Introducing Helix CXM
Today, I’d like to introduce HELIX CXM, a new venture I’m excited to begin. Our aim is to modernize the way B2B data operations work by making data accessible across MarTech applications. We envision a world where you can get the data you need accurately, in real-time, synchronized from any of your data stores.
The idea for HELIX gelled for me while on a trip to Thailand this summer, we got stuck in traffic. Two hours and three blocks later we decided to ditch the taxi and take the MTS (Bangkok’s Mass Transit System). It was an eye-opening experience for me because public transit proved to be the most efficient way to get around in a big city congested with traffic. Everything from the purchase to the transfers from skytrain to ferries worked harmoniously. As a person who obsesses with efficiency, our MTS experience made me feel at ease.
In these moments, I thought back about many of our customer problems we solved while at Digital Pi. We were able to build out an incredible “Gold Standard” framework for their marketing automation. I learned a big lesson: no matter how well we performed our work, success was always elusive because inaccurate data would slow us down or stop us in our tracks. Pull a Smartlist in Marketo and the customer would say “that doesn’t look right” or “we can’t tell who’s a customer and who’s a prospect because our CRM data isn’t right.” Worse yet, it’s something that seems to never be a priority to tackle although the problem is exacerbated with each additional additional application or data set (new tools, acquisitions, etc.). Supposedly simple operations like opt-in/out compliance, or just having the same person’s information, account and entitlements were practically impossible to sort out.
At HELIX CXM we believe it’s time for a modern approach to the problem of making B2B data come together in a trusted, timely, actionable form anyone can employ. It feels great to be back solving for the biggest barrier between B2B companies and their customer relationship: their messy, disparate data.
