient operations. They’re deploying the right resources at the right time to improve seller performance, build pipeline, create discounting strategies, reduce waste in comp systems, craft optimal territories, retain and recruit top talent, keep their high-value customers, and much more.

In fact, using AI has become true “table stakes.” Sales leaders who have not yet integrated AI into their business decision-making are, quite simply, falling behind. But many AI solutions in the marketplace are too narrow to merit significant investment. I recently spent some time with a company whose leadership was pushing aggressive sales goals. They were particularly intrigued by an AI tool that would generate an algorithmic lead score, which could help them decide which prospects merited additional attention and cultivation. Lead scoring is a great use case for AI, and the tool worked pretty well. But when the company inquired about how to use the AI tool with different data or to solve different problems - for instance, how to tease out coachable lessons for the sales team or how to manage customer value - the vendor could only shrug and point out that those solutions were “on the roadmap.” Ugh.

 

Getting AI to work for your specific business needs and your specific data can be a challenge, because the AI providers in the market today don’t know your data, your people, and your problems better than you do.

 

I also recently participated in a handful of interviews with sales leaders, from Director to SVP levels, in which we asked them about their analytics priorities. We heard two primary themes: first, they lack confidence in much of their internal data, and second, they want analytics and AI to help solve a wide range of business problems. They talked about territory optimization, seller and customer churn mitigation, pipeline velocity improvement, and more. Their data and their needs were highly diverse.

Now, I’m just guessing here, but your data probably isn’t perfect. And I’m awfully sure that you have more than one or two opportunities to use AI to improve your business. (If not, click here for a little more info!)

What is an AI workbench?

An AI workbench solves for this. An AI workbench is a customizable analytics and AI tool that allows non-data-scientists to manage, visualize, and analyze their own unique data in ways that are uniquely important to their business. A good workbench has an intuitive interface and is flexible - enabling analyses as simple as comparing averages across groups to running sophisticated predictive algorithms. Vendors who build only prescribed AI solutions that are embedded in their products are making their best guesses as to what’s important to you. They guess about your data availability and quality. (Let’s be honest, here - do all your sales reps really maintain their deals uniformly in your CRM?) They guess which metrics matter most to you. They guess about the ways that AI will most help your business.

Time and time again, I have seen smart business leaders question the wisdom of investing in tools that solve only one or two problems and that rely on data that they might not have.

A workbench allows you and your team - those who know your data and your business the best - to use AI to solve the problems that are important to you. Workbenches aren’t hands-free - heck, no AI is ever hands-free, despite what the headlines say. But you should invest in AI that works for you right now - that lets YOUR people solve YOUR problems with YOUR data.

That’s exactly as AI should be.

 

See how AI can help your organization efficiently drive revenue using data science, today!

 

Tags: Revenue Intelligence

Picture of Joel Shapiro
Chief Analytics Officer

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