Customer Loyalty Leads to Customer Profitability
Most companies that have implemented CRM applications realize that the analytical data available from these applications can provide rich insights into their customers, partners, channels, and markets. It is not uncommon to see enterprises quickly follow up their CRM implementation with a data warehouse that can be accessed via one or more analytics applications. These initiatives are usually driven by marketing departments that are looking for hard data about who their most profitable customers are, which channels are most effective, and what marketing campaigns have been most successful.
Specifically, CRM applications collect data about customers: who they are, what their corporate affiliations (parent/subsidiary) are, where they are located, what industry they are in, the applications they are using products for, and potentially the most important, what they buy and what prices they are willing to pay. If a company creates quotes in their CRM application, data can provide insight into their competitors as well as the deals they have lost. This win/loss data can be used to uncover opportunities that may not have been available pre-CRM. How a company leverages this data may be the answer to how they will realize the return on their CRM investment.
Emerging software applications like profit optimization are cracking this data's code and increasing sales revenue by realizing more profit from flat sales. One of the key components of that code is the ability to understand customer-buying behavior. CRM applications are a rich resource for just such data. Applying sophisticated mathematical techniques, these software applications can help companies analyze this data and better understand the segments of customers who buy their goods and services. And, these applications recommend what prices should be charged for them.
Another way that these applications leverage CRM data is by creating micro-segmented models that allow companies to target specific goods and services, promotions, bundles, and most important, prices to very specific groups of customers. These segmented offers ensure that the customer is receiving the products they want and that the price charged realizes the maximum amount of margin available from that segment. Profit optimization is even enabling companies to judge in a split-second whether or not a sales opportunity is good for the company and immediately recommend counteroffers when the deal is unacceptable.
Traditional methods of analyzing these sales opportunities were a rearview-mirror approach to determining which sales were profitable and which were not. Profit optimization allows companies to be preemptory in reacting to changes in their markets. One global manufacturing company, for example, was able to identify the trend that small distributors in one part of North America had very similar buying habits to large OEM customers in another geography. This insight was based on win/loss data collected in the company's CRM application. Armed with this knowledge, the company made changes to its discount schedules that realized a higher OEM profit margin without losing revenue.
In another example, a durable goods manufacturer was able to see a 5 percent increase in contribution margin using profit optimization on CRM sales and agreement data in real time. By eliminating price variation in distributor agreements, identifying contract non-compliance, eliminating quote-to-order discrepancies, preventing customers from "cherry-picking" contracts, and segmenting customers by geography and application, this manufacturer was able to see a $5 million increase to the bottom line of a $300 million line of business.
Profit optimization applications use sales data created in CRM applications (as well as ERP and supply chain manufacturing systems) and push the reach of this knowledge to other parts of the company that may not use CRM directly. For the first time, people in marketing and manufacturing who are responsible for pricing goods and services, and pricing managers who must approve exception-case pricing requests from the field, have the complete information they require to do their jobs.
The most attractive aspect of profit optimization is a demonstrable return on investment. Many customers have seen a complete return on an optimization software purchase in as little as four months. After the investment has paid for itself, companies realize between 3 and 10 percent increases in margin on goods and services.
Turning knowledge gathered in the CRM application into increases to the bottom line leverages not only the investment in the optimization software, but also the investment in CRM.
About the Author
Daphne Carmeli is cofounder, president, and CEO of Metreo Inc. in Palo Alto, CA.