Sales: how to analyze your sales results?

Sales analysis is essential to avoid inaccurate forecasts and identify opportunities for improvement.

Whether you're a large company or a start-up, a regular analysis (annual, quarterly or monthly) of your sales will not only provide you with valuable information on your performance, but will also enable you to highlight areas for improvement and training to boost your teams' productivity.

Let's start with a little story:

Nokia led the phone market in the mid-2000s, with 40% market share in 2007-2008. But in 2014, market share fell and the cell phone company was sold to Microsoft. So what happened in seven years? How did a market leader disappear?

Two things happened:

• Apple entered the mobile market with the launch of the iPhone, the very first smartphone, in 2007.
• Nokia underestimated the growing popularity of smartphones and delayed the adoption of change.

The result: underestimation and poor estimates have wiped out a world leader.

If it can happen to an established brand, it could well happen to you. 

Just like an emerging trend, a prospect's interest in your product is limited in time. Whether your aim is to reduce sales cycle time, increase conversions or optimize sales performance, periodic sales analysis is essential.

What is business data analysis?

Salesdata analysis involves collecting and analyzing data from different sources to extract information and make data-driven decisions. By analyzing sales data, you examine your sales performance to identify :

• Vulnerabilities that affect your conversion rate
• Opportunities to optimize the sales process
• Customer weaknesses for targeted messages

The most common example of a successful sales analysis is understanding the performance of your team members. According to a report by Brevet, 84% of sales training is forgotten within three months. So, if you notice a drop in the performance of a member of your sales team, it may be a sign that you need to organize ongoing training programs.

What is included in the business analysis?

A detailed sales analysis involves auditing every aspect of your sales, including :

• Lead generation indicators
• Customer data
• Sales figures such as total sales, average order value, sales per month, etc.
• Sales team performance
• Trends and patterns, comparisons with previous year/quarter/month
• Segmentation-based data analysis
• Forecasts 

Ideally, you gather together everything to do with sales and try to understand what's happening and why. Objective: identify what you're doing right and wrong to create strategies for improvement, and analyze the data to establish an accurate sales forecast.

How often should you carry out a sales analysis?

There is no universal answer. How often you do this depends on many factors, such as resource availability, objectives, sales data and time. Ideally, you should :

• Annual reviews to analyze YOY growth
• Quarterly assessments to analyze parameters such as sales representative growth
• In-depth monthly analyses to create next month's forecasts
• Evaluations after the launch of new campaigns to analyze performance and set target expectations for the future

Why is analyzing sales results essential to boosting sales?

While sales analysis helps you identify financial losses, it can also help you in many other ways:

1. Make data-driven decisions

Next month's sales target must not be unrealistic. It must be backed up by data that is ambitious, but above all achievable. Companies that establish accurate sales forecasts, i.e. define their objectives on the basis of sales analysis, are 10% more likely to increase their revenues year-on-year, and 2 times more likely to be leaders in their sector. 

2. Improve team performance

Sales analysis enables you to evaluate the performance of your sales team, revealing the most effective sales strategies of your top performers. By examining calls or email sequences, you can define their techniques for handling objections, negotiating and closing deals. This analysis can also be used to identify salespeople who need further training. For example, a sales rep who makes 100 calls a month but only closes two deals probably has solid prospecting skills, but needs to improve his or her closing skills. Training these reps to adopt the sales strategies and scripts of their most successful colleagues can boost their effectiveness.

3. Increase conversion rates

Analyzing your sales funnel can help you determine where your prospects are coming from. Are they abandoning their shopping carts? Are they not responding to solicitations? Or don't show up for scheduled demos? Identifying these trends and optimizing bottlenecks will help you achieve better conversion rates. Often, it's the small changes that make the difference. For example, the absence of product demonstrations on your website, or a contact form that's too long, can encourage your prospects to turn to your competitors' products rather than yours.

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What are the key metrics for analyzing sales results?

Before carrying out an in-depth sales analysis, identify your sales KPIs. These vary from company to company, depending on its objectives and resources.

Some sales measures divided into categories:

1. Revenue indicators

• Total sales: Sales generated at the end of the month
• Revenue growth rate: Increase in revenue over last month
• Average transaction size: average revenue generated per account
• Customer Lifetime Value (CLV): expected sales per customer

2. Analysis measurements

• Sales productivity : Efficiency/cost ratio of sales operations
• Sales channel efficiency: revenues generated by the various sales channels compared with the cost of maintaining these channels.
• Customer acquisition cost (CAC): Average cost of acquiring a new customer.
• Sales cycle time: average time required to close a deal, from initial contact to closing.

3. Measurement of sales activity

• Calls made: Number of calls made by each sales representative
• Scheduled appointments: Number of appointments made with prospects
• Lead response time: time taken by sales staff to respond to leads
• Average closing rate: Ratio between the number of leads closed and the number of leads contacted.

4. Pipeline measurements

• Transactions in progress: total number of transactions at various stages
• Transaction conversion rate: percentage of transactions passing from one stage to the next.
• Pipeline velocity: the speed at which transactions progress through the pipeline
• Gain/loss ratio: comparison of completed and lost transactions

5. Forecasting indicators

• Accuracy of sales forecasts: comparison of forecast sales with actual sales
• Meeting quotas: Percentage of sales staff meeting or exceeding quotas
• Revenue forecasts: projected revenues for a given period
• Opportunity success rate: Percentage of opportunities converted into customers

6. Customer engagement indicators

• Customer Satisfaction Score (CSAT): customer satisfaction with your products/services
• Net Promoter Score (NPS): customer loyalty and satisfaction
• Customer retention rate: percentage of customers who remain loyal to your company over time.
• Churn rate: percentage of customers who have stopped using your products or services after a certain period.

Of course, this list is not exhaustive, as the priority depends on your company's objectives and resources. So get your sales team together and create a list of essential sales metrics. Focus on a few indicators. Katie Devoe, co-founder of CBD Nationwide suggests "simplifying the process by staying focused on a few key indicators that best reflect your company's goals and performance. Avoid "analysis paralysis" by not getting lost in too much data. It's all about understanding which metrics really drive your business and focusing on those."

4 steps to analyzing sales data

Once you've defined your sales KPIs, it's time to start the sales analysis process:

Step 1. Collect sales data

Start by collecting sales data from a variety of sources. You can use a Google sheet or Excel if you like, but CRM software makes the task easier: it will save you time, stress and resources, while simplifying the overall process. According to Draven McConville, CEO of Klipboard.io, "Using a CRM and its analysis tools facilitates the data collection process and automates the creation of reports. These tools can automatically collect data and create pre-configured reports, so you don't have to do anything by hand and you save a lot of time." The key to choosing the ideal CRM for your business is to look for a platform with automated reporting and 24/7 customer support. That way, you can create reports quickly and get answers to your questions on time.

HubSpot is a good solution for comprehensive sales management, but don't limit yourself to sales, as this can leave blind spots in your understanding of your customers and your market.

Gather data from a variety of sources to get the full picture, for example:

• Google Analytics shows you which landing pages your customers interact with most, enabling you to identify and reproduce their key characteristics on other pages and increase conversion.
• Hotjar visualizes user interactions in the form of heat maps and session logs, so you can see where your most engaged users are, and where to place CTAs on your landing pages.
• Spiff creates automated sales reports so you don't have to spend time going through all the data to extract meaningful information and articulate the results in detailed reports.
• Supademo tracks user engagement through interactive product demonstrations. It shows a prospect's demo experience, so you know exactly which step converted the prospect.

Step 2. Choose a sales analysis method

Once you've gathered all the data, choose a sales analysis method to suit your business objectives, time and resources. By selecting an appropriate method, you can increase its effectiveness and obtain relevant information to answer specific questions. For example, suppose your objective is to examine the health of your sales pipeline. In this case, you would perform a sales pipeline analysis and focus on indicators such as lead-to-opportunity conversion rate, sales pipeline velocity, average transaction size...

7 types of sales analysis methods

• Sales trend analysis: examine historical sales data to identify trends, growth areas and seasonality. Identify what worked/not worked to inform future actions.
• Sales performance analysis: focus on how your sales team is executing its strategy against sales targets. Find out who's winning and where you can improve.
• Predictive sales analysis: use data and algorithms to forecast future sales and trends, and optimize resource allocation.
• Sales pipeline analysis: examine the health and progress of prospects through your sales funnel. Identify gaps and ensure consistent deal flow.
• Product sales analysis: examine the performance of each product, including revenues, profitability and customer preferences.
• Predictive analytics: use data and models to forecast future events and make informed decisions for sales and any other data-driven area.
• Market research: gather information on your target market, competitors and industry trends

Step 3. Extract key information and forecast sales

Once you've selected a sales analysis method, it's time to get down to business: analyzing the data. Do you have to read the data yourself? Or is it useful to use a tool? Using a tool is certainly useful, but the key is to identify where you need help and whether software is available.

If you're running a predictive analysis, Clari, a revenue platform, will collect data from multiple sources, such as a CRM and Google Analytics. Its AI-based algorithms will identify patterns in customer behavior, such as the typical steps they take before buying.

If you're conducting a sales performance analysis, Gong.io's coaching function will help you collect and analyze sales reps' performance. It will track the topics and behaviors with which reps are struggling during calls, and provide information on the soft and hard skills they need to develop to close more deals.

For general analysis, Diana Zheng, Marketing Manager at ShipStallion, suggests using Tableau or Power BI: "With these tools, you can visualize data in an interactive and visually appealing way, enabling you to gain a deeper understanding of trends and patterns. This data-centric approach has been instrumental in optimizing our marketing efforts and improving the overall customer experience."

Step 4. Create a sales analysis report

Finally, you need to create a sales analysis report to present all your findings in an attractive way. This is your opportunity to explain the team's strategies, goals and growth to stakeholders, based on your findings in a sales analysis report. Include visual elements such as charts and graphs to present complex information in a simplified way. Here are the elements a sales report should include:

Summary of main conclusions and recommendations

• Sales audit methodology
• SMART objectives and goals
• Findings and suggestions for improvement
• Sales strategies with concrete steps
• Conclusion with expected results

We began with the tragic story of Nokia, where a market leader disappeared because of a wrong valuation. Let's finish with the beautiful story of Glossier: a company (which started as a blog in 2014) and reached a valuation of $1.8 billion in 2023. Would you like to guess what its strategy for success was? They anticipated demand with precision. How? Glossier established itself as a "community-driven beauty company", using Instagram to interact with customers, understand their needs and preferences, and generate demand. The brand also analyzed data to predict consumer behavior and market trends.

The result? Sales have grown exponentially.

To be successful, start with sales analysis:

• Do it regularly and watch your sales grow like Glossier.
• Ignore it and watch your sales plummet like Nokia.