The Two Most Meaningful CRM Reports

CRM systems are where the richest data about customer relationships is supposed to live, and most CRM systems provide a report-writing system as well as dozens of canned reports. As I wrote last week, reports immediately expose data quality problems and some of them can provide dangerous misinformation.

This week we're looking at the reports that really do make a difference in managing your business. But first, let's look at the foundation: meaningful data.

Let's Assume Data Hygiene

I'm sure it's safe to assume that nobody reading this article has any problem with dupes, phantoms, inaccurate field values, or systemic problems with data quality. So I'll go ahead and assume that.

But seriously, nobody achieves 100% data quality. As I wrote here, perfectionism in data is prohibitively expensive, and those last few percent yield asymptotically less real business value. In the real world, we can live with 5 to 10 percent data impurity, particularly if we know which parts of the data have lower quality than others. (Hint: calculate a data confidence index for each record, and include it with the records to help temper analytical conclusions).

The Meaning Police

Three areas where central IT can add real value to CRM systems are:

1. Controlling the data definitions and system object model to achieve the most consistent semantics.

2. Purifying the data on a regular basis to remove pollution and troubleshoot systemic sources, whether caused by flaky business processes or buggy integrations.

3. Writing reports so that users don't get tripped up by misunderstandings and logical fallacies.

The marketing and sales folks — those pesky right-brained CRM users — are not going to get this right themselves. Trust me, they'll thank you for this as long as your team is halfway responsive.

Valuable Report Area #1: Customer Service

If you've got your order expediting, help desk, or tech support function using CRM, a terrific amount of information can be fairly easily and accurately measured. When an inbound call comes in, your automatic call director (ACD), interactive voice responder (IVR), or even soft-PBX system can start sending customer and call info into the CRM. If your system is equipped with "screen pops" and other features that make the support peoples' job easier, they'll naturally enter in information about what the customer's problem was and what the path to resolution is. Integrate the CRM with your e-mail system and Web portal, and you'll effortlessly get tons of information about the specifics of the problem, how many touches were required to resolve it, what documents are the most useful to problem resolution, and what the ultimate time to resolve was. Add a survey system to the end of your support process, and you get immediate feedback from the customer about the service quality, general satisfaction, and willingness to recommend.

Since almost all your service interactions will be with customers, you'll have good data for cross-referencing and segmentation. You'll instantly be able to approximate the cost of escalated bugs and service-level agreement (SLA) violations, even if the CSRs aren't logging timecards in the system.

While some of the metrics may be somewhat arbitrary (e.g., number of calls handled per hour), here are some very meaningful reports and dashboards that can be created from the CS data:

• What is our most error-prone product (the product isn't broken, but you get lots of calls from first-time users)?

• What product has the highest service costs, and what are its top 3 problems?

• What is our most profitable service offering?

• Which products yield the highest and lowest customer satisfaction?

You're on pretty solid ground with CS-driven reports as long as you don't try to link customer happiness back to the sales process: just because a customer is satisfied doesn't mean they have a need to purchase anything new within a given time period.

Valuable Report Area #2: Order Operations and Fulfillment

In most companies, order operations is a forgotten backwater. It's just assumed to work. But the quote-to-cash business process can be amazingly complicated, full of opportunities for errors and waste. Add in eCommerce and sales channels, and there's tons of hidden information about your products, customer behavior, and your sales organization.

Order operations and fulfillment is ripe for data mining because it's practically a closed-loop system, and you don't deal in speculation or opinion. You got the order or you didn't...you shipped it right or you didn't...it was profitable or it wasn't. The hard part of these reports is the integration of order flows and accounting information across e-commerce, ERP, aAccounting, and CRM systems, but the leverage comes from the unique keys that are available for nearly every object and record.

Here are the kinds of reports that can come from a well-oiled order ops business process:

• Who are the most profitable customers, and what do they buy?

• What are the products causing the most shipment and returns problems?

• When is the channel discounting the most, and what incentives or programs do the best job of counteracting it?

• What products do our repeat customers buy most?

You'll notice that neither of these great report areas touches on sales and marketing — what most people consider the "home base" for CRM's value added. Now I'm a card-carrying member of the right-brained group, but even I have to admit that there's a lot less certainty about data relating to the decision/purchase cycle than the fulfillment/consumption/service cycle. In order ops and service, you'd never hear a quote like John Wannamaker's quip: "half the money I spend in marketing is wasted — trouble is, I don't know which half."

David Taber is the author of the new Prentice Hall book, "Salesforce.com Secrets of Success" and is the CEO of SalesLogistix, a certified Salesforce.com consultancy focused on business process improvement through use of CRM systems. SalesLogistix clients are in North America, Europe, Israel, and India, and David has over 25 years experience in high tech, including 10 years at the VP level or above.

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