skip to Main Content
Back to Insights

The Science of Sales: Using Data to Accelerate Sales


    In our most recent portfolio sales event, we hosted Mark Roberge of Hubspot discuss his philosophy on using a data driven approach to all parts of the sales organization including hiring, training, managing, and generating demand. In our conversation with Mark, we asked him to share how we should be applying his approach to the Scale portfolio (and beyond) and what companies should be thinking about when they scale from $1M – $10M, $10M – $25M, $25M – 100M?

    Q. Let’s start out with a pretty broad, tee up question. Traditionally sales has been viewed as an art. You propose applying science to get better results. Why do you think that? How did this manifest itself at HubSpot?

    MR: It was not intentional on my part. It was all about survival, I had a lot on the line and needed to succeed. In time of stress, I naturally fall back to the numbers. That said, the industry was ripe for this perspective, 1) sales was moving inside, 2) ASP’s were dropping with the cloud and freemium, 3) technology was getting better.  I was lucky to have the right timing with this perspective. In addition, we were building this from the ground up at HubSpot. I didn’t have any legacy bias and we had a culture that promoted fresh thinking.

    We started with a core foundation around the mission of scalable, predictable revenue growth supported by 4 tactics

    1. Hiring same successful sales person every time
    2. Train every sales person in the same way
    3. Hold them accountable to the same process
    4. Provide same quality and quantity of sales leads

    Q. Assuming a company has achieved product market fit, it’s fairly typical for companies to explode to ~$5M – $10M, but then we see some plateau. There is a different class of companies that then continues to excel past $10M. Do you have advice on three things that people can do to continue to accelerate growth when they reach the “danger zone” to get them to $100M+?

    MR: Obsess over blockers to scale, even when times are good. Practice the metrics early so that you have them ironed out at scale when it counts. There are aspects of the planning process that others overlook on the way to $10M that will impact growth later on.

    1. Demand Generation: people take for granted the natural inbound leads from PR, referrals, general new product buzz. There is an under appreciation for that demand gen to dry up. A big blocker is not diversifying sales ops during that 1-10M growth period
    2. Start practicing how to measure and analyze your unit economics early – even before they really mean anything. It’s much harder to create the right process to measure and analyze when it’s critical and you haven’t done it before.
    3. How aggressively you are experimenting? 5-15% of resources should be on experiments.

    Q. It varies by company, but often times we will see that the go-to-market model that got you to where you are today starts to slow down. How would you advise our companies to experiment with their go-to-market model without interrupting the machine that they’ve created? Do you have a framework you can share with the group on how to drive improvements without messing up what’s working?

    MR: Focus on experiments with big upside that take minimal resources and minimal time to run. In running experiments, it is important to stay true to the scientific method – Define the goal and quantify success. Work to find, identify and understand true negatives. Put your best people in the experiment to learn and run your experiments with multiple people to avoid people selection as the cause of failure.

    Q. How did you manage the people management of that?

    MR: At HubSpot, we had a bottom up funnel for innovation and this served two purposes. It allowed for us to get ideas that were based on real life experience in the field, but it also allowed us to give ownership to the person who came up with the idea. What we found was that pride of ownership in sales led to great execution. I found that sales people tend to fall in three buckets. The first, sales leader and they are on the path to management. The second, are career salespeople and they want to make money and sell the latest thing. The third are innovators, future founders and CEO and sales is the path to that. This last category is best suited for driving experiments.

    Q. What was your best experiment, can you give us some examples?

    Experiment Example 1:  Cold Calling

    HubSpot grew up all inbound, it was our strategy, what we sold as our brand. You can imagine the response I got when I proposed cold calling. But our growth was outpacing our demand gen. I proposed a test for 60-90 days and monitored social media to be sure we weren’t getting any backlash to our cold calls. We had the benefit of our brand and being known for inbound that the prospects we were reaching out to didn’t feel like a cold call. We had 2 reps on the experiment and it was vital to separate the team inbound vs outbound – different CAC and buyer education. We saw good improvement by separating these.

    SDR and BDR – we have found too many were using them for inbound and it wasn’t right for the sale. We were able to use science to recognize target lead and that went to the best rep.

    What about the roll of Customer Success in this equation?

    MR: Marketing, sales and customer success, it is important to keep these aligned. Easy when you are small but as a company grows, these often get out of line. Each function defines a good lead fit based on their own role. Marketing defines good lead as easy to drive a download; sales as easy to get a credit card; customer success as easy to make successful.

    We broke down these functional areas and organized cross functional teams around buyer personas. 1 Marketer, 5 reps and 10 customer success, all measured in a way that we were being measured by the board. Rethink the divide and organize cross functional teams that are closest to customer.

    Experiment Example #2: Channel

    We had a motivated sales rep that believed in the channel, we didn’t agree but let him do an experiment on his own time. He works nights and weekends and we saw progress. We then gave him 2 reps and 50K budget. Today channel is approximately 39% of our revenue and 49% of our customers.

    Did this impact direct sales team?

    MR: Eventually, but channel had to direct their own deal flow. It was also slow, we didn’t see direct and channel conflict until about 100M.

    Q. How do you manage growth vs efficiency?

    MR: Establish model and identify leading indicators. If we hit targets, we accelerated, if we didn’t, we slowed hiring. Focused on 30-60 day lifetime customer success metrics.

    Q. For some companies, a data driven approach to sales isn’t a problem, but for those that are challenged with the “status quo,” how do would you start to introduce a data driven sales mentality? How do you start to make changes? How do you make sure that the rest of the executive team is on board? How do you make sure that the data driven mentality permeates its way down through managers to the front lines?

    MR: It is easiest to start the company with this culture in mind.  Then people know what they are getting into from day 1. Otherwise, the transition to a data-driven culture is highly circumstantial to the company. Rarely is the CEO a blocker. Most CEOs crave the predictability and visibility that a metrics-driven culture enables. Some heads of sales are averse to it. It will be difficult to move in that direction if the sales leader is against it. If the leader is for it but not overly analytical, simply surround the leader with a good ops team. Often, the front line reps, especially senior reps, are against such a move.  Create wins with the less tenured folks to demonstrate success and leverage that success to change the culture.

    Back To Top