Measuring for success
By Kenneth Hitchen, Consulting Director, Sabio
They say you are what you measure, and that’s bad news for a customer service industry that has spent far too long concentrating on quantitative metrics that focused excessively on the average. However, the problem with average metrics is that they tend to hide inconsistent performance - concealing variance, and making it much more difficult to improve key measures such as quality and adherence.
We all recognise the classic contact centre performance report – it’s quantitative because that’s the format our ACD generates. Many organisations just accept these figures, and – providing they’re around the 80/20 mark – assume everything is OK. But quantitative assessments don’t always provide the insight needed to move an operation forward. With average information, contact centre managers simply aren’t being driven to ask critical questions such as ‘what data is required for change?’ and ‘how do you acquire it?’
Today it’s far more important to focus on more relevant, customer-focused contact centre metrics – such as Net Promoter Scores, social networking comments, real time customer feedback, and balanced scorecards – that succeed in matching quantity with a qualitative performance aspect.
Organisations don’t have to look far to find a measurement approach that could work for them. It could be post call IVR or feedback survey solutions, datamart mining, ACD statistics, balanced scorecards from a vendor such as Verint, or intelligent reporting approaches such as IQ from Avaya.
Moving towards more granular metrics
A good start is to seek out more granular metrics that will allow you to identify performance exceptions, and adopt an approach that shifts towards a more balanced set of metrics. By measuring over time, you can start to look into more meaningful metrics such as quality scores based on call samples – and then use these exception-based metrics to build Balanced Scorecards featuring essential performance drivers such as First Contact Resolution and customer satisfaction.
Once these core operational metrics are in place, contact centre managers can apply the same approach to other customer service elements, including customer contact history, self-service, customer feedback and agent classification. With contact history data, for example, managers can move from logging summary quantitative data on call volumes to keeping notes on individual customer records. They can also start to look at customer contact histories across multiple channels, storing the data within a more accessible business application, with the ability to access contact details on an ad hoc basis.
The next stage would be to put a more in-depth contact centre datamart in place across all channels, with recordings of actual transactions and details of interaction outcomes. You can also apply the same escalation of metrics to the self-service process. Perhaps initially only recording high level volume data on the numbers of customers or transactions flowing through the web and IVR self-service channels.
Customer feedback data also plays an important role in providing an external counterbalance to internally generated records. You can start the process with quarterly customer satisfaction surveys that cover all aspects of service. The next stage is to gather more data, maybe with monthly surveys or by setting up a customer panel that lets you gather feedback around new products or changes to your service. Looking more deeply, organisations can progress to post interaction surveys across all channels, gathering customer viewpoints, incorporating social networking opinions as well as customer satisfaction surveys and panels.
It’s also important to gather data from the agents. It’s surprising how many contact centres don’t actually log post contact classification data around the reasons for a customer’s contact and its outcome. You can start with simple categorisation in a standard business application, collecting reasons for a call and providing the ability to search and report on this field.
Establishing analysis and reporting processes
There’s no point collecting all this data unless you do something with it. First stage reporting lends itself to regular manual reports that can be sent to contact centre stakeholders with high-level summary metrics. Progressing forwards, regular automated reports that feature a balanced spread of service metrics can be broadcast to stakeholders at regular intervals. A more advanced reporting process would be to deploy analysis and reporting tools – such as the latest speech generation tools - to allow more complex queries to be made against specific transactional data.
A business that makes sure its agents are performing efficiently, that takes note of what its customers are calling about, that asks them for their feedback, pays attentions to how their brand is being discussed on social networks, and actively measures their customers’ propensity to recommend their service to others (using Net Promoter Scores), is much more likely to be getting things right and moving forward. The right measurements really can make a difference.
www.sabio.co.uk
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