TechBytes with Jesse Wolfersberger, Chief Data Officer, Maritz Motivation Solutions
CDO, Maritz Motivation Solutions
AI is a powerful force for marketing and sales teams. After finding ‘romantic buyers’, we had a chance to know another set of customers in the buyer’s journey. These are ‘Mercenary Loyalists’. To better understand the scope of sales enablement in empowering employees and improving collective dimensions in the business, we spoke to Jesse Wolfersberger, Chief Data Officer at Maritz Motivation Solutions.
Tell us about your role at Maritz and the team/technology you handle.
My role at Maritz is to bring data and AI into our loyalty, incentive, and employee experience programs. I lead the Decision Sciences team, which is a group of data scientists who specialize in human behavior. I often say that we work with the data of irrationality. If people were robots, then my job wouldn’t exist – everything would be perfectly rational and predictable. But people aren’t robots. Human motivation and behavior are complex and difficult to predict, which makes the data much more interesting, in my opinion.
What is the state of Sales Incentive and enablement in 2018?
I think we’re at an inflection point. We are heading rapidly towards an AI-powered future, but we’re at the adolescent stages. Sales incentive programs in the near future will be focused on empowering and supercharging salespeople. AI-powered programs will help people find the right training, curate the right leads, efficiently spend resources, and ultimately close deals. We are starting to see parts of that future come to light now, but we’re all just taking baby steps. I think one day soon we’ll look back at sales programs of today the same way we look at websites of the 90’s – it will feel like a thousand years ago even though it’s only been a couple of decades.
As a Data Officer, how do you define employee engagement in a B2B space?
One of the concepts we talk about at Maritz is “mercenary loyalty.” This means that someone has all of the indicators of a loyal customer or employee, but ultimately if a different brand offered a dollar more, they would jump ship. Mercenary loyalty is still loyalty, but you’d rather have people who are loyal because there is something about your brand that they are proud to identify with. Think Harley Davidson or Southwest Airlines. That is a squishy answer from a data perspective, but this is a squishy topic. Employee engagement is not a 0 or 1 – it is a spectrum across several dimensions. Through data, we can diagnose a company’s culture and watch it change, but it can’t be encapsulated in a single variable.
How does Maritz leverage data to increase sales productivity?
There are dozens of ways that we engage on a sales program, but the most common and the most important is measuring a program’s effectiveness. A sales program presents a unique challenge from a mathematical perspective because there is no control group. So, if John Doe sells 1,000 widgets and wins a trip to Hawaii, it’s impossible to say for certain how many widgets he would have sold if there were no trip to Hawaii. However, if you get clever with your data analysis, you can create an estimate that, in the aggregate, works just as well as a control group. This allows you, a program manager, to walk into your boss’s office knowing that your program is driving incremental sales, not just rewarding people who would have been top performers anyway. Understanding which parts of your program are and are not working is the first step to improving it.
Do you anticipate content-creation on sales technologies and B2B lead-gen to further improve sales?
I think AI is on the verge of improving the lives of salespeople from top to bottom. Let me be clear, there are will always be aspects of sales that are extremely human – golfing with your client isn’t going away. The innovations will be in giving salespeople tools that help them pursue and close the deals that are the best fits. It’s a benefit for the customers too because the salespeople can be more targeted with their efforts, meaning less shotgun-blast, irrelevant solicitations that we all hate getting in our inbox.
To what extent can automation and analytics improve human-driven sales output for humans?
I’ll use a baseball metaphor. For 100 years, managers and front offices did their best to find, improve, and retain the best players for their teams. With the Moneyball revolution, data and analytics changed what everyone thought they knew about the game and brought about new strategies and processes. Baseball is a human game, and the humans who play it are better at it now than they have ever been. Pitchers are throwing harder. Batters are hitting longer. Managers are getting more out of their teams. Front offices are discovering talented young draft picks that previously would have gone overlooked. This is not autonomous, hands-off automation. This is data-driven, decision-enabling, augmented intelligence. This is happening in business as well. Analytics and data-driven decisions can help you acquire, engage, and retain sales talent. To what extent will this improve human sales output? Hard to say exactly, but likely on an order of a magnitude or two.
With GDPR incoming and disrupting data management practices, what change to your data strategy have you made? How would it benefit your employees and customers?
Like countless other companies, we’ve made the necessary changes to our policies and procedures to comply with GDPR. I think we’ll continue to see a trend of people having more control of their data. However, that is not the same as people sharing less data. In fact, I think sharing will go up, just in more focused ways. Stitchfix, the subscription clothing service, is a good example. In terms of data sensitivity, my body measurements are about as private as data can get, but I’m happy to give that data to Stitchfix because they use it to give me clothes that fit. I’m willing to make that trade because of the value proposition. That’s the kind of thing we’ll see more of, regardless of what laws are in place. Customers will be willing to share their data in order to get personalized experiences. Employees will be willing to share data if it enables their growth and wellness. Salespeople will be willing to share their data if it helps them find and close leads.
How do you work with Data Science and AI/ML for casting better customer loyalty?
We recently completed a pilot with our client HSBC, using AI to make their credit card rewards program more personalized. In this pilot, we trained an AI model to predict reward preferences of HSBC’s customers. In a sense, the AI acted as a personal shopper for the customer, suggesting redemption options that are in line with the customer’s preferences. In our test, 70% of the consumers who redeemed did so in the category that the AI recommended for them. That’s a huge indication for us that this was a benefit for those cardholders. We were able to save them time and effort by letting the AI shop for them. We were the Stitchfix of rewards points. While we were thrilled with these results, we are only scratching the surface. Powered by AI, the future of brand-customer interactions will all start to feel more personalized, seamless, and helpful. The benefits of being a loyal customer will be having great, personalized brand experiences and having the brand solve problems for you without you even having to ask.
Thanks for chatting with us, Jesse.
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