How to measure First Contact Resolution?

In the first article from this series, I depicted First Contact Resolution (FCR) as a crucial indicator, which properly measured and improved will bring value to both organization and the customer. It’s kind of a 2 in 1 product — on the one hand, it influences satisfaction of customers and on the other, it enables a company to optimize operational costs. Definition of FCR is easy… but that’s where the easy things end. ;)

First Contact Resolution can be measured in several ways and in this article I will tell you more about these options. The value of the indicator should take into account multiple sources of information as well as different communication channels. None of them alone will provide, in my opinion, an adequate level of objectivity or suffice to obtain sample enough big at reasonable costs.

So let’s consider the options

Self-evaluation by agents

This method is cheap and easy in implementation and can easily provide a big sample. The role of an agent is just to state whether, in his opinion, the case was solved successfully at first attempt. However, it’s strongly dependent on agent’s evaluation, which can be very subjective.

Bottomline: big sample, cheap but often biased.

Customer says

Sometimes the customer directly notifies that this is not his first attempt about the case. “I contacted you earlier about it…” and “I used solution from the website but…”. In such situation, we should advise our agents to mark such case i.e. in CRM as a repeated contact. We can now have a rough estimate of resolution rates. To minimize the bias and ensure the measurement the agents, if customer does not state so, ask him whether he tried to solve it earlier and contacted company somehow before.

Bottomline: Right perspective, possibly low bias, and middle to the large sample.

So maybe we should ask the customer about their opinion at the end of the conversation directly?

Evaluation will be made from the best perspective and at low implementation costs. But in some cases, the customer may not know if his case was really closed at this point. In addition, again the interface here is the agent. Many customers just will not give you such feedback this way (especially negative).

Bottomline: right perspective (customer) but probably biased small sample.

Quality assurance team

The next option is to give this assessment to quality assurance team that monitors the interactions with customers. In this way, we eliminate subjective view of the agent and choose more objective one — from other employees. This approach ensures proper evaluation of formal standards and preparation of appropriate feedback for agents. At the same time, we can identify potential weaknesses in this process. However, obtaining the sample which is large enough is a really costly endeavor… The advance here is that quality team can go through the whole case resolution to determine its success.

Bottomline: Small sample, less biased and covering the whole process.

Surveys — follow-up

Once again we refer to the customer perspective, providing quick access to feedback information that can be linked to a specific agent. This method gives the opportunity to gain in-depth knowledge and ask open questions. However, for example for phone channel you should remember that it may be difficult to reach the customer and obtain his/her consent and the costs of gaining a proper sample may be correspondingly high. It’s very important to make sure that enough time has passed from a conversation to a survey, adapting it to the customer’s case. If it concerns i.e. updating financial information, we shouldn’t contact customer two days later, but after the customer receives the next invoice. Another option may be the follow-up callback made by IVR or by SMS. Smaller involvement of people lowers costs, but certainly, it will negatively influence the number of questionnaires (people do not like it) and the scope unless you just want to ask “Was it solved?”

Bottomline: right perspective, for calls/voice channel: in-depth feedback possible, but small sample at the high cost.

Automated surveys right after the conversation.

To avoid potential manipulation by agents, surveys should be conducted for a random sample of the conversation and without agents’ knowledge. In this situation, this is not the agent who decides if the customer will take part in survey after the conversation. He may be asked by the system if he wants to take part in a survey before the conversation. This approach, when conducted with a reasonable level of investment, provides fast and data-based access to feedback which is directly linked to a specific agent. Depending on channel such approach might be completed via email follow-ups (rate us or our efficiency), sms (was your case solved?), during chat (give thumbs-up) or after a chat (post chat survey).

There are of course also other solutions which work as complex analytics systems integrated with CC platform, CRM business systems, quality management systems and feedback. They provide a high coverage of interactions with an almost objective, data-driven assessment. Unfortunately, this solution is often expensive.

As you can see, the key to success is to provide multi-source measurement and construct indicator as a result of two perspectives — the company’s and the customer’s. You have to remember to suit your approach to a specificity of the case in which we contact the customer.

There are still a few matters to consider and I wrote here only about collecting measurement data. Stay tuned for the next posts where I will write more about implementation and success factors when raising the FCR level!

Please tap the clap button below if you enjoyed this post. 👏 👏 👏

For more Customer Care Insights follow us on Twitter, Facebook and LinkedIn.