This is part 2 of my blog post on using data to improve Customer Success and Account Management.
The formula as a Customer Success Manager in SAAS is really quite simple.
Reduce Churn; Drive More Revenue.
It’s the formula leading to the coveted SAAS goal of negative churn.
That first goal can certainly be achieved through data, but how can you use data to drive new business from existing accounts?
For the Looker Customer Success team data is an integral part of our up-sell workflow.
New revenue for Looker means more people using data. But instead of spending cycles prospecting new business opportunities within existing customer accounts, our team focuses on helping customers with new use-cases, expanding current use-cases, advising on ways to ingest new data sources, and how best to onboard new teams.
Happy customers help sell Looker for us (check out what people think of our support). If we do our jobs well, up-sell opportunities naturally present themselves.
And, with a centralized data warehouse that lets us compare contracted user counts from Salesforce with monthly active users from our license server, we spend zero time prospecting. Instead, we pursue the natural opportunities that arise based on the hard work we’ve invested in helping a new department onboard with Looker.
This, for example, is an up-sell dashboard that tells each account manager what their up-sell opportunities look like across their account base:
Once a Looker Customer Success Manager has an idea of where there is up-sell opportunity, we’re again using data to drive discussions.
Visualizations, CSVs, Excel downloads, reports of all active users and database connections all come into use as we engage with our customers to inform them, with data, how many users they’re over license. This is only possible through Looker’s centralized data approach wherein we have our Salesforce account & contract information (number of users, number of licensed database connections, licensed database types, etc.) sitting alongside our Looker application event data.
With these data sets sitting side-by-side, we’re able to compare the two datasets in a single visualization, and export all of that data directly into an email to a customer. This is one such visualization that would be dropped into the body of an email directly to a customer:
Through Looker and our centralized data approach, we’re able to know not just where there is up-sell opportunity, but initiate action. Tangible action that leads to more up-sells, more revenue per up-sell, and ultimately, negative churn.
If you’re interested in learning about using data to drive revenue expansion, shoot us a note. We’re happy to help out.