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Sales Analytics: Definition and the Fundamentals

Sales analytics turn data into action here's a step-by-step plan to help you build the fundamentals.

Jo White · November 18, 2019
Sales Analytics: Definition and the Fundamentals

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You can collect and measure data on just about every area of sales and consumer activity. It can be tempting to dive headfirst into a data-gathering spree but before you pour resources into tracking every metric, make time to define a strategy.

Your KPIs determine which metrics you should track, not the other way around. By building a process for your sales analytics and tying it to your performance goals, you will empower your team to turn data into action.

What is sales analytics?

Sales analytics is the process of using data to describe and interpret trends and metrics in sales. Tracking consumer behavior and sales activity can uncover patterns businesses use to analyze the results of past sales efforts and predict future sales success.

There are many KPIs more easily achieved with sales analytics data in hand. Examples include: revenue targets, per-customer transaction or revenue targets, sales team productivity goals, and quote-to-close ratios.

The aim of sales analytics is to predict revenue more accurately and make the most of the opportunities in your reach. Continue reading for the fundamentals you need to create a solid sales analytics strategy and generate insights for your team.

How to track sales analytics

Achieving your goals starts with a thoughtful strategy. This step by step guide will position you to track and analyze data you can put into action.

Select data sources

Gather the data for your sales analytics from your actual target market. Your business type will help you understand the best place to find and analyze your customers.

  1. Actual customer foot traffic at a mall or shopping center can show you who’s coming in contact with your store.
  2. Meanwhile, website data from Google analytics or other online data tools are the digital equivalent of a busy crowd.
  3. Collecting survey data is a sales analytics favorite. The structure and consistent questions provide qualitative data that goes deeper into the psychological and behavioral traits behind the actions.
  4. Your past business transactions are a rich source of data. Your real customers’ purchases, and purchasing behavior, can serve as a blueprint for improving your marketing and sales approach.
  5. Similarly, your sales pipeline is full of prospective customers. Mining this resource for insights can help you make the most of marketing and sales qualified leads.

Determine the analysis schedule

Designating regular times to run sales analytics will give you up-to-date data you can use to plan your next sales cycle.

As is often the case, the best sales schedule will vary from business to business. Often, a monthly or quarterly review will suit many companies.

Consider your available resources and sales cycle length to find your best fit. One additional factor to consider is whether you usually see seasonal spikes in sales. These periods could be valuable opportunities for additional insight, so plan to run additional analytics checks during these times.

Choose your team

Who will take ownership of running sales analytics affects the results you’ll get. Your top sales representatives understandably want to focus their best efforts on selling. Giving this responsibility to the wrong person almost guarantees sales analytics will stay on the back burner.

Instead, find people who have the background to use tech solutions and analyze metrics effectively. Communicate results in different areas of your organization, such as marketing, tech, web management, and of course your sales team. Presenting results in a way that engages your team and shows them how the data can influence their goals can motivate your sales representatives.

Choose metrics

Find your critical metrics by focusing on your end goals. Ask yourself key questions such as: What decisions do you want to make with sales analytics insights? Do you need a high-level overview or a more detailed and granular look at particular sales patterns? How many variables do you have the employee hours to analyze in-depth?

Your answers will guide you towards a sales analytics strategy scaled for your business.

10 Essential sales metrics

Almost every business will benefit from insights on these key areas:

  1. Sales growth
  2. Opportunities
  3. YTD and Year-over-year comparisons
  4. Lead conversion
  5. Lead velocity
  6. Sell-through rate
  7. Product performance
  8. Average purchase value
  9. Sales rep performance
  10. Quote-to-close ratio

These metrics will give you a view of your sales strength, historical trends, and how effective your current pipeline is at converting new customers.

Sales analytics outcomes

Once you have data in hand, it’s time to analyze for patterns and trends you can use to drive sales. See which of these goal types are at the top of your list.

Create product promotions

Reviewing purchasing patterns can generate ideas for new marketing strategies. Products that consumers frequently buy together can make an exciting bundle offer. You should also be on the lookout for under-performing products.

Instead of discontinuing these lackluster sellers, talk with the marketing team first and discuss the data insights that may open up new avenues to promote these items more effectively. A great product deserves the right marketing messaging to get the sales numbers you deserve. Finally, think about fresh ideas for top products and seasonal bestsellers.

Investigate new opportunities

With data in hand about your ideal customers’ purchasing behavior, you can develop a more targeted marketing strategy. Segmenting target markets enables you to customize your approach. Patterns and trends can also inform your sense of how to price new and existing products and services to stay competitive.

Set smarter sales targets

Sales metrics apply to your sales team as well as your customer trends and transactions. Reviewing your sales reps’ performance can highlight problem areas in the pipeline that impact revenue and ability to meet KPIs. You may also notice opportunities for coaching to strengthen your sales representatives’ skills. Recent data on how leads move through the pipeline (or where they get stuck) provides important context to set revenue and other sales performance quotas.

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