Why we Invested in SupportLogic

I have observed that the essential function of customer support does not always receive the same level of investor attention. Although Gartner predicts that 89% of businesses are expected to compete mainly on customer experience, very little of that interaction–or the underlying data it creates–is shared across the enterprise in a way that improves products and services, operations, and strategy.

What’s worse, in my view, is that enterprise support organizations are often relegated to second-class status, even though they perform the vast majority of customer conversations. I’ve never understood this mentality. Even when I was running an international sales and marketing group years ago, I knew that the best place to get feedback about our products, competitors, and new market opportunities was our customer support team. I always viewed the area as an opportunity ripe for change.

When I met Krishna Raj Raja, founder and CEO of SupportLogic, nearly a year ago, my head danced with possibilities. It was the first time I had heard someone clearly articulate how AI, modern cloud architecture, and existing, unstructured enterprise data could be used to fundamentally transform traditional support models in the same way that DevOps transformed how companies deliver applications and services.

When Krishna established VMWare’s first office in India more than fifteen years ago, he witnessed just how disconnected support was from the rest of the organization. That experience got him thinking. What if he could build a platform that facilitated collaboration across the organization so that everyone in the company—support, product, engineering, and sales—could work together to take advantage of the intelligence that was being generated from everyday customer interactions?

The idea for SupportLogic was born, and today his vision has become a reality.

SupportLogic combines sophisticated natural language processing (NLP) and deep neural network methodologies to extract critical information from every customer interaction, regardless of channel—phone, web, chat—or medium—voice or text. What’s more, SupportLogic can identify both qualitative (e.g., sentiment and emotion) and quantitative signals that help organizations respond more quickly, predict new opportunities, and optimize business decisions.

From the traditional customer support perspective, SupportLogic could be effective in reducing costs, escalations and time to resolution by 25% or more in key performance categories. What gets me most excited is SupportLogic’s ability to drive collaboration and performance improvements across the entire organization.

SupportLogic’s Intelligent Support Platform aims to help companies understand what customers need and want using a company’s existing unstructured data. Because it integrates with ticketing systems like ServiceNow, Salesforce Service Cloud, Jira, and Zendesk and doesn’t require surveys or focus groups, organic customer interactions define the conversation and produce information that is unbiased and direct.

When I talked with SupportLogic’s early customers, like Nutanix, Rubrik, and Databricks, they raved about the product and its impact on their businesses. One VP of Support told me she couldn’t understand how she ever did her job without SupportLogic. Another told me, “Every company that cares about delivering great customer experiences and reducing churn will soon be a SupportLogic customer.”

I was convinced.

SupportLogic may be primed to change traditional enterprise support models from static, reactive bookkeeping to proactive recommendation engines that address issues in real-time. Perhaps that’s just the beginning. With SupportLogic, I believe customer support will be able to harness and share intelligence from each and every customer engagement in a way that benefits all aspects of an enterprise’s operations and strategy.

I look forward to working with Krishna Raj Raja and his team to elevate the enterprise support experience.

This material presented is for informational purposes only and should not be construed as investment advice and is not intended to recommend any company or investment described herein.  Our views and opinions expressed in any website content are current at the time of publication and are subject to change. Past performance is not indicative of future results. Any specific company discussed is not intended to be representative of any or all companies purchased, sold or recommended for Sorenson Capital’s advisory clients. A complete list of Sorenson Capital investments is available upon request.

One should not assume that all investments are or will be profitable. This material contains forward-looking statements regarding future events or expectations; due to various risks and uncertainties, actual events or results may differ materially from those reflected or contemplated in such forward-looking statements. No representation, warranty or undertaking is made as to the reasonableness of the assumptions made herein or that all assumptions made herein have been stated. Quotes provided by personnel of portfolio companies (or their customers) of certain of Sorenson Capital’s advisory clients may not be representative of the experience of personnel of other portfolio companies and are not a guarantee of future performance or success.