CRM success: How to measure it?

By Jay Bauer, President, STI Systems, San Clemente, CA

It is vitally important that you know whether your CRM implementation is tracking toward success or something less.

To do that you will need to:

1. Have an operational definition of success that will allow you to measure it.
2. Identify the metrics you will use to determine if the goals of your implementation are being met.
3. Build a CRM Success Matrix that serves as a tool for establishing your current level of performance and for setting quantifiable goals for making improvements.
4. Understand which of these metrics can be used at various stages of your CRM system's life cycle.

Focus on Revenue and Productivity Increases

Companies can use a number of metrics for gauging CRM success. Two of the best are (1) Increase in Revenue and (2) Increase in Productivity. Both are inter-related. Tracking the first is straightforward and easy. The second is both difficult to track and to score, but essential none-the-less.

Productivity improvements of 2% to 15% will yield impressive revenue increases. A modest target of 10% is readily achievable in most instances. Once you have set the productivity target, revenue increases are easy to project.

Of course, you cannot measure increases in revenues or productivity without a baseline. Companies know what their revenues are, so that baseline is easy. But how do you go about determining your productivity metrics and setting baselines for them?

Build a CRM Success Matrix

In most companies a small percentage of existing personnel are actual revenue producers. Gather as much intelligence as possible on their activities (as well as on their management and support staffs.) This information will be the basis for the CRM Success Matrix that will tell you how efficiently your revenue producers are working and where productivity can be increased to generate additional revenue.

Data on a wide range of CRM productivity metrics should be collected and cross-correlated. Some examples: ratio of phone calls to in person meetings; ratio of closes to proposals; suspect to prospect ratios; time frames, including start and end times for each customer relationship phase.

 Most organizations find, when they begin collecting the data, that much of it is missing. They may need to make provisions for collecting it as part of the CRM design process. Once the CRM Success Matrix has been built, it can be used both for monitoring real time activities and for creating what-if scenarios for setting productivity improvement goals and predicting revenue increases that can be associated with them.

Target Productivity Improvements

Here are some examples of the elements you can track in your CRM Matrix to determine if you are achieving success.

• Number of Accounts Managed: If under your current plan representative are managing 400 accounts, it wouldn't be unreasonable to expect them to manage an additional 40 accounts on average across your organization.
• Weekly Meetings: If your average weekly meetings across your organization are two per rep you might expect that number to increase to three a week.
• Close Ratio: If your average close ratio is 4.o per ten proposals, you might expect an increase to 4.4 per 10 proposals.

Soft Targets Also Important

Some of the other measures of success are softer than the measurements described above, but may be of equal value to your business.

For example: What impact can the implementation have on the management team?

• Provide more information on the individual performance of the representative.
• Allow the management team to concentrate on the problems instead of general broad-brush management techniques.
• Reduce turnover, which impacts a broad range of additional issues, including: staff productivity, lost opportunities, customer retention, operating costs, etc.
• Reduce the time it takes to get a new representative productive in his or her territory.

When to Measure

Depending on the quality of your organization's initial data, you should tier the process of capturing and evaluating success metrics. Don't start too soon. It will take 3 - 6 months for the staff, once you have implemented the system, to be proficient with it. Any attempt to measure success during this time period is difficult and could be considered dangerous to the overall health of the project.

You will need a good solid 6 month's to a year's worth of data to compare with your original data before you can make any meaningful determination of how well your project is succeeding. At this point it is appropriate to use the Success Matrix to determine any modifications to your system or measurement standards that may be needed to fine-tune your implementation project for higher levels of success.

Be prepared for some surprises. We have encountered management teams who thought they fully understood their market and what their representatives were doing, only to find out the representatives were doing something totally different. In other cases initial design assumptions about market needs and representative activities were correct, but changes occurred in the marketplace during the implementation to make the system less responsive to actual conditions. So embrace the opportunities revealed by your success matrix and make changes to the system and your measurement metrics as the system matures and your market changes.

One Consultant's Definition

In our view a successful CRM project is one that

• Has been implemented for five years or more
• Is reviewed and updated to meet the changing business requirements
• And has an acceptance rate internally of over 90%.

Acceptance means that, when you ask, users will tell you that the CRM system is necessary for meeting their objectives and managers will say it is necessary for managing their staff.

That, in our estimation, is success. How would you define it? Drop me a note at jay.bauer@salestechnics.com. I'd like to know what you think.

About the Author:

Jay Bauer is President of STI Systems, Inc., San Clemente, CA, CRM implementation consultancy with a success rate substantially higher than industry averages.