How to perform a sales analysis (step-by-step with methods & metrics)
If you want to achieve your sales goals month after month, then guesswork and intuition aren’t your best friends. You need cold hard data, and your sales CRM must capture all necessary information on the deals closed by your reps.
To improve your sales effectiveness and make informed data-backed decisions, you need to conduct sales analysis regularly.
As you’ll see in the article, sales data analysis provides intelligence about your sales strategy, the performance of your team, and much more. It’s a competitive advantage that you can’t afford to miss out on. So let’s get started with its basics:
- → What is sales analysis and why is it key to your sales strategy?
- → Importance and benefits of sales analysis
- → 9 types of sales analysis methods and techniques
- → How to perform sales analysis: a 3-step process
- → Top 10 sales analysis metrics and KPIs
What is sales analysis and why is it key to your sales strategy?
Sales analysis is mining your data to evaluate the performance of your sales team against its goals. It provides insights about the top performing and underperforming products/services, the problems in selling and market opportunities, sales forecasting, and sales activities that generate revenue.
Regular sales data analysis provides an understanding of the products that your customers are buying and helps you dissect why they are behaving in a certain way. You can also find patterns in your lead conversions and drop offs. All of these aspects enable you to optimize your sales process.
With an intelligent sales CRM like Close, you get actionable reports to keep a close eye on the essential sales KPIs. Such a continuous sales analysis helps in iterating your sales strategy so that you can continue growing your business sustainably.
Importance and benefits of sales analysis
Do you know which products of your company are faring the best and the worst? Sales data analytics examines sales reports to evaluate how your company is performing against its goals. Here’s why you need to integrate it into your sales operations.
- Make data-driven decisions instead of relying on gut instinct - Effective and regular sales analysis unveils how your sales plan is panning out and measures the performance of every individual rep on your team in real-time.
- Find your most profitable customers - Your sales reps should spend the majority of their time engaging with high-quality leads that add value to your company. So it’s invaluable to identify the characteristics of customers that spend the most money on your products and remain loyal to your company.
- Get awareness on the market trends - Are you preparing to launch a new product? Are you planning your future course of actions in terms of stocking inventory, rolling out schemes, and modifying your manufacturing process (if applicable)? A sales analysis report identifies market opportunities and trends to support these efforts.
- Serve your customers better - If you can nail down why a deal closed, you can keep your customers happy and forge deeper relationships. Once you understand their needs better and your brand develops goodwill, you can also upsell and cross-sell to these existing customers.
- Expand your market reach - Sales data analysis and interpretation will also fetch intel on your non-customers. The information is invaluable for sharpening your sales pitches and personalizing your future marketing activities to potentially find new customers.
Now that you’re convinced about conducting sales analysis, let’s look at the different types of sales analysis methods...
9 types of sales analysis methods and techniques
Based on your sales goals, you can refer to different kinds of sales analysis reports for getting insights. Here are nine types of analysis methods you need to know about.
1. Sales trend analysis
This type of sales analysis is about finding patterns in sales data (whether they are going up or down) over a specific timeframe. A micro trend might last for a week for a specific product, while a macro trend might last for a quarter over a range of products.
For instance, the graph below shows that a company has seen an increase in ‘orders shipped’ and ‘sales.’ However, the ratio of sales per orders shipped is decreasing, which the company might want to investigate.
Why sales teams should measure this: Sales pattern analysis is an easy way to track progress towards your sales goals while simultaneously understanding the sales patterns in specific products, customers, or geographies.
2. Sales performance analysis
If you want to gauge the effectiveness of your sales strategy and how your sales team is performing, a sales performance analysis can come in handy. It can involve conducting a strictly financial analysis based on the sales revenue generated and how it’s meeting your sales targets.
Image source: inpaspages.com
Based on what you intend to achieve, you can also seek to evaluate parameters like an improvement in your win rates, faster closing rate, quicker revenue growth, better price margins, and the like. You can work on the gaps found in a sales performance analysis to put your business back on track to “where you need to be.”
Why sales teams should measure this: Sales performance analytics shows how you are currently faring vs. the expected performance. It’s useful for sales managers to coach their reps and fix the vulnerabilities in their sales process/pipeline.
3. Predictive sales analytics
Predictive analytics software can automate sales forecasting for you by predicting your future risks and opportunities. 50% of the global financial planning & analysis teams (FP & A) have described predictive analytics as a priority in 2020.
By conducting past sales analysis, you can predict the likelihood of a prospect converting into a customer and make personalized offers to leads that are ready to buy. You can also increase the lifetime value of existing customers by identifying upselling and cross-selling opportunities in customer behavior.
Why sales teams should measure this: Integrating predictive sales technology with a sales CRM enables data-backed suggestions for improving your conversions and accurate sales forecast analysis.
4. Sales pipeline analysis
I’ve already told you how sales pipeline metrics can be misleading. However regular pipeline review meetings are important to get the context of the deals your sales reps are after. Such sessions involve sales pipeline analytics that looks at the activities your prospects go through before they convert or fall off.
Close offers robust sales pipeline forecasting analytics by letting you quickly review your pipeline through the opportunities page.
It also lets you zoom into your interactions with a specific contact through the leads page.
Why sales teams should measure this: It lets you gain context around a deal so that you can instruct your sales reps to perform sales activities that carry their deals forward.
5. Product sales analysis
If your company offers many products, then you need to conduct regular product sales analysis to find out the items that are overcrowding your product lining. You can use KPIs and revenue bar charts to look at the product sales overall or in a specific time frame.
Image source: microstrategy.com
Why sales teams should measure this: It lets you approach product sales data from various angles like the demographics, product popularity, and the like. Multi-product firms can use the results from this analysis to take constructive actions, like discontinuing unprofitable products.
6. Sales effectiveness analytics
Sales management reports are important to monitor the effectiveness of your sales reps and help them identify selling opportunities in customer interactions. Essentially these reports are about crunching meaningful patterns in your data and actionable insights to improve the sales performance of your team.
With sales management software like Close, you can trust that your sales reps will stay organized, efficient, and spend time on deals that positively affect your bottom line. Our dashboards will let you identify the traits of your top performers so that you can shape your sales training.
You can even share feedback with your reps for filling the gaps in sales skills and improve their effectiveness.
Why sales teams should measure this: Sales effectiveness analytics not only improves the quality of your business decisions, it also enables automating tedious business processes. Thereby your sales reps can spend more time selling, and your sales force can grow stronger.
7. Diagnostic analysis
This sales analysis involves justifying the trends and observations in sales related data with reasonings. For example, the increased competition in the industry might lead to a decrease in your product sales. Sales leaders conduct internal diagnostics to identify the roadblocks for their teams, list their observations, and brainstorm ways to improve.
The Center for Sales Strategy has prepared a diagnostic list that you can refer to as a starting point for auditing your performance.
For your first audit, you can follow the five steps laid out for conducting an internal sales diagnostic here.
Why sales teams should measure this: It lets you review the health of your sales organization by giving detailed insights into different aspects of your sales operations.
8. Prescriptive analysis
Remember the “do this, not that” series? Prescriptive analytics involves generating predictive inferences about customers and prospects. It empowers your SDRs to know the right prospect opportunities they should go after and the offer they need to pitch them (“sell this, not that”).
Indeed your reps are empowered with a granular game plan for every prospect (based on the analysis of past successful sales pursuits). They know the specific sales action, including the sales cadence (i.e. the sequence of touch points across email, phone calls, rich media, and social media), to increase the probability of closing a deal.
To analyze your cadence further and develop a better analysis, try Sequence Reporting in Close. This shows you response rates for each step in your email sequences, giving you the right analytics to optimize and improve your overall results.
Why sales teams should measure this: Guided selling through prescriptive analytics will make the jobs of your sales reps easier. It will also improve the effectiveness of your salespeople and raise your win rates.
9. Marketing research
Occasionally the good old market research helps make informed business decisions.
The technique could involve surveying your customers over the phone, email, or in-person. You can also study your competitors and general sales statistics.
Once you get a good handle on the market conditions, you can evaluate your company’s performance and identify the weaknesses of your sales team. It also identifies potential business opportunities and gives a better understanding of your customers’ needs, thereby improving your sales effectiveness.
Why sales teams should measure this: Sales data analysis and interpretation are based on your past sales data, but market research can fill in the gaps of such analyses. For sales directors, it serves as a gateway into the future.
How to perform sales analysis: a 3-step process
Once you’ve chosen a sales analysis technique, here are three simple steps to create your first sales analysis report.
Step 1: Identify the data you want to track
You need to analyze the right kind of sales data for generating meaningful insights that positively affect your bottom line. Begin with objectives around the departments or products whose sales performance you want to focus on. Here are a few you can get started with:
- Measure the impact of your sales training
- Find the top-selling product from a campaign
- Determine the characteristics of your repeat customers
Next, you need to identify your data sources, the variables that are relevant to your above objectives, and the performance metrics you’ll rely on.
And finally, choose a time frame for collecting your data. You can consider choosing a weekly, monthly, quarterly, or yearly period depending on your requirements. Regular tracking is essential, and you may want to conduct analysis more frequently during special promotions.
Step 2: Choose a sales analysis tool and analyze your data
Microsoft Excel is a robust tool for sales data analysis and interpretation. To get started, ensure that you have sufficient quantity and quality of data to make informed decisions. You may have to lengthen the period of your data to arrive at meaningful behavioral patterns.
With Close, your sales reps can operate efficiently and dedicate maximum time to selling. Indeed much of the sales analytics and reporting is available inside the CRM.
Once you’ve crunched numbers, you should get a historical overview of your sales performance and insights into the success/failure of your team. You can draw preliminary conclusions at this stage.
Step 3: Share your results with relevant stakeholders
It’s time to present your sales data analysis. Unless you’re asked to share the process you used to arrive at the results, only show the key findings. You can use graphs and visuals to help your audience interpret the data.
For example: If you lead a team and want to share your sales performance with the CEO, then you might include charts around your sales goals, your best selling products, the revenue and expenses of your team, and the like.
Overall, keep your presentation actionable and easily digestible. Depending on the nature of your meeting and the role of the stakeholder, you may want to dissect the sales trends and create recommendations for improving your performance.
Top 10 sales analysis metrics & KPIs
Sales reporting and analysis will mean dealing with lots of data. Below let’s look at the top ten sales analysis metrics. If you want to explore more, please check out the full list of 18 sales KPIs that you can track.
1. Monthly sales growth
This metric tells us how your sales revenue has grown/shrunk month-over-month. It’s an actionable metric that you can use to optimize your sales process and strategies.
How to calculate it: (Current month’s performance - previous month’s performance)/100
This KPI dissects the effectiveness of your sales process by telling you about the opportunities that your sales reps are creating. You can use it to forecast sales and determine which opportunities are worth the most.
What to track: Total number of opportunities created by the sales team in a specified period
This gives a broad overview of how your entire team is performing by telling you how many leads are converting into sales. You can work backward from it to understand why and how leads converted, then prepare a foolproof plan for acquiring future customers.
How to calculate it:
(Number of leads that converted into opportunity in a given period)/(Number of leads created in this period)
4. Average conversion time
This sales analysis metric gives an insight into the productivity of your funnel by telling you how long it takes for a lead to convert. Alongside lead conversion rate, sales opportunities, and other metrics, this KPI gives you a bird’s eye view of your sales pipeline.
How to calculate it: Sum of all lead conversion times within a specified period / number of lead conversion times included in that period
5. Monthly onboarding and demo calls booked
Prospects that have made their way this far in your funnel are highly likely to convert. So tracking this metric month-over-month is a great primer for determining the health of your sales funnel.
What to track: # of onboarding & demo calls booked
6. Pipeline Value
This metric tells you the expected revenue from all the sales opportunities in a specific time frame. You get a quick overview of the current value of the deals in the pipeline. And the progress of your sales reps towards your goals.
How to calculate it: Value of projected sale x percentage of confidence in seller that they will Close.
7. Sales targets
This KPI gives historical data on how your team is performing in terms of revenue generated, the number of product subscriptions sold, and the like. Instead of setting ambitious sales targets, you should set attainable future goals so that your reps remain motivated and don’t burn out.
8. Customer lifetime value (LTV)
This sales analysis metric tells you how much revenue an average customer generates for you during their lifetime with your company. You can use it to predict your future revenue, but you need a large data set for accurate assumptions.
With LTV, you can make informed decisions on how much your company can spend on acquiring new customers (CAC).
How to calculate it: Sum of all revenue generated by an individual customer
9. Calls and emails per rep
This metric tells you the volume of calls and emails that your sales team is making over a month, week, or a day. Besides functioning as a sales productivity metric for sales reps, it gives sales managers and leaders an idea if something is off in your sales funnel.
What to track: Sum of all calls & emails made by the sales team in a specified period.
10. New and expansion Monthly Recurring Revenue (MRR)
For most SaaS companies, this is an important metric that tells you the number of paying customers multiplied by the average amount they pay.
How to calculate these two metrics: The new MRR tells you additional recurring revenue you added by acquiring new customers (or lowering your acquisition cost). Expansion MRR is the revenue you collected from existing customers as they upgraded their plans.
If you’re just starting your sales process, then the above sales analytics metrics might overwhelm you. So resort to the basic AQC framework to stay at the top of your sales performance.
A = Activity (for example: the number of cold calls your team is making)
Q = Quality (for example: the actual number of decision-makers that your team gets to speak on the phone i.e. your reach rate)
C = Conversion (for example: how many sales your reps closed or how many demo calls they booked)
Regular sales analysis creates accountability, reveals insights about your customers, the traits of top performing sales reps, and more aspects that will improve your bottom line. I have shown you the different types of sales analysis methods and given you a step by step strategy to perform your first sales analysis.
Now, it’s your turn to leverage sales data analysis to improve the sales performance of your team.
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