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5 Common sales metrics

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Often, when companies look to integrate business intelligence processes the first department that systems are applied to is sales. By employing metrics that track sales activity and any sales-related activity, business owners can gain a better picture of overall success. The problem is, it can be tricky to pick which metrics to track. To help, here are five of the most commonly tracked sales metrics.

The sales pipeline

This metric is often employed by businesses to show current sales opportunities and estimate the number of sales or revenue the sales team will bring in over a set period of time, usually a couple of months. When employed correctly, team members are better able to track and remain in control of their sales. Managers can also be assured that targets are more accurately set and reached.

When companies set up their sales pipeline metrics they often set out to measure:

  1. Average time deals remain in the pipeline.
  2. Average percentage of converted leads.
  3. Average worth of every deal.
  4. The number of potential deals in the pipeline.

Overall sales revenue

This metric is often seen to be the most important sales-related metric to implement, largely because it provides managers and owners with a good overview of the health of their company and overall performance. In short, sales revenue allows you to accurately view the profitability of your business, even if your profits aren’t presently growing.

Beyond giving a useful whole-business overview, this metric can also uncover exactly how much each sale influences or contributes to the bottom line. This can be calculated by using the standard profit-ratio equation – net income over sales revenue.

Accuracy of forecasts

Any sales manager knows that forecasts are just that, predictions. But, because so much of sales is based on informed speculation it is important to track the overall accuracy of any future forecasts. By doing so, you can uncover gaps in processes and reveal any forecasting tools that need to be improved.

From here, you can track improvements and tweak forecasts to ensure that they become as accurate as possible. After all, if you can show that you are meeting your goals, or are close to meeting them, you can make more reliable decisions and be assured that your company is doing as well as it appears to be.

Win rate

The win rate, also known as the closure rate, is the rate that shows how many opportunities are being translated into closed sales. Because this rate looks at the number of sales, you want it to be as high as possible, especially when you look at the time your sales team puts into closing sales.

While a high rate is preferable, low win rates are also useful largely because they can highlight areas where improvement is needed. For example, if your team has constantly low win rates across the board, then it could signify that there is a need for more training on closing sales, or that sales staff may not be knowledgeable enough about the products or services being offered. A fluctuating rate could show increased industry competitiveness and highlight when a sales push could be beneficial.

Loss rate

The loss rate can be just as important as the win rate, largely because it focuses on how many potential customers did not purchase products and/or services from you. It can really highlight problematic areas in the early sales process. For example, by tracking the loss rate you may be able to see that response time is low, causing potential customers to walk away.

Essentially, when measured correctly, you can use loss rate to improve the overall sales process and hopefully bump up your overall win rate. You can also compare the two rates to really see how big of a gap there is and give your team a solid goal to try and find ways to reduce this gap.

If you are looking for solutions that allow you to track and measure your sales and any other data you generate, contact us today to learn how we can help turn your data into valuable, viable business information to lead your company to better success.

Published with permission from TechAdvisory.org. Source.

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Varay

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