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3 Steps to Effectively Analyze Sales Data (Methods Included)

3 Steps to Effectively Analyze Sales Data (Methods Included)
Allie Smith
August 9, 2021

Performing a regular and detailed sales analysis provides real-time insights into various aspects of the sales cycle. This helps to drive continual improvement and growth. When you analyze sales data and use it effectively, the entire team is better set up for success.

In this article, we’ll discuss why every sales leader should have a comprehensive sales analysis system, as well as the common methods used to analyze sales data.

Why should you analyze sales data?

Analyzing sales data is a crucial part of being an effective sales leader. Especially when it comes to improving your sales team performance and reaching your company’s goals. It can:

  • Help boost revenue
  • Improve team performance
  • Prepare you to scale

Jarrod Wright, Marketing Director of Fi911, says the following about sales data analysis.

“A comprehensive sales analysis system can provide sales leaders with a tool to test and understand what works best for their market. By relying on internal analysis rather than external wisdom, a sales team can establish their own doctrines.”

Help boost revenue

It helps determine the top-performing products or features as well as the ones that may be lagging.

In addition, a sales analysis gives you great market and client insights for growth opportunities. It also means you get a better understanding of your company’s value proposition in the marketplace.

Improves performance

Analyzing your sales data helps narrow in on any issues within your sales cycle. Tracking data like sales activity or training progress will help determine how well your team is performing.

Spend the time in your numbers. It will allow you to regularly find ways to enhance your sales cycle for the most optimal revenue outcome. It also leads to more accurate forecasting, which means better-suited quotas and goals for your reps.

Analyzing your sales data helps narrow issues within your sales cycle

Helps prepare to scale your sales

Reviewing your metrics will help when it comes time to scale your team. Analyzing your sales data to solidify and improve your sales process means you can scale your sales team with confidence.

In addition, communicating and reporting your sales data internally will encourage educated cross-departmental business decisions. When the company has access to regular sales data analysis, it can make smarter determinations for the future.

Steps to Analyze Your Sales Data

How you set up your sales analysis system will depend on many factors: internal sales structure, product, and resources. Regardless of your specifics, there are a few general steps for effectively analyzing your sales data:

  1. Define your objective & metrics
  2. Create a reporting system
  3. Implement your changes

1. Define your objective, then pick your method to analyze sales data

Before you can begin analyzing your data, you first need to understand what you’re looking for and why. What is your goal in analyzing your data? What’s the main data point you want to track?

For example, do you want to focus on customer retention? Then the main metrics you’ll want to track are post-sales data like NPS scores, customer engagement numbers, and churn rates.

Once you determine your main objective, select the most suitable method (or methods) for your sales analysis. There are many types of techniques when it comes to performing a sales analysis. So, it will depend on your company’s goals. Here are the most common sales analysis methods:

  1. Tracking the number of products or units sold
  2. Better forecasting accuracy
  3. Improving sales team performance
  4. Finding improved solutions to current problems
  5. Increasing effective customer engagement & satisfaction

Objective 1: Tracking the number of products or units sold

Revenue Analysis: This method focuses on the actual sales numbers for the products sold. This helps determine which products are top performers and which are underperforming for better sales planning.

Example: Let’s say your company offers 10 different products and you want to analyze how each product sold during Q1.

Running a revenue-focused sales analysis at the end of the quarter shows you that eight of your products are hitting expectations, while two of your products are lagging.

This insight can help direct your sales and marketing planning for the remainder of the fiscal year.

Objective 2: Better forecasting accuracy

Pattern Analysis: A sales pattern analysis focuses on finding trends within your sales data, which can help you better understand your product demand — leading to more accurate forecasting and quotas.

Example: Let’s say your main objective for the year is to grow your product in one of your newly established regions. Utilizing this trend analysis method, you track the sales in the new regions and see which ones are currently trending in the right direction.

From there, you can sharpen your sales approach by using even more distinctive details like buyer trend information.

Predictive Sales Analysis: This analysis uses sales forecasting and anticipatory customer behavior for dissecting data and predicting upcoming revenue.

Example: Let’s say your main objective is increasing your close rate percentage. Using a predictive sales analysis, you see that based on your historical data and current pipeline information, your forecasted close rate is still below your goal.

By focusing on the predictive data in your analysis, you can hone in on where the conversions are struggling specifically within your sales cycle and work on that particular gap.

This method is also particularly helpful when it comes to scaling since you are working with data that gives you insight into your future growth.

Objective 3: Improving sales team performance

Performance Analysis: Sales performance analysis means specifically tracking the performance of your sales team over a specific period of time.

Example: Let’s say your goal for the year is to improve your sales team’s revenue growth performance by 10%. With this method, you track the team’s overall revenue performance each month. Data shows that while they are increasing their revenue, they are still below the 10% goal.

With this information, you can work with your team to incentivize their selling with friendly sales competitions or utilize motivational tools.

Effectiveness Analysis: The sales effectiveness method also focuses on performance, but on an individual level. This includes the rep’s specific quotas and goals, as well as tracking the effectiveness of your coaching.

Example: Let’s use the same example as above — you want to improve your sales team’s revenue growth by 10%. But you also want to see individual revenue growth year over year for each of your reps.

With effectiveness analysis, you focus on tracking each rep’s individual KPIs, in addition to remaining consistent with their 1:1 meetings for regular feedback and coaching.

Don’t forget about the importance of analyzing the effectiveness of coaching different teams as well!

Pipeline Analysis: The sales pipeline method focuses on analyzing the opportunities in your pipeline, including the quality of the leads and your close ratio.

Example: Let’s say your main goal for your team is improving the number of quality opportunities in your pipeline.

Using this method, you track the lead to opportunity ratio to see if there are any noticeable gaps. You notice that the number of outreach is high — based on the SDR team’s activity — but the movement from lead to opportunity is stagnant in comparison.

By utilizing the pipeline for analysis, you can see that the SDR team may need more training on how to identify quality leads instead of focusing on only their outreach numbers.

Objective 4: Finding better solutions to current challenges

Diagnostic Analysis: The diagnostic analysis targets the reasons behind the sales metrics and helps with a potential strategy for improvements.

Example: Let’s say your company released a new product in Q1 of this year and you want to see how it’s been performing with your current customers. Using a diagnostic method, you run post-sales customer satisfaction reports.

You find that while the product initially sold well, your retention rate was lower than normal — this means that there has been some disconnect between the product and the client after the sale has been made.

This method helps you diagnose the specific area of concern, which allows you to focus your solution in the right area.

Prescriptive Analysis: Oftentimes, this method goes hand and hand with the predictive and diagnostic methods since it focuses on the best steps to take to close the anticipated sale and adjust for any potential problems.

Example: Let’s say that you’ve used the predictive analysis method to determine that your sales for Q4 will be lower than previously anticipated.

Using the prescriptive analysis method, you run a sales activity report which shows that your SDR reps are not consistently hitting their outreach numbers. This can be an area where you focus on increasing those sales numbers for the quarter.

This method helps to find ways to increase productivity and find solutions for potential roadblocks to pave the way towards higher revenue opportunities.

Objective 5: More effective customer engagement and satisfaction

Customer Research Analysis: This method is all about market research and how to utilize the information to grow your revenue and retain your clients.

Example: Let’s say your main objective for the upcoming year is to scale your product while keeping your retention rates high.

Using this method, you run post-sales reports like NPS scores and customer satisfaction survey results. While your retention rates are still high for now, you see that the customer satisfaction levels are lower than you had anticipated.

This means that you can focus on training your post-sales Account Managers on areas where they may not be excelling, like their response time or conducting effective business reviews. You can also adjust how often you reach out to your customers regarding marketing campaigns.

Sales analysis methods summarized

2. Create a reporting system

After you’ve settled on your sales analysis method(s), then it’s time to remain consistent with a reporting system. You will want to set up a regular structure for analyzing your data — for example, how often do you want to pull this data? Have you invested in the best software for your particular needs? How do you want to share the results?

Here are some helpful tips for setting up your sales analysis system:

Use your tech stack

Utilize your CRM to create daily, weekly, or monthly team reports for regular updates on the team’s progress. In addition, create a centralized and customized sales dashboard for real-time visibility— this way everyone on the team can have direct access to the current status of overall sales, as well as their own performance.

Also, encourage your team to use the tech stack to their own advantage — whether that’s by creating their own personalized dashboards, running their own individual status reports, or using software for instant feedback and assessments.

Automation for accuracy

One of the most important aspects of sales analysis is making sure your information is as accurate as possible. Embrace automation where it can be the most beneficial for whichever analysis method you choose to use.

For example, let’s say you want to scale your sales team, so you are focusing on the sales performance year over year. This means you’ll want to use the sales performance analysis method and utilize both your CRM and sales coaching/feedback software for the most well-rounded insight into your team’s performance.

Have more, accurate data in your CRM


Communicate the findings of your sales analysis with your team — your sales data is an incredibly helpful tool for your reps in every department. This is also essential when you want to eventually scale your sales team. Before you can scale, everyone needs to have a thorough understanding of the current sales data as well as future sales projections.

Understanding your sales through consistent analysis will keep your sales team focused and productive, but can also direct decision-making internally. A more cross-departmental understanding of the sales data means more knowledgeable goal setting for the company overall.

3. Implement changes

Once you’ve done the analysis, implement any necessary changes or adjustments in your sales process.

For example, let’s say you have a close goal of 20% for the year, so you are using the sales pipeline analysis method to determine the quality of your sales cycle. With your analysis report, you see that while you have a large number of leads converted to opportunities, your close ratio is below 10%.

By using this data, you can hone on the particular part of the sales cycle that needs improvement — in this case, the Account Executives may need stronger coaching sessions or the Sales Enablement team may need to create different sales collateral for your reps.

Once you locate the main issue, you can use the results from your analysis to solve the problem — making the data an asset to improving your sales team's performance.

Final Thoughts

Sales analysis offers direct insight into your sales team, but also marketplace trends, your customers, and your overall ability to grow your product.

Utilizing different sales analysis methods gives you a versatile view of how your teams perform and where you can improve. It also better prepares you for scaling your team and your product — when you have the foundation of your sales cycle securely implemented and performing at its peak, then you are more prepared to grow with determination and certainty.

Hungry for more of our sales resources? Here’s our Sales Capacity Planning article to help you meet your revenue targets.

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