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How to define and track the right sales metrics

What are the best sales metrics that we should track, and how do we do it?

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As result of "big data" mania, there is an explosion of interest in business intelligence solutions and advanced analytics techniques. In particular, organisations of all sizes want to sharpen their ability to track the health of customer relationship management (CRM) business processes. A common question that I get from my clients is: "What are the best sales metrics that we should track, and how do we do it?"

Recently, my colleague Boris Evelson and I responded to an inquiry on this topic. Our answer is summarised below.

Question:

"How do we set up BI dashboards for a sales-focused company? We currently have Cognos, IBI, and various cubes around a 6 (+) year old Teradata warehouse. We are upgrading our Teradata to its latest technology and have purchased IBI's BI suite to use in conjunction. Our focus is on sales - How did other organisations start out? We would like to know what works best for different roles from the CEO down to an inside sales rep?"

Answer:

We believe the answer to your question relies in adopting best practices around analytical sales performance management. You should take a top-down approach that has five steps:

1.     First, define the overall sales strategy.

2.     Then, identify goals and objectives that you need to achieve in order to make your sales strategy successful.

3.     Next, identify and agree on the set of metrics and measures that you’ll need to monitor on a daily/monthly/quarterly/yearly basis in order to see where you are against your goals and objectives.

4.     Organise metrics by relevant decision areas (see the next paragraph) and by decision types (see Step 4 below).

5.     Last, but not least, identify data sources (your Teradata data warehouse, plus potentially some other data sources) and create processes using data transfer tools to populate and refresh the metrics.

Step 1. While we can’t speak about specific sales strategy and specific objectives in your organisation, typical decision areas that reporting and analytics support include:

    • Sales results. What is driving sales performance?

    • Customer/product profitability. What is driving sales contribution performance?

    • Sales tactics. What is driving sales effectiveness?

    • Sales pipeline. What is driving the sales pipeline?

    • Sales plan variance. What is driving the sales plan?

Steps 2 and 3: For each of the decision areas, create the following goals, metrics, and attributes.

To monitor sales results against:

    • Goals, such as:

  • New customer sales in $

  • Sales growth %

  • # of sales orders

    • You need to monitor metrics such as:

  • Average sales per order

  • Average units per order

  • Customer credit balance

  • Customer credit limit

  • Customers

  • Lost customer count

  • New customer count

  • New product sales

  • Sales order count

  • Units delivered

  • Analyse these metrics aggregates by:

  • Customers

  • Geo regions

  • Time periods

  • Market segments

  • Product lines

  • Sales channels

  • Sales team/org

… and so on for every decision area outlined above in Step 1.

Step 4. Then, you should map these metrics to the types of decisions they support, such as:

    • Strategic (should be relevant to C-level execs)

    • Tactical (should be relevant to VPs and middle managers) and

    • Operational (should be relevant to all individual contributors)

This now gives you the ability to design and create strategic, tactical, and operational sales performance dashboards.

Step 5: Finally, build ETL processes to populate and refresh each metric and build and update the dashboards.

This is just a tiny glimpse into sales performance management process. You may find our report “Define The Right CRM Metrics” helpful. It contains more than 70 examples of sales, marketing, and customer service metrics.

Posted by William Band

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