Click 'Read Original' for details. Sales data analysis reports are a must-have for sales work. If salespeople can't create them, they're just fighting battles without keeping score—ending up with a mess! A sales data analysis report is composed of both statistical data and the salesperson's analysis of that data. In other words, data without scientific analysis is just numbers, not a sales data analysis report! When creating such reports, you often hear comments like:

  1. Isn't it just data compilation? Then organize and summarize—how simple is that?
  2. At the very least, organizing the inventory data should suffice.
  3. What you're saying is too complicated. Just tell the boss whether the task was completed or not. Giving the result saves so much trouble!...

What's in it for you?

  1. Speaking with data is a prerequisite for having a voice as a salesperson—it's professional integrity!
  2. Analyzing data reports is a summary of your own sales work, giving you a clearer, more macro view of the market's pulse, then filling gaps. It's like a routine 'health check' for your market area. It deepens your familiarity with sales conditions, helps analyze market dynamics, enhances your business awareness and control, and cultivates market forecasting.
  3. Sales data analysis is a way to 'win over clients'—it's in black and white, hard to dispute, showcasing your professionalism and earning trust.

Why don't salespeople take sales data analysis seriously?

  1. The company has no specific requirements or standards for sales report analysis. Even if there are, it's just the boss saying, 'Analyze the market for me,' and that's it. Then the salesperson is confused, scratching their head, piecing things together. Finally, the boss looks at it, sees it's 'off the mark,' and says, 'Redo it!' You're left dumbfounded.
  2. The company has standards for sales analysis reports, but they're too cumbersome and complex. They might as well make it the 'most comprehensive database on earth,' making frontline work time-consuming and exhausting. It takes days to complete, so salespeople resent it and start producing 'fake' data. The results are predictable. Then managers take this 'fake' data and report it up the chain—no wonder company strategies go astray! Such cases are all too common.
  3. The company lacks promotion of sales analysis reports. Salespeople don't understand the benefits, so managers need to lead by example. The content of sales analysis reports must evolve with the times—don't keep policies from 1999. Of course, I'm not saying to change things constantly or flip-flop. Companies need a 'guidance system,' not just a sentence or a notice, and then it's done!

Common Methods for Sales Data Analysis Generally, analysis is conducted from two dimensions: 1. Product. Focus on each product, including sales, price, inventory, promotions, market share, etc. Identify problem areas and problem customers. 2. Customer. Analyze by customer or region to see which customers have performance anomalies, find the real reasons, and identify improvement points for better target management.

Sales Volume Analysis The simplest, roughest data is: whether sales targets were met and the completion rate. But it's more than that. Performance Achievement Daily data: Analyze issues in the day's sales. Daily data is for reference only. Basic data: Monthly cumulative sales progress compared to time progress. Shipment data: This is often overlooked by manufacturers. Shipment data can reveal logistics, inventory, and turnover issues. So, be sure to understand the number of customers shipped to and shipment frequency, identify reasons for reduced shipment volumes, and optimize logistics costs. Analyze this monthly or quarterly.

Comparative Analysis You can't avoid 'year-over-year (YoY)' and 'month-over-month (MoM).' YoY compares data at the same time point in similar periods. For example, March 2017 vs. March 2016—both March—is a YoY comparison. MoM compares adjacent time periods. For example, May 2017 vs. April 2017 is a MoM comparison. Using MoM Honestly, MoM isn't commonly used because sales are highly seasonal, with peaks and troughs. Anyone who says sales don't have off-seasons is just brainwashing! Even if you sell rebar or coal, the government has macro-controls! So, monthly MoM has too much seasonal influence. Why not do weekly MoM instead? Weekly MoM has some reference value, provided there are no holidays between the weeks. For example, comparing Golden Week (early October) with the second week of October isn't appropriate.

Competitor Comparative Analysis I don't need to explain this—you all know it better than me. But many people can't figure out who their competitors are! In principle, any brand in your industry is a competitor. But that's what books say; in reality, you can't treat everyone as an enemy—are you starting a world war? A goal you can't focus on is a dream, not a goal! Remember that—it's a sales iron rule. Who Are Your Competitors? Here's a simple method: Find a competitor brand you can reach out and grab, one that's within your grasp, and whose sales are 30% greater than yours. Focus on that brand and go for it! Don't challenge an 'elephant' that's N times bigger than you. You can treat the 'elephant' as a dream or vision, but first, take care of the 'present.' Otherwise, you're aiming too high and falling short. Once you've identified competitors, what do you compare? In principle, all your sales data should have competitor comparisons alongside. Only then can you know yourself and your enemy to win every battle! This tests your 'intelligence capability' in data collection.

Product Sales Structure Analysis For example, analyze price points and inventory adjustments to understand key product sales. Also, analyze the company's key products, identify issues, and provide recommendations. Be sure to clarify for salespeople:

Which are the company's 'fist products' (to hit competitors head-on, like Popeye with spinach). Which are the 'steamed bun products' (to fill your stomach). Which are the 'cornbread products' (just to get by).

Expense Analysis Expense analysis is generally not for frontline salespeople; it's mostly for regional managers to focus on! I'll add: Regional managers should treat 'basic finance' as an important course to study. Return on Investment (ROI) = Total Output Revenue / Total Cost × 100%. As a manager, when handling expenses:

  1. Focus on the big items and let go of small ones; don't dampen morale.
  2. Delegate authority; one person shouldn't have the final say. Expenses controlled by a single voice are bound to have issues—check it out!
  3. Settle accounts after the fact; every expense needs this step to avoid becoming a 'messy account'! Salespeople can't excuse missing sales targets just because sales expenses are low.

Channel Analysis Analyze supply price, gross margin, and profit for each channel, and be sure to compare with competitors. Classify and tier each channel, then allocate different sales resources (distribution, inventory, logistics). Write down channel issues with numerical support. Pay special attention to inventory in each channel, especially inventory turnover days. Turnover days = Current Inventory Quantity / Current Daily Average Sales Quantity. Judging whether a product is selling well based solely on turnover days is biased. For example, if sales remain constant, larger inventory leads to longer turnover days; conversely, smaller inventory shortens turnover days. So, don't just look at turnover days—combine it with inventory levels for accurate judgment. Analyze inventory composition, and ensure computer data matches actual inventory. Don't rely solely on computer data; conduct regular stocktakes to identify issues promptly. Only then can you grasp the sales situation of each SKU. Focus on which regions and channels are performing, and analyze development trends and sales characteristics. Pay special attention to regions with significant growth or decline to avoid potential threats, beware of competitors exploiting weaknesses, and conduct multi-dimensional analysis.

Personnel Analysis Include the number of new employees (cumulative this year), departing employees (cumulative this year), performance per employee, salary costs, and daily work analysis (distribution, visits, etc.) In sales analysis reports, avoid these issues:

  1. Most people report work by dodging the real issues, circling around problems, and highlighting only successes. The dumbest employees think 'your boss and boss are idiots.'

  2. Misreporting: downplaying important issues and exaggerating minor ones. This trick is used masterfully by seasoned salespeople to extract company resources for personal gain. I strongly suggest that if a report lacks specific analysis and only states facts, leaders should not make decisions, as this can easily lead to errors.

  3. Focusing only on frontline battles while neglecting team internal improvement, causing mismatched internal and external resources. Such salespeople may be flash-in-the-pan. They're suited to be snipers, not managers.

  4. Making plans without analysis, relying on gut feelings—a common pitfall for many managers. Sales analysis reports become a mere formality.

A good sales analysis report should have:

  1. First, data must be presented truthfully, completely, and in detail. Where does the data come from? What does each data point mean?
  2. Data analysis must be objective, without subjective bias, to avoid a skewed report.

Source: 土拨鼠跟我走, 简书经管专栏优秀作者