I use the term ‘Lawyers question’ fairly regularly. I use it to mean asking a question you know the answer to. This is also called a known answer question (Rhetorical or Dorothy Dixer might work). In cross examination I understand that lawyers are trained only to ask questions where the answer is known and benefits their case. I reckon my Lawyer would get a perfect NPS.
Net Promoter Score (NPS) is commonly used as a key performance indicator (with a genuine emphasis on ‘the K’!) in many of our major Australian Businesses. There are a lot of senior executives who keenly examine the results as to whether we would recommend their company and its services to our friends and colleagues. In many of our clients, the NPS survey results are held in Teradata and fed into Executive Dashboards and Scorecards.
I was in a client review recently where we were discussing the many applications that the client’s Teradata Data Warehouse underpins and looking to develop move value by broadening the scope or depth of the Analytics they perform on the platform as well as looking to add new data sources. When we discussed the NPS application they have developed, a conversation followed on how open some staff are, particularly in the call centre, about the use of NPS and that it may be possible to influence the level of service with the promise of a positive NPS survey score.
Stories then unfolded of other companies’ call centre staff disconnecting calls before the survey could be processed with an unhappy client or others who are able to control to whom the survey is sent only letting those that would most likely provide a positive score receive it.
If this is indeed the case, they could assert Campbells Law and state that although not a ‘social indicator’, NPS as ‘the one number you need to grow’ could be on the way to becoming something of a perverse incentive and that, just as Campbells Law predicts, it has become corrupted and is losing efficacy as a valuable metric.
I wouldn’t go as far as Ron Shevlin does in this blog that its “Time to kill the Net Promoter Score” but I would certainly argue that analysis should be performed to both
1) Maintain he integrity of the test.
2) Look for enhanced metrics to address the effect of Campbell’s on MPS.
Some of the comments in Rons blog (it’s a good debate) make the case that in the era of Big Data (and most apologise for using the hyped term!) we should be able to get to the behaviour of clients and understand why they did what they did.
This I wholeheartedly agree with. With a broader range and depth of data in analytic models, including data that is collected and integrated across multiple client facing channels, there is an opportunity to create new metrics or enhance existing ones.
"Customers are creating new metrics based on being able to get to new detail and behavioural patterns in the interactions their clients have with them and understanding how experience of service influences things like likelihood to recommend."
With our customers, we are now mapping, for example the sequence of events preceding an NPS score and have seen remarkable correlation in some paths or ‘experience’ and the NPS given. We have a client who is able to predict within (to use their own words) “an alarming degree of accuracy what the NPS of an individual will be”.
In most cases, businesses have seen that a rise in NPS has correlated with a positive financial outcome so dismissing and ditching the metric isn’t something they are about to do. What they are able to do, however, now that they are able to predict it so accurately is to have a clearer understanding and ability to test causation. This enables new metrics to be created along that ‘path to positive/negative NPS’ such that more clients are guided to the type of experience and service that leads to that key action indicative of a satisfied customer – a referral.
Customers are creating new metrics based on being able to get to new detail and behavioural patterns in the interactions their clients have with them and understanding how experience of service influences things like likelihood to recommend.
Whilst I can’t disclose what metrics they are creating (like all good analytic implementation and insight, it’s key to their competitive advantage) many examples are similar to the concept of Failure rates and moving from an average failure rate to a specific failure rate and the density of those failures.
The Net promoter score equivalent is what Ron Shelvin suggests as the Referral Performance Score (RPS), a way of measuring actual referral as opposed to intent. By the same token as with NPS, if you can see the clients that referred and understand the experience they had and the path they had before they went through to referral you can understand what experiences are more likely to lead to referral, understand what good customer experience looks like and give more customers that type of experience then test the effect on the referral rate.
I believe this is retaining value in the NPS and taking it to the next level. In the complex, multi brand, multinational organisations we are engaged with, understanding and combining that experience across a range of increasingly digitised channels is one of the biggest challenges in place and requires the ability to quickly combine this disparate data, put it in the hands of a business savvy analyst and let them map the experience of the customer across all channels to discover which data provides insight that can be used to inform a change in engagement and a change in the customers experience.
So back to my lawyer and their lawyers questions .... If they were measured on NPS, they would only pass you through to a survey if they knew you would give them a 10!.
NPS is so prevalent in Australia that it has surely touched us all. So some final questions:
- Have you been “NPS’d”?
- Were you aware of it at the time?
- Were you coersed?!
- Most importantly, what new metrics and measurement have you seen developed as a result of more behavioural/experience data being available to inform the process?
Alec Gardner is General Manager responsible for the Teradata Advanced Analytics line of business in Australia and New Zealand, incorporating Teradata Aster, Big Data Analytic solutions and the Teradata partnership with key Analytic partners such as SAS. In this capacity, Alec heads an expert team of Data Scientists and business analysts.