How I Built a High-Performing Data Driven Sales Team [And How You Can Too]

data driven sales team
Sales Operations

As founding CEO of Datameer, I doubled revenue six years in a row, attracted $100M in venture capital and built a market-leading company. The secret sauce that led to my success? A data-driven sales approach. While a data driven sales coaching approach is still challenging to many sales leaders, the importance of chasing the right sales metrics is growing by the day!

Based on Salesforce’s research in 2015, top sales teams are three times more likely to use analytics than under-performing teams. In fact, it’s the top indicator of a high-performing sales team.

Why Is Building a Data Driven Sales Team so Hard?

You can’t deny that sales teams by nature are not data-driven and I would argue, they are almost data averse. But why?

The answer is in their personality profiles. Let’s use Myers Briggs as an example. I observed that companies tend to hire mostly ESFJ personality types as sales reps. Those with ESFJ personalities are typically individuals with great human interaction skills but are less process oriented and data-driven.

Additional reading: The 30+ Most Desirable Sales Skills You MUST Develop

CSO Insights reports that less than 37 percent of sales reps actually use their company’s CRM system.

What’s even worse is that we hire great communicators with sparkly personalities but then force them to become data-entry robots. Especially when it comes to implementing our CRMs, for example.

As you promote these personality types to managers, this change management problem persists. But you can break the cycle.

Below are six steps that can help you build a data-driven team and sales process.

1) Align on Larger Goals and Ownership of Metrics

I can’t stress enough how important alignment is within the entire company, which begins with a path of direct and open communication.

First, get everybody on board with your objective. Often, sales reps misunderstand the intentions of sales managers. Reps may incorrectly assume that management is trying to observe their every move, but their real goal is to boost revenue.

There needs to be a clear understanding of the sales goals and expected benefits across the organization.  

According to Marketo, when sales and marketing teams are aligned, companies become 67 percent better at closing deals.

It’s also critical to clearly define ownership of the data. This means determining which team is in charge of delivering which pieces of data and defining how data quality is measured and how often.

In larger organizations, it might make sense to appoint a member of each team to be in charge of the data from the marketing, sales, support, product and other teams. This cross-departmental team can then collaboratively solve any challenges that arise.

2) Streamline Your Sales Process

Your initiative will likely not improve sales success overnight, but there will be marginal gains day-after-day once you incorporate prioritization. Make sure your team understands this is a long-term plan and why the process is set up this way.

Plot out the steps through small, incremental improvements. It’s rare to see a big project that moves quickly turn out successful.

Set up regular status meetings to track your progress against your goal. Research shows that the more often you review a metric, the more likely you are to achieve your goal.

A study by Censuswide and Geckoboard shows that metric-driven companies are more than twice as likely to hit their goals.

Use a Design Thinking approach to quickly iterate and come up with improvement ideas. Or, it might be worthwhile to consider running your process as sprints, an approach many software development teams have been very successful with. It involves tackling big complex projects in small steps on a weekly basis.

3) Use Existing Data to Help Sales Conversations

An initial assessment of your company’s data assets is important to understand the data’s current quality and value. I saw companies discover “data jewels” that had a big impact on their sales success.

For example, your marketing team has metrics on the leads that read company blog posts, “What is big data?” or “How to put big data into production?” Both articles signal completely different stages of buying readiness and could help improve your sales conversations dramatically.

An approach to finding these jewels is to run a brainstorm session with all parts of the organization. I usually draw the buyer’s journey on a whiteboard and let all departments add their data assets as sticky notes. That way I can see which data assets we collect at which part of the buying process.

There’s no need to start a year-long enterprise data warehouse project. First, investigate if these data assets help before you commit to a resource-intense data integration project. Many times it is just fine to export the data once a week and manually load it into your CRM system.

4) Assess Your Company Data for Quality

Since you need to show the success of your project, motivate and align all stakeholders, you need to measure your progress regularly.

I would start with measuring some simple data-quality metrics, like:

  • How many records do you have?
  • What percent of fields are filled?
  • When were these records last updated?
  • How many prospect phone numbers are actually usable?
  • What is the email bounce rate?
  • How do you measure lead quality and who owns the conversion rate (and everything that impacts it) of leads to opportunity?

Only 23 percent of companies believed that they had reliable data in their CRM.

Have you heard of database decay? Every month, two percent of a lead database becomes outdated as individuals change jobs or titles, companies go out of business, and mergers occur. At that rate, within a year your data can lose up to 25 percent of its value.

If you put garbage in, you’ll get garbage out. Everything you do depends on clean data, so must make it an organizational priority.

The most important measurement to track is whether your data initiative has an impact on your sales success. You won’t see the long-term gains immediately—measure the quick-wins. These marginal gains will eventually add up and show substantial improvements.

I’ve been very successful with constantly running small A/B tests within the sales organization. For example, splitting the team into two different groups and giving each a lead or account list that is sorted differently for a call blitz. After two weeks, you can assess which version saw the most success and implement accordingly.

5) Use the Right Tools to Automate Your Sales Process

I highly recommend testing any process changes with prototypes, like spreadsheets, before you invest a lot of resources and time into building long-term solutions. Adding another set of required fields into your CRM masks or starting another enterprise data warehouse project are huge endeavors without having any indication of its success.

If one of your prototypes shows success, think about ways to automate it. Your sales reps are expensive data entry clerks and are the least motivated to perform administrative work. In fact, their data entry tasks are actually holding them up from selling.

Sales reps only spend 37 percent of their time selling according to research by InsideSales.com.

Try to find technology that automates pesky tasks and reduces the cognitive load, like SalesHero’s sales AI assistant. AI is on the rise and new products can save sales reps up to an hour each day on repetitive sales tasks.

6) Analyze Your Conversion Rates and Sales Velocity

With reasonable velocity and good data quality, you can now tweak and perfect your sales process. Rather than building all of your own reports, I suggest using a solution like InsightSquared as it provides KPIs that you might not have considered.

You can analyze your conversion rates or sales cycles by segmenting industry, company size, product or deal size and plot them into what’s called a “strike zone” that can provide transformative insights.

For example, you might find that for a certain industry your conversion rate is twice as high and sales cycles are much faster. From there, you can load similar targeted accounts into your CRM system and you’re off to the races.

You’ll also find opportunities to help your sales team. Low conversion rates during a certain part of the sales cycle may indicate you need to step up sales enablement and provide reps with extra training and education. You’ll even be able to reliably measure the success of your sales training.

Winning Teams Use a Data Driven Sales Approach

Teams with a data-driven approach significantly outperform those that lack data-driven processes.

Sales reps’ extrovert personalities make them averse to data and process. But an iterative and marginal gains-focused process will help move an organization into a successful data-driven culture.

Having deep insights into high-quality data allows sales leaders to optimize their strategies and significantly increase sales performance and boost revenue.


Also published on Medium.

Stefan is an AI and big data veteran and serial entrepreneur. After building his previous company, Datameer from the ground up to become a leader in data analytics, Stefan is now focused on leveraging AI to solve the biggest cost and pain points for businesses with his latest company, SalesHero. At Datameer, he raised ~ $100 million in venture capital and doubled revenue six years in a row. His passion for entrepreneurship has led to his active involvement with a number of accelerators, coaching entrepreneurs on a path to success.