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How to Analyze Sales Data and Optimize Your Pipeline

How to Analyze Sales Data and Optimize Your Pipeline

Your business has many processes that keep it running. But none of those processes are more important than your sales process. Sales are the key to revenue, which is the whole reason your business exists. In fact, the success of your business hinges on your ability to drive sales.

But how do you know if your sales metrics are where they should be? What if there are ways you could be improving your sales pipeline to generate more revenue? Well, there’s only one way to find out: Analyze your sales data.

By performing a sales data analysis, you can learn how to reoptimize your sales process. This also helps with closed-loop marketing:

But you might not be sure how to analyze sales data. If that’s the case, don’t worry — you’re in the right place.

The process of analyzing sales data will look different for every business. That said, there are three basic steps that every sales data analysis will follow:

  1. Track your sales data
  2. Organize your sales data
  3. Assess your sales data

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1. Track your sales data

If you want to analyze your sales data, you have to track that data. But how can you do that?

You probably have a few different tools that already generate sales data. For example, if you have an online store, that store will have data on all the purchases made there, including who buys from you and what they buy. Those key performance indicators — or KPIs — are vital to understanding your sales.

Here are just some of the best sales KPIs for your business to track:

  • Close rate: The percentage of sales that you successfully close.
  • Churn rate: The percentage of existing customers who stop doing business with you in a given period.
  • Annual recurring revenue (ARR): The amount of money you earn each year from recurring payments, like subscriptions.
  • Customer acquisition cost (CAC): The average amount of money that you spend in the process of converting each new customer.
  • Customer lifetime value (CLV): An estimate of how much money you can expect a customer to earn your company over the entire duration of their relationship with you.

Continuously tracking all these sales KPIs is key to your sales data analysis.

2. Organize your sales data

As you track your sales data, consolidate that data into one place and then organize it. 

The best way to do that is to use a tool like a data management platform (DMP) or customer relationship management (CRM) platform. These tools can integrate with multiple sources to pull your separate datasets into a single, centralized location. You can also do this with sales intelligence tools.

Once your data is centralized, you can then clean it — that is, remove any errors, inconsistencies, or duplicates — and organize it however you want. That organization will make your analytics process much easier.

3. Assess your sales data

The final step is assessing your sales data. This is where the actual analysis happens. Essentially, the goal is to take the data you’ve gathered and try to learn from it. You want to extract valuable insights that show you how to go forward with your sales.

But how do you do that? What types of sales analysis can you perform?

The answer depends on your business’s unique needs and concerns. However, there are a few broad types of sales analysis that every business can do:

SWOT analysis

One of the most effective types of sales analysis you can perform is a SWOT analysis. SWOT stands for strengths, weaknesses, opportunities, and threats. 

As the name implies, you want to look through your sales data to find each of those factors. Though often used for competitor analysis, you can use it for sales analysis as well:

  • Strengths: Areas where your business is doing a great job driving sales.
  • Weaknesses: Areas where your sales pipeline is struggling.
  • Opportunities: Areas where you have a chance to generate far more revenue.
  • Threats: Areas where outside factors may cause your sales to decline.

By assessing each of these areas, you can quickly get a sense of how to go forward. Strengths show you what you should keep doing, weaknesses and opportunities show you where you can improve, and threats show you what to keep an eye on.

Historical analysis

Another type of sales data analysis you can do is a historical analysis. That’s where you compare your current sales KPIs to where they were in the past. This gives you a sense of how your sales process has developed over time.

For example, you might see that your churn rate has gone up dramatically in the past six months. That probably means you’ve done something in those six months to frustrate your existing customers, and you should investigate what that is so you can fix it.

You can perform historical analyses over both the short term and the long term to give you a wide perspective of your company’s sales.

Day-to-day analysis

Finally, you can perform sales analyses on a weekly (or even daily) basis. Technically, we’re not talking about a full-blown analysis here — it’s more a matter of setting up a sales analytics dashboard that you can briefly check each day to keep an eye out for any drastic changes.

This type of analysis helps you stay constantly informed about the status of your sales so you don’t ever find yourself out of the loop. It also lets you quickly respond to any sudden problems that crop up in your sales metrics.

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WebFX can help you optimize your sales data analysis and drive more revenue

Looking for help analyzing sales data, or maybe just improving your pipeline? Partner with WebFX! 

We have over 25 years of experience with digital marketing, so we know exactly what it takes to build a killer strategy that drives more sales and earns you more revenue. We also have a top-tier tool for helping you do that — MarketingCloudFX.

Interested in partnering with us? Just give us a call at 888-601-5359 or contact us online today!

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