1 to 1 Magazine had an interesting article on matching customers and agents in different call centers (“Customer Service: Matchmaking in the Call Center“)
Skills based routing, i.e. the concept of routing customers to agents based on the customers’ needs and the agents skills, has been around for several years already. The idea of having the right agent, at the right place, at the right time is very intuitive and appealing, yet is not as simple when it comes to its implementation.
For many years, the main difficulty was how to best route customers given that we know the customers characteristics (and problems) and given that we know the skills sets of the agents. For example, if a customer speaks Spanish he can be served by agents that speak only Spanish and agents that speak Spanish and English (say). The main issues are: (a) the more skilled the agent, the more expensive he or she is, and (b) determining the actual priority rule that ensures that all customers receive adequate service.
In the above case, the skills are well defined. Interestingly, most of this literature disregards the fact that in many cases, the skills themselves are not simple to define.
The article focuses on different strategies firms use to match the right customer with the right skill…or attitude:
According to Hardy, some companies that are finding success in their contact center matching strategies give online psychographic tests to agents, record interactions with customers, and combine that information with psychographic data to better understand and predict optimal matches. “To be able to refine and mange the [customer-agent] profile has become key,” she says. “We see this model transforming the way in which businesses operate, using it to ensure that they [have] the right leaders in place, managing the right staff, and keeping the staff engaged at all times.
So the first thought that crossed my mind was that probably someone listened to my customer service calls and figured out that I am a pretty annoying customer (just read the rest of my postings). Then, assuming that I am indeed a fairly annoying customer, I will be matched with the worse agents. Why? It is well known (see Prof. Anat Refaeli’s work) that angry customers put a lot of mental pressure on agents, and increase turnover. So, if the firm likes to retain its best agents – it should avoid matching them with annoying customers. Using this strategy, the firm will alienate its worst customers (those it does not mind losing anyway) and will increase the turnover among its worse agents (those it does not mind losing anyway). Sounds like a perfect solution to me (of course, as an ops professor, and not as an annoying customer).
The article discusses also other matching methods. The University of Pittsburg Medical Center (UPMC) relies on geographic data to match its members to their personal concierges. But they do not stop there:
UPMC ensures that the concierges are continuing the personal relationships when they conduct outbound calls to their assigned members for such customer-focused initiatives as calling them on their birthdays, alerting members of changes in premiums, educating them on benefits, helping to schedule appointments, and even taking preventative care measures such as letting them know whether they’re eligible for a glaucoma screening. Palmerine reports positive results since deploying the agent-matching strategy. The organization is in the midst of open enrollment and it expects to see 15 to 20 percent growth over last year, and customer satisfaction already has increased from 89 percent to 91.8 percent.
I am not sure if these numbers are significant, and how they are measured, and it is also not clear what the additional costs are. Increasing satisfaction levels from 89% to 92% is ok if comes for free, but I doubt it does. In short, I like the ideas, but I think we would like to see a more rigorous analysis of the viability of these solutions.