Taft Love is a former police officer and federal investigator turned sales operation leader. Taft has built sales development and operations teams for high growth startups like Pandadoc, Smart Recruiters, and DocSend, as well as founding IceBerg RevOps. Today, Taft leads multiple sales teams at Dropbox, while also advising and sitting on the board of a number of startups, and he’s here today to talk about building better sales and marketing operations.
Our conversation with Taft Love about building better business operations, begins with an admission that he wasn’t particularly skilled in this aspect when it came to his own company.
“After running the company solo for years,” begins Taft, “I hired a CEO for Iceberg RevOps, because I realized I’m very skilled at revenue operations, but not so much at running a business. What we see with clients often, is they reach a point where they’ve grown their business beyond ‘gut feeling,’ and they struggle to obtain trustworthy data. There is a huge difference between trustworthy and accurate data. Every report you run is ‘accurate,’ but it might not be trustworthy. Data is a huge barrier because most folks jump into data without a strategy.”
Without a strong data strategy and solid definitions around its usage, Taft believes that data can be a huge operational roadblock for business leaders.
“Starting with a high-level overview of data trustworthiness is key,” says Taft. “You have to have appropriate filters, which means there must be a shared strategy and taxonomy, and those filters have to be set up properly. The CRM has to match the taxonomy of how you’re collecting data, and the people putting data into a system need to know how to gather and enter data into it. Structure and process around data are essential to scale operations.”
Taft then states that data cleanliness is a fool’s errand without key definitions in place.
“First of all, define the word ‘clean,’ says Taft. “For something to be clean it has to be accurate and complete. More specifically, you have to decide what ‘complete’ means. Defining accuracy can be trickier because it relies on verification. If something is accurate, you need an external database to check it against. This is why defining what clean data is, before you clean it, is the key to getting clean data. For example, removing duplicate data is a huge issue in most businesses, but if you’re running a franchise, duplicates are to be expected. Again, this is why peeling back the fundamental layers of definition in regards to data is so essential.”
The conversation then pivots to Taft’s declaration that sales teams are focused on the wrong metrics.
“Most sales teams are focused on the metrics that are easy to measure,” explains Taft, “Not the ones that are important. I’ve been to a ton of sales development conferences, and everyone is talking about activity, like open rates and response rates, which in a vacuum are unimportant. Where we struggle is how those metrics roll-up into companies. Here’s a hypothetical; say there are two reps doing outbound, they both make 100 calls in a week, they both have the same response rates, and both set two meetings. If you only focus on activities, ostensibly that had the same week. Now, what if the first rep was contacting a chain of gas stations in Maryland, but the second reached and booked meetings with a Fortune 1000 company? Not the same week at all, but by focusing on activity metrics alone, you’d never know.”
For a few Cinderella stories about how Taft has helped companies scale and grow their operational processes, a cautionary tale on how it can go wrong, and insight into how you can build better sales and marketing operations in your company, listen to the full episode at the links provided above and below.