⌚ 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.
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 sales by time period
Sales by lead source
Revenue per sale
Revenue by product
Sales per activity
Percentage of revenue from new business
Percentage of revenue from existing customers
Number of sales lost to competition
Cost of selling as a percentage of revenue generated
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.
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.