Ushering in the Era of Intelligence

October 18, 2016

Ah, Dreamforce. After a whirlwind of meetings, sessions and keynotes, the dust has finally settled on the world’s largest customer conference. This biggest news? Einstein, artificial intelligence (AI), built right into the core of the Salesforce platform. It promises to make every customer interaction – from sales to service to marketing to IT – smarter and more predictive.

And, here at Zilliant, we couldn’t be more excited! As a data science company that’s been around since 1998, we’re all about empowering smarter decisions. In fact, Zilliant CEO Greg Peters has been touting data-driven decision-making as early as 2012.

As Shuba Nebar, Salesforce head of data science stated, it’s about “Enabling all businesses to be smarter and more effective and connect with customers in a whole new way.”

Absolutely! Einstein uses all of the data stored in Salesforce – account, lead, case, opportunity, email, calendar, e-commerce, click and social – to surface insights in the context of the business user. For example, making Amazon-like product recommendations that marketing can use to boost cross-sell for consumers. Or, flagging leads with a higher propensity to buy for sales reps with predictive lead scoring. Another use case – predicting when a service ticket is likely to escalate. All of the use cases prove to be powerful in helping Salesforce realize its vision to democratize AI.

Intelligence is the Electricity of Our Era

Consider this statement from the conference: “Intelligence is the electricity of our era.” Salesforce predicts that AI stands to revolutionize lives, just as electricity did, and that analogy is spot on. The world was revolutionized with the introduction of electricity and AI promises to do the same, particularly in a business context.

We have a complementary approach at Zilliant: Delivering data-driven insights to the B2B seller that helps them maximize each and every customer relationship. Using a company’s existing transactional data and applying scientific models and algorithms, we can surface customer retention opportunities at the product level, when they are likely purchase more based on similar purchase patterns, and deliver prices that meet customer expectations and business objectives.

Smarter, More Intelligent, Sales

Let’s walk through an example of the Zilliant approach: Laura works at a B2B industrial distribution company; her book of business includes more than 100 customers that purchase items across the company’s entire product catalog of tens of thousands of SKUs. She’s got quite a lot on her plate, but manages the workload by following the 80/20 rule, spending 80 percent of her time with the top 20 customers. Like all good sales reps, she knows success is a numbers game, if she can hit six to 10 sales calls per day, she’s likely to meet her sales goals through sheer brute force.

Recently, Laura’s company deployed Zilliant solutions to infuse a layer of intelligence into each and every customer interaction. She still plans six to 10 calls per day, but now she can prioritize those calls based on the intelligence she’s received right in the CRM she uses every day. For example, she might call on a mid-tier manufacturer that just dipped purchase volume on two product categories – $1,600 in gears and $765 in lubricants. SalesMax flags these retention opportunities for her, and also serves up opportunities to for Laura to grow the business. She can also see that, based upon customers with similar, ideal purchase patterns, that this mid-tier manufacturer is highly likely to purchase a new product category, $2,238 in rotors. Now, she’s armed with intelligence to have a thoughtful and relevant conversation when she calls on this customer (and Laura knows it’s likely to drive an additional $4,603 in revenue). While she’s there, MarginMax ensures the prices she quotes meet this customer’s expectation on price without giving away the business.

At Zilliant, this is what it means to grow sales, grow profit and grow smarter. And it’s not just the single customer interaction. The magic of data-driven decision-making powered by AI is that Laura doesn’t have to do any of the heavy lifting, sifting through cross-sell reports, analyzing lengthy spreadsheets, or pushing quote requests through internal negotiations. These insights are available to her for each and every customer, each and every time she logs in. Even better, each time she closes a deal, machine learning kicks in, taking in new data, using it as input to continually refresh the model – growing smarter with every interaction.

The result? Our customers consistently achieve 5 to 15 percent growth in sales and profit. That’s why they view Zilliant as a smarter way to sell. And, that’s why we’re thrilled to see the leader in customer relationship management embrace AI and usher in the era of intelligence!

Learn more with this video: A Smarter Way to Sell

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