A Real Example of Sales Artificial Intelligence

While many in sales fumble around with automated blasting and spamming, some of the best minds in the world are quietly revolutionizing sales forever. Make no mistake, all professions are facing the great disruption of the machine age as the bots steadily take over the trickiest of surgeries and medical procedures, legal research and precedent analysis, driving in the most hazardous of roads and mines, navigating and piloting the airways, automating banking and accounting, making the most complex decisions for marketing and advertising within markets.

"The best AI vendors are the ones who have walked a mile in the salesperson's shoes. The irony of great AI is that it results in better humanity." - Kyle Porter, SalesLoft

Relationships alone cannot save your sales career. You'll need technology if you are to achieve the level of efficiency and effective needed to thrive. Think like Ironman, Tony Stark integrated with Jaris, in order to avoid being career-kill for Terminator.

The person on the right is my friend Matt Michalewicz and he is changing sales with his company Complexica and their AI salesbot, Larry. The rest of this article is written by Matt and in response to this question.

What's the probem we are seeking to solve with AI for sales?

In my view, there are 5 specific problems that sales managers are struggling with and trying to solve:

1. How can we reduce the non-selling time of our sales reps?
2. How can we increase the ROI on our sales resources, particular those in field?
3. How can we maximise revenue and margin of each quote and order we process?
4. How can we help our sales reps “change the conversation” and become more of a “trusted advisor” with customers?
5. How can we increase CRM compliance, without increasing the sales rep’s administrative burden and non-selling time?

Given that Complexica is extremely “market driven” when it comes to developing software – meaning that we build software products that solve real problems and provide tangible results in terms of business outcomes – we wanted to tackle these problems head on through the application of Artificial Intelligence and big data analytics. The first thing we discovered was that many of these problems were actually data analysis problems – as an example, consider these:

?1)  To “change the conversation”, sales reps need to conduct research on the customer or prospect prior to each visit, in order to create value-adding insights that are specific and relevant to that particular customer or prospect. However, the more time that sales reps spend doing this kind of research and preparing for visits, the greater their “non-selling time” will be. Hence, there’s a total contradiction there, and at heart, this is a data analysis problem.

2)  A similar problem exists when it comes to increasing ROI on sales resources. The only way this can be done is by targeting the right customers and prospects with the right message/conversation/offer. But again, for a sales rep to answer the “who should I call” and “what should I say” questions requires significant data analysis (in-depth analysis of customer trends, buying behaviors, comparison to similar customers, promotional uptake, etc.) and the more of this analysis reps do, the greater their non-selling time will be.

3)  The same holds true for increasing “CRM compliance” – the more time reps spend keeping the data in CRM current, the greater their non-selling time will be, which is another contradiction.

To tackle these problems head on, we first built a computational engine based on Artificial Intelligence (which we’ve called Larry, the Digital Analyst) that can take internal and external (ie web) data and automatically analyse it. We wanted to solve the data analysis problem first, by automating the-time consuming analysis that reps are asked to do. The second thing we did, was build a variety of cloud-based applications that sales reps can access to get real-time answers to these common questions that eat up their selling time to answer. Specifically, Complexic’s software applications use Larry to automatically answer the following questions for sales reps:

• Where are the highest value opportunities in my territory or region? (both customers and prospects) 
• What is my "share of wallet" for each customer? Where are the opportunities and gaps?
• Which customers and prospects should I visit or call this day/week/month? (based on possible churn, highest value opportunities, and other aspects)
• How can I personalise each customer conversation?
• What is the "Next Best Action" or "Next Best Offer" for each of my customers?
• What value-adding insights can I provide to my customers to "change the conversation" and become more of a “trusted advisor”?
• What products can I offer my customers – at what price – to maximize the revenue and margin of each quote or order?

Now let’s turn our attention to CRM, and explain why we also developed a CRM system for our customers, which is “Touchless”. First, it’s important to recognize that most CRM implementations never live up to their original expectations or business case projections, largely because sales reps don’t want to use them – Why? Because sales reps view the data entry associated with CRM as a chore that adds no value to their job (and increases their non-selling time in a very real way). Once CRM is implemented, they view it as a “monitor and report” system that requires a significant amount time to keep current, with all the benefit accruing to management rather than individual sales reps.

The fundamental disconnect here is that management teams need CRM for pipeline reporting, activity monitoring, and the preservation of “customer history”, whereas sales reps are asked to spend countless hours to keep the system current to achieve these objectives. This results in the common problem of compliance. A company spends a significant amount of time and money to configure, integrate, and deploy a CRM system, only to find that it’s barely used, and the data being entered is of poor quality

Our approach to CRM was to develop a “Touchless” system that addresses these common problems from a different angle. Powered by Larry, the Digital Analyst and driven entirely by Artificial Intelligence, the goal of our “Touchless” CRM system was to provide management with the reporting they need, without any data entry from sales reps. We have basically built a system that allows sales reps to go about their day-to-day job, and the “Touchless” CRM monitors their plans, tasks, and executed activities, and automatically updates the appropriate customer record. The less time sales reps spend updating CRM, the greater their compliance will be (with the smallest impact on non-selling time). 

Here are case study examples of Ai enabling sales

Thanks Matt! The world is changing. A cyborbian approach will ultimately win the day for savvy salespeople. If you valued this article, please hit the ‘like' button and also share via your Twitter, LinkedIn, Google+ and Facebook social media platforms. I encourage you to join the conversation or ask questions so feel free to add a comment on this post. Please follow my LinkedIn post page for all my articles and visit me at www.tonyhughes.com.au if you are looking for a keynote speaker. Go to www.RSVPselling.com for sales methodologies that generate pipeline and manage complex opportunities. Image from Google, attribution anonymous.