Convergys Case Essay

10224 Words Jan 25th, 2012 41 Pages
Customer Information Strategy

Convergys Case

1. Convergys, a leader in contract-based business process outsourcing services, has been successful in acquiring high-profile customers (e.g. Verizon, FedEx & Starbucks, among others) across a wide variety of industries. Despite Convergys’ impressive customer list, the company has seen its operating margin decrease about 20% over the past 5 years. Key decision makers within the company believe that this decline is due, at least in part, to issues relating to client retention and acquisition strategies.
At present, Convergys classifies its customer accounts into 3 tiers: A, B & C. “A” customers are considered to be of highest value, followed by “B” and “C” customers. Although the idea of
…show more content…
Although Carlson’s proposed metrics could be helpful, other measures, such as profit margin and the evaluation of more dynamic processes might be more useful.
Carlson’s proposed RV offers some unique aspects for measuring customer value by incorporating a “softer” approach, albeit not without difficulty. For example, determining a client’s reputational value is largely a subjective measure, a fact that stresses the challenge of translating this value into a quantitative score, which could seem more like an art than the application of a scientific approach.
The same issues arise when attempting to evaluate a customer’s probability of switching upon expiration of the contract with Convergys. Since these customers have most likely not switched from Convergys before (unless they are “return” customers), how accurate will outside measures, such as industry-wide switching behavior and predicted attrition rates, be in determining the value of this metric? It is plausible however, that Convergys may be able to build a model to determine these metrics, as weighed against the actions of its own clients over a statistically significant time

horizon. Perhaps, other additional “Relationship metrics” could be incorporated, such as satisfaction scores, internal relationships, etc, to generate a more robust predictive index. The marriage of the best aspects of both RV

Related Documents