How to Run Your Sales Team Like a Data Scientist

Sales Data Scientist

Sales forecasting is a dark art. It’s hard, and something all sales leaders struggle with. But I would argue that forecasting your business accurately is almost more important than hitting your goals.

Here’s the reality: If you’re at a venture-backed startup, chances are you’re aspiring to run your business in the public market. A business in the public market reports their forecasting on a quarterly basis to analysts. If you get your forecast wrong, your share price tanks and wealth goes away. For all of you looking to move into the public market, you absolutely have to get this right now. If you don’t, the perception is that your executive team doesn’t understand their business. No one wants to put money into something that’s unpredictable and volatile — it’s like throwing money on a craps table.

So what can sales leaders do to ensure a more accurate forecast for their growing business? They must adapt the mindset of a data scientist.

Data scientists don’t just solve challenges — they know how to pick the right problems that have the biggest impact on the organization, and then attack those head-on. They’re also inquisitive — always exploring, asking the right questions, doing “what if” analysis, and questioning existing assumptions. Sales professionals are quickly moving towards this mindset as a result of the technology and tools available, and your days in sales are limited if you remain stuck in the old ways.

Focus on Performance, Not Results

Before getting into the right questions to ask, it’s important to understand the relationship between performance and results. As sales leaders, we are obsessed with results. On a day-to-day basis, we need to know what’s coming in today, tomorrow, this week, and this month. We obsess over it to the point of it is paralyzing. That’s not productive.

Performance is doing the things you need to do to get the results you want. Results are simply a byproduct of performance. So, if we can force ourselves to have the mental discipline to obsess over performance measures, the results will take care of themselves.

Never Stop Questioning

Albert Einstein once said, “The important thing is to never stop questioning.” This is particularly true for those who are trying to build world-class sales organizations at high-growth SaaS companies. Constantly increasing quotas and goals forces you to ask yourself: How can we get more? How can we do better?

Adapting the mindset of a data scientist starts with asking the right questions. Here are the questions you need to ask yourself and your team in order to make your business more predictable and efficient:

Is marketing performing against the lead goals that have been set?

In high-growth venture-backed companies, both top-down and bottom-down approaches are important when figuring out how you’re going to take your team from A to B. Part of this is knowing how many leads you can rely on marketing for in order to yield the results you need. Of course, the leads won’t mean anything unless there is strong sales and marketing alignment to go along with it.

Are BDRs hitting activity goals?

An important aspect of sales and marketing alignment is clearly defining the rules of engagement around the leads coming in. In order to uphold those standards, you must have a deep understanding of the activities your reps are completing and the results they are yielding.  How many calls did they make? What was their call to connect ratio? Connect to the meeting ratio? Meeting schedule to opportunity ratio? Understanding these outputs will tell you if your goals are set correctly.

What is the quality versus quantity of leads in our pipeline?

On top of the number of leads, you need to ask yourself if they are the right quality. Doing the simple math of how many leads are coming in versus how many are going out will tell you if sales and marketing are in alignment on the amount and type of leads.

What are my conversion rates at each stage of the sales process?

This, in combination with the next data point, is crucial. It tells you both how much you need and how you are doing. If you know that out of the almost 1,200 opportunities that are generated, you’re going to close 260 of them, you know exactly how many leads you must source at the top of the funnel to reach your goal. This information is helpful from a macro level, all the way down to the rep level.

Sales Funnel Conversion Rates

For example, if your funnel indicates that you are burning through a pipeline and dropping opportunities in stage one or two, this tells you one of two things: either the quality of pipeline being accepted is questionable, or additional training on particular sales execution skills is necessary to help your reps tell a better story. This information gives you a really good insight into what actions will help your team work faster and smarter.

What is my average sales cycle?

On top of conversion rates, the average sales cycle is another key element in understanding if you’re going to hit your number. Based on your conversion rates through the stages, and the time it takes to move through each stage, you can determine if you’re in good shape to realize your goals.

This is also great information for individual coaching. With this knowledge, a rep is able to easily compare himself to his peers. If he can see that he is taking double the amount of time at one particular stage versus the rep who sits next to him, he can figure out what she’s doing that he’s not in order to move people through that stage faster.

Are we wasting time on time wasters?

Sales is an emotional job. We get told no a lot, so when we hear a yes, sometimes we hold onto it more tightly than we should. It’s crucial that we have data to inform which yes’s we should be saying no to.

Think about it — time is the most critical asset you have. A $1 million quota for the year is a $460 an hour cost for a sales rep. If you’re focusing on opportunities that you won’t win, it means you’re wasting $460 dollar an hour, and it will make it that much harder to hit your number. An understanding of how much time you are spending on deals you’ve won, lost, or are still open at each stage can help you hone in on where time and money is being lost.

What deals are at risk?

You need a way to bubble up the deals that are at risk of being lost. How can we know when we aren’t wasting time, and it’s actually worthwhile to throw the cavalry at a certain opportunity? Risk factors include opportunities that are bigger than your average deal size, stuck in a certain stage for longer than usual, or have too few or too insignificant activities logged against it. Once a deal is flagged as a risk, really dig in and understand if it’s a good fit. If not, throw it out. But if it’s a compelling enough opportunity, bring in the extra resources you need to get it done.

Why are we losing?

Win-loss analysis is one of the most important things to consider. We’re so results-obsessed that we often focus on the wins and ignore the losses. The losses can yield extremely rich information for you. If you can pinpoint why the people you thought would buy from you ultimately didn’t, you can take the actions necessary to fix the problem and help increase your conversation rates.

There’s no silver bullet to building and optimizing a sales team. It’s hard work, and every day brings on a new set of challenges. However, by adapting the mindset of a data scientist through focusing on performance measures and asking the right questions, you will have the information you need to grow your team faster and close more deals.

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