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Everything You Need to Know About Data in Sales


This is a repost from the HubSpot Sales Blog.

Sales has traditionally been an intuition-driven profession.

What do I mean by this? Well, salespeople conduct research on potential customers and then engage the best-fit prospects in conversation. This allows reps to feel out each prospect’s interest and determine whether or not they’re an ideal customer.

In recent years, however, sales data and technology has changed the way that sales teams think and feel — no longer does intuition sit in the driver’s seat. Sales data has taken the wheel, and for good reason.

Today’s businesses need to make sales decisions in response to market changes, competitor activity, customer preferences, and company-wide campaigns. Plus, as the cost of acquiring new customers continues to rise, sales teams need to focus on targeted efforts to preserve resources.

Dive into this guide to start compiling your data-driven sales strategy.



  1. Sales Data
  2. Types of Data a Sales Team Should Track
  3. Data-Driven Sales
  4. Building a Data-Driven Sales Team


Sales Data

Data is an indispensable component of successful sales teams. Sales data can help representatives avoid pursuing bad-fit customers, and it can inform new opportunities that sales teams wouldn’t detect otherwise.

But data on its own can be intimidating, especially for teams who are getting used to such an analytical culture.

Moreover, sales teams don’t need to make use of every single metric. Before I dive into the types of sales data your team should track, let’s start with how to approach sales data so it benefits your team and company goals.

How to Approach Sales Data

First, set your business objective(s). (This step isn’t about what data can do for you; it’s about the goals within your business. So, focus on what you want for your sales team.)

Example: We want to shorten our sales cycle in Q2.

Next, make a note of what questions arise from your objective.

Example: How long is our current sales cycle? What’s causing it to be at this length? How long would we like it to be? How much money would this save us? What do we need to shorten the current sales cycle?

Finally, identify which sales metrics are needed to answer these questions. (We’ll cover the types of sales data below.)

Now your sales team should know which specific sales metrics to leverage as you work to meet your objective. Over time, as your objectives change, you may need to add or remove various data points based on need.

The following section will cover the types of data your team should know.

Types of Data a Sales Team Should Track

  1. Total revenue
  2. Total sales by time period
  3. Sales by lead source
  4. Revenue per sale
  5. Revenue by product
  6. Market penetration
  7. Sales per prior activity
  8. Percentage of revenue from new business
  9. Percentage of revenue from existing customers
  10. Year-over-year (YOY) growth
  11. Average customer lifetime value (LTV)
  12. Net Promoter Score (NPS)
  13. Number of sales lost to competition
  14. Percentage of sales reps attaining 100% quota
  15. Revenue by territory
  16. Revenue by market
  17. Cost of selling as a percentage of revenue generated


In this section, I cover the most common sales key performance indicators (KPIs). These are important for covering company-wide performance as well as tracking how your sales team is impacting your broader company goals. Let's look at them in more detail in the following chart. We'll talk about how to actually collect this data later.

(For a list of over 50 sales metrics as well as a breakdown of sales KPIs per team type, check out our Ultimate Guide to Sales Metrics.)



Total Revenue - How much revenue your sales team is generating

Total Sales by Time Period - How your sales team is performing (i.e. improving or worsening) over time

Sales by Lead Source - Where your sales are coming from and what lead generation sources are or are not working

Revenue per Sale - How much revenue is generated by every sale you make

Revenue by Product - How much revenue is generated by each product, product line, or service that you sell

Market Penetration-How much your product or service is being used by customers as compared to the total estimated market

Sales per Prior Activity-How many sales were made for each prior activity (e.g. phone calls, email outreach, in-person meetings, etc.)

Percentage of Revenue from New Business- How much revenue is generated from brand new customers

Percentage of Revenue from Existing Customers -How much revenue is generated from existing customers (i.e. cross-selling, upselling, repeat orders, expanded contracts, etc.)

Year-over-Year (YOY) Growth- How your sales team performance is growing as compared to the previous year

Average Customer Lifetime Value(LTV) - How much revenue you can expect one customer to generate throughout your business relationship

Net Promoter Score®(NPS) - The degree to which people (e.g. your customers) would recommend your company to others

Number of Sales Lost to Competition - How many sales in a given time period are lost to competition

Percentage of Rep Attaining 100% Quota - How many representatives on your team are attaining 100% of their quota

Revenue by Territory - How much revenue your sales team is generating by territory

Revenue by Market -How much revenue your sales team is generating by market

Cost of Selling as a Percentage of Revenue Generated - How much your company is paying to generate sales

Download our free Sales Metrics Calculator to calculate your average deal size, win-loss rate, churn rate, and more.

Data-Driven Sales

Data-driven sales is a sales approach that involves collecting and using specific metrics to inform all sales decisions, from lead prospecting to people management to churn reduction and pricing.

Using data in sales can help your representatives improve productivity. It can also save them precious time and energy pursuing customers who aren’t a good fit or are uninterested. Implementing a data-driven sales approach can also make your business more profitable — up to 6% more profitable than their competitors.

This approach sounds easy enough, right? Well, it’s one thing to say you embrace a data-driven sales strategy … and it’s quite another to use that data to influence, develop, and empower your sales organization.

Let’s talk about what a data-driven sales approach looks like in action.

Building a Data-Driven Sales Team

A sales team that relies on data observes a handful of distinct practices. Read through these to see how your sales team can start following the same approach.

1) They align on goals and mission statements.

A data-driven sales team is aligned on everything — from big objectives to day-to-day goals. This alignment is the responsibility of sales managers to communicate and execute. It’s also good practice to develop those objectives and goals with your entire sales team, so loop them in on any planning or goal-setting meetings.

This process mirrors the questions I discussed above about figuring out what sales data to use. They help determine what goals your sales team are pursuing, what data can help you achieve those goals, and what each team member needs to do to stay aligned in your pursuit.

2) They build and follow a sales process.

A data-driven sales team follows a distinct sales process — a repeatable set of actions your team does to close a new customer. A sales process allows you to see which parts of your sales approach are working and which parts aren’t. By repeating the same actions across your team, you can make a note of where you can incorporate and track new KPIs and sales data.

When making changes or updates to your sales process, do so slowly and with one change at a time. This lets your team get used to the change and allows you to clearly see if that change is benefiting or hurting your overall sales process.

3) They use existing data to inform strategy.

A data-driven sales team doesn’t only use new data; they also use any data they’ve already been collecting (even if it’s never been put to use). Existing data can be a goldmine of insights and untapped ideas — just take a look at how Harley Davidson used old data to increase new sales by almost 3,000%.

Before diving into a new data tool, do some analysis on any existing sales data, such as information about past buyers and prospects. Gather your sales team and chat about what existing data you have and how you can use it to inform new decisions or strategies.

4) They work with a CRM — and they make data accessible.

A data-driven sales team works closely with a customer relationship management (CRM) tool, such as HubSpot’s free CRM. A CRM database is highly valuable. It effectively replaces cluttered spreadsheets and disjointed tools — and it generates helpful sales reports (which you can also find in HubSpot’s SalesHub).

A CRM can track all prospect and customer activity and automate even the most menial tasks, such as email follow-ups and contact updates. It also keeps your sales team aligned, making all of your sales data equally accessible.

Get full visibility into your sales process with HubSpot’s free sales reporting.

5) They track all prospect interactions to learn what works and what doesn’t.

A data-driven sales team treats every prospect interaction with equal importance. Whether a prospect never responds or becomes a customer, every interaction can give your sales team valuable data and insight into what’s working.

Prospect interactions can tell you a few important things:

  • Where that prospect came from
  • Why your sales rep reached out in the first place
  • How your sales rep made contact and what form of communication they used

From initial contact, you can also track either 1) the sales cycle for the specific prospect, or 2) which competitor you lost the prospect to. You can also gather demographic and psychographic information from each prospect that becomes a customer to further build out your buyer personas.

6) They only engage with leads and prospects that fit certain criteria.

A data-driven sales team only pursues leads and prospects that prove to be good-fit customers — something that proper data can tell them. As I said above, sales data has the potential to save your sales team precious time and energy, as well as make your company more profitable.

To do this, your team must make use of the data it collects. Once you qualify good-fit leads, your team should know what data to look at to understand whether they should engage a new prospect. Perhaps you’ve defined a good-fit lead as a customer with a certain monthly revenue as well as a certain minimum of marketing team members. Encourage your team to focus their energy on prospects that fall into this category.

Learn how to prospect and identify good-fit leads that could become paying customers.

7) They communicate about best practices and approaches that don’t work.

A data-driven sales team is constantly sharing best practices with one another. Perhaps one of your sales reps has learned a new way to use their sales data. Perhaps another has found a new approach that almost always guarantees a prospect response. Regardless, your sales team should always be chatting about their best practices and approaches that don’t quite work. You can share this information through team-wide meetings or via one-on-ones between managers and reps.

Not only will this strengthen morale and act as a means of sales coaching and training, but it will also help you continually keep your data — and how you use it — up-to-date. Sales data is an iterative process, and your sales team can help you constantly improve on how you use and apply it.

Sales Data Helps You Grow Better

No longer does intuition lead the charge on your sales team; sales data is the new kid on the block. A data-driven sales team can save your organization time, energy, and money — resources that your company likely doesn’t have to waste. Data in sales can also align your sales team and streamline your sales process in a way that maximizes revenue and business impact.

Take a look at your existing sales data, get started with a free CRM, and dive into how data in sales can help your organization flourish.

Originally published Sep 27, 2019 7:30:00 AM, updated September 27 2019

Written by Allie Decker

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