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Sales analysis can seem daunting, but it’s a critical skill for marketers and salespeople.
To understand how your efforts contribute to the bottom line, you need the ability to read and interpret sales reports.
What is sales analysis? Why should you care about it? And how can you learn to analyze sales reports and use the results for better decision-making?
This guide will walk you through the steps of sales analysis, from understanding your reports to interpreting the results and using that information to improve your marketing and sales strategies.
By the end, you’ll confidently analyze your sales data and make informed decisions about where to focus your efforts.
Let’s dive in!
What is sales analysis?
Let’s start with the basics.
Sales analysis is the process of examining sales data in order to better understand trends and patterns in customer behavior.
This breakdown can be used to make informed decisions about where to focus and align your marketing and sales efforts based on insights into customer needs, wants, and interests.
In order to do this effectively, you need to have the right data at your fingertips, which means being able to read and interpret sales reports.
But what are sales reports? You might ask.
Sales reports are data-rich documents that contain information about your sales performance, customer behavior, and marketing effectiveness.
They typically include:
- Sales figures (such as sales revenue, sales volume, sales growth, etc.)
- Customer data (demographic information and buying patterns)
- Marketing efficiency metrics (such as sales conversion rates, sales lead quality, and sales response times)
In order to effectively analyze sales reports and use the information to make informed decisions, you need to have a good understanding of these different types of data.
That’s where LaGrowthMachine comes in! Thanks to our tool, you’ll be easily able to follow your leads’ actions, understand their sales cycle, and figure out how to improve your sales performance.
Each campaign action you take is easily trackable thanks to our user-friendly interface, so you can know exactly where sales success is coming from – and how to achieve even more.
With reliable live reporting, our tool allows you to track your progress and KPIs in your sales funnel so that you can always monitor your success.
Why is sales analysis important?
Sales analysis is important because it gives sales and marketing professionals valuable insights into customer behavior, sales performance, and marketing effectiveness.
By analyzing sales data, you can identify trends and patterns that inform your sales and B2B marketing strategies.
This helps you make better decisions about where to focus your efforts in order to achieve greater sales success.
What’s more, sales analysis provides sales professionals with huge advantages including:
- The ability to track sales performance and sales funnel progress in real-time
- Insight into sales opportunities, sales conversion rates, and sales lead quality
- Access to customer data that informs marketing decisions about target audiences and buying trends.
- Make data-driven decisions for sales and marketing success.
Make sure your marketing and sales departments are aligned on the metrics used for your sales analysis. That way, sales can feed valuable sales data into your marketing efforts, while marketing can provide sales with actionable insights based on customer data and sales performance management metrics.
The different sales analysis methods
Before you begin to analyze your sales, you need to understand the different methods available and how to use them.
There are different types of sales analysis reports you can refer to, depending on your goals. These reports will give you insights into what is working and what isn’t so that you can make changes accordingly.
Here are 4 of the most used analysis methods you need to know about.
Sales funnel analysis:
Sales funnel analysis is a powerful tool for sales and marketing teams for understanding where sales success is coming from.
By tracking and analyzing your progress online, you identify bottlenecks in your sales process and areas where conversion rates are lagging.
This allows you to improve digital sales performance by optimizing sales tactics and investing more in campaigns that drive sales success.
Focus on your pipeline metrics, conversion rates, sales cycle times, etc. in your sales funnel analysis.
Customer behavior analysis:
It’s important to understand your customers’ needs and buying behavior in order to run an effective sales process.
Customer behavior breakdown is one of the most important sales analysis methods, providing sales professionals with a wealth of valuable insights into sales opportunities and customer needs.
By analyzing your sales data, you can gain insights into:
- Buying trends (e.g., sales trends, sales seasonality)
- Sales opportunities (e.g., sales volume, sales conversion rates)
- Customer needs and preferences (e.g., target audiences, sales triggers)
To stay ahead, it’s important to understand how your competition is performing in terms of sales success and customer engagement.
Competitor analysis is an essential way to get insights into your competitors’ strengths and weaknesses as well as their marketing tactics, sales strategies, and customer targeting methods.
Analyzing your competitors’ data allows you to identify areas where you could improve your own sales process or start new marketing campaigns for maximum impact on sales performance.
When conducting sales competitive analysis, focus on sales success metrics (e.g., sales volume, sales conversion rates), sales data (e.g., sales funnel progress and sales funnel gaps), and customer data (e.g., target audiences, buying trends).
Predictive sales analysis:
Predictive sales analysis is a cutting-edge sales data analytics tool that helps salespeople identify opportunities and predict future sales success.
By using sales data to uncover sales trends, sales triggers, and sales patterns, sales reps can identify future sales opportunities and predict sales performance with a high degree of accuracy.
With predictive sales analysis tools, you can also identify marketing tactics that are driving sales success so that you can invest more in these areas.
By analyzing your past sales, you can not only predict how likely a prospect is to convert into a paying customer, but also make targeted offers to leads that are more ready to buy.
You can furthermore increase the revenue generated per customer by identifying opportunities for upselling and cross-selling based on their behavior.
How to perform sales analysis
Now that you understand the basics of sales analysis and the methods that sales teams use to analyze sales data, it’s time to learn how to perform one yourself.
There are several steps involved in sales analysis, you just have to follow the relevant data and metrics.
Step 1: Understanding & Analysis of your sales reports and data:
The first step in sales analysis is, naturally, to understand your sales data and reports.
This means reviewing your:
- Sales funnel metrics -from your lead generation funnel to customer conversion rates
- Sales conversion rates
- Lead quality (SQLs and MQLs)
- Sales cycle times
- and other important sales metrics.
Make sure that you focus on specific metrics that are relevant to your sales process, and that you have a clear understanding of how these metrics are calculated.
Once you have a clear understanding of your sales data and which metrics to focus on, you can start analyzing.
You can do this manually, or choose a tool for your sales data analysis and interpretation such as Microsoft Excel.
Before starting, verify that you have enough data to make informed decisions and don’t be afraid to use a longer data timeframe to uncover useful trends.
Once you’ve processed the information, you’ll get an overview of your team’s sales performance and previous successes or failures. You can make initial conclusions from this stage.
Step 2: Interpreting the results of sales analysis and using it to inform sales decisions.
Once you have your sales data and sales reports analyzed, it’s time to interpret the results.
This can involve identifying sales success triggers or sales patterns, exploring what factors are driving sales success or failure, and using this information to inform sales decisions.
You may want to create sales KPIs based on your findings, and use these to track sales performance and sales success over time.
This is what we meant by the ability of sales analysis to help you make data-driven decisions earlier.
Once you’ve implemented sales decisions based on sales analysis, it’s important to regularly review sales data and metrics so that you can ensure sales success.
By mining sales data and sales reports, sales professionals can gain valuable insights into their sales process and make informed decisions that improve sales performance over time.
Step 3: Leveraging ales analysis tools:
As we’ve touched on before, there are many sales analysis tools available that can help sales teams analyze data from basic sales reports to sophisticated predictive sales analysis.
Depending on your team’s needs and budget, you may want to explore some of these sales analysis tools before beginning your own sales analysis process.
Usually, these tools are included within a Customer Relationship Management system, sales platform, or sales analytics software.
Some of the most popular sales analysis tools by their functionality:
- Predictive sales analytics: Salesforce, Bizible, and salesPredict
- Sales funnel analytics: Funnel.io, InsightSquared, and ClickFunnels
- Sales analysis dashboard and sales reports: Outreach, HubSpot, and Salesforce
Luckily, with LaGrowthMachine, you can set up your sales processes and let them run on autopilot.
We’ve also created our tool so it can be integrated into all the CRM software that exist thanks to our Zapier integration.
This means you can add LaGrowthMachine to your existing sales process without experiencing technical issues and have access to sales analytics and sales reports at the touch of a button.
Step 4: Optimizing sales tactics and processes based on sales insights:
Once sales data and sales reports have been processed and analyzed, sales teams can use sales insights to optimize sales tactics and improve sales performance.
This may involve revising sales objectives, updating sales goals based on past successes or failures, changing sales processes or procedures, or even completely overhauling the sales process.
Sales teams should always be working to improve sales targeting and performance by leveraging the latest trends in sales technology, testing out different sales tactics and approaches, and using their sales data to make informed decisions that continue to drive results.
Get your sales analysis to the next level
Whether you’re a seasoned sales professional or just starting out in your career, understanding how to analyze sales data and use it effectively is a crucial skill for success in today’s competitive landscape.
By employing effective sales analysis techniques, sales teams can gain valuable sales insights that help them make data-driven sales decisions and improve sales performance over time.
So if you’re ready to take your sales analysis skills to the next level, be sure to explore some of the sales analysis tools and resources available today.
With the right tools and strategies in place, there’s no limit to what sales teams can achieve!