4 Best Practices for Smarter Sales

5 min read

Let’s talk traditional sales. People have been selling and buying goods and services for centuries, and at the core of it, the process hasn’t changed that much. 

Of course, things are more polished and advanced today, buy the sales process, at its most simplified level, has always boiled down to a basic formula: The seller finds out information about potential buyers, and then engages with the ones that are best fits. From there the prospect’s interest in buying can be determined and an offer made.

It was (and for many people still is) based on intuition. 

And while intuition-based sales may have worked wonders during the 20th century, in today’s world, businesses must base their sales decisions on rapid market changes, competitor activity, and diverse customer preferences. The rising cost of customer acquisitions also underpins the need for targeted efforts that are efficient and conserve resources.


The Fix: Data-Driven Sales

Data-driven sales involves collecting and using specific metrics to inform all sales decisions, from lead generation to up-selling.

Utilizing such an approach becomes an invaluable asset to businesses. It helps prevent the pursuit of bad-fit customers, which saves time and money and increases productivity. Data insights can also reveal new opportunities that good old intuition can’t detect.

But it can be intimidating, especially for those still learning to embrace data-based decision making. In a world where you can track anything, what is actually worth tracking?

Below are the sales key performance indicators we recommend keeping an eye on:


Total revenue

Total sales by time period

  • Shows whether sales are improving or worsening over time

Sales by lead source

  • Where sales are coming from and which sources are worthwile

Revenue per sale 

Revenue by product

Market penetration

  • How much your product/service is used by customers compared to the overall market

Sales per activity

  • How many sales were made as a result of phone calls, email, in-person meetings, etc.

Percentage of revenue from new business

Percentage of revenue from existing customers

Year-over-year growth

  • Comparison of sales to the same period in the prior year

Number of sales lost to competition

Cost of selling as a percentage of revenue generated

  • How much are you spending to generate sales

Case Study

Brittney is an HR consultant that works with small to medium-sized businesses. Her sales process has been mostly based on following her intuition - relationship building is critical to her business after all!

And while her intuition did lead her to great clients and successful projects sometimes, that wasn’t always the case. She often lost valuable time and resources pursuing clients who weren’t a good-fit and with whom she never entered a working relationship. Even with prospects who eventually turned into clients, she found that the initial sales steps were taking too long because she didn’t have a set process to follow.

Deciding to take a more analytical route, Brittney sets a concrete objective of shortening her sales cycle. This goal raised the following questions for her to answer: How long is the current sales cycle? What’s causing it to be this long? How long should it be? How much money would this change save/bring in? What needs to be done to make this happen?

Based on these questions she identifies the sales metrics that will produce corresponding answers. She begins tracking, gathering, and analyzing data and can then identify the changes she needs to implement to reach her original objective.


4 Steps to Building a Data-Driven Sales Process

  1. Set an objective. What is a business goal you want to achieve? Note what questions arise from your objective.

    For example, if you want to increase the quantity sold of a certain product, you might ask the following: How many units have I sold over a certain time period? Are more of these products being purchased by new or returning customers? Where have my leads come from in the past? And so on.

    Then identify which sales metrics you can use to answer these questions. As your objectives change so will your questions and metrics.
  2. Build a distinct sales process that can be repeated with every customer. With an established process you can see which parts of your approach are working and which ones aren’t. A standardized process also allows you consistently track your desired metrics.

    Keep in mind when making changes to your sales process, make one change at a time so you can collect insights as to if the change is beneficial. 

  3. Track and collect data from every sales interaction, whether you receive no response or turn a prospect into a customer. Even if a sale is never generated you can derive valuable information like where the prospect came from, how they were contacted, why they were qualified as a lead, and if they went to a competitor instead.

  4. With time, you will be able to use your data to find patterns and categorize what evidence points to “good-fit” customers. These metrics will vary from business to business and objective to objective. Sales efforts should then be focused on these customers to make sure time, money, and energy are being maximized.

Sales decisions based on data aren’t complicated or hard to formulate. You just need a little patience, time, and commitment to gathering the data points needed. It’s a small investment to make for a big pay-off.


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