1. CSI or customer satisfaction (C Sat) indexes. This research usually takes the form of a post event, such as a sale or other transaction, where a customer is asked to participate in a research questionnaire. Typically this is a telephonic interview and involves a number of stepped or bridged questions (i.e. a path is taken depending on answers). Usually questions are graded on a 4 or 5 point scale. The objective is to provide scores based on representative sample sizes that reflect a level of service satisfaction.
a. Pro’s: This research provides an analytical rating based on gaps between delivery & expectations. If consistently applied they can be used to track for continuous improvement.
b. Con’s: CSi can be very expensive and is often too complex and detailed for interpretation by managers and employees. It can be an irritation to customers as it often takes a lot of their time.

2. Net Promoter Score (NPS). Many companies have embraced this tool and use it to replace or complement CSi. It is simple but effective as it uses only two questions, namely: (1) “How likely is it that you would recommend our company to a friend or colleague?” (2) based on the response (which usually uses a 10 point scale) a second question is typically asked. The first question divides respondents into promoters, passives and detractors.
a. Pro’s: Much less intrusive to customers yet gets to the core of the issue – i.e. are customers likely to be retained by the company? Lower costs mean that larger samples can be sought or money can be used elsewhere.
b. Con’s: It is limited by the nature of itself, it is difficult to use to track trends for example. It also takes a very finite view of grading responses, it assumes that Jack’s 8 out of 10 means the same as John’s.

3. Implicit association tests (IAT). Although this methodology has been mainly used to measure prejudices such as race and gender, there exists great potential to apply this to brands (I am working with Beyond Philosophy to do some work in this field). For example we can look at ‘prejudice’ against or toward a brand as well as its traits and characteristics such as service and delivery.
a. Pro’s: Unlike nearly all other research, IAT records subconscious responses rather than logical/analytical responses. The methodology also provides a degree of comparative analysis between brands.
b. Con’s: IAT is very new and results are not well tested, particularly for brand research. The methodology makes it more expensive than NPS.

4. Surveys. This is a big umbrella but the scenario that we are talking about here is ad-hoc surveys used to gather responses from customers. The subject matter might typically include topics such as retention, satisfaction, performance and opinions. These are quite often online surveys or might be print questionnaires. The objective is usually to gather feedback in a short space of time to make a tactical decision.
a. Pro’s: Usually relatively inexpensive and can give you a quick ‘dip-stick’ gauge on customer perceptions.
b. Con’s: Lack the structure to track trends and quite often are poorly constructed leading to poor quality of information.

I have listed a number of points that would contribute either for or against the statement and I’m sure that you probably have a few ideas of your own (Which I’d be interested to hear about);

• There is a danger of running a business on figures alone.
• It is impossible to measure everything that is important to management.
• Because it cannot be measured, does that make it less important?
• What gets measured tends to get done.
• How is the data/information applied, distributed and communicated?
• Poor information can be more damaging than no information.
• There are big dangers of misleading information and even bigger dangers of misinterpreted information.
• Successful strategies rely on high quality information and intelligence.

I believe that the statement has been over-used, usually by agencies that use it as a tool of fear against their clients so that companies continue to throw large amounts of money at research. Yet at the same time I recognise the importance of having data to keep track of scores and positions.

The answer, in my opinion, is that the truth lies somewhere in-between. Why should it be one or the other? That raises the concept of polarity which we can discuss another time.

What do you think?

• Recency – based on the time of the last engagement with the customer. These may be purchases, activities or cases. Or a combination of all or some of these.
• Rate of attrition – the rate of customers lost per cohort (time period).
• Rate of acquisition – the rate of customers gained per cohort.
• Average rate of retention – the percentage of customers retained per cohort or across a number of cohorts.
• Duration adjusted rate of retention (DARR) – is the rate of retention across a number of cohorts with a weighted adjustment.
• Profit or revenue retention – using retention measures as above but adding in profit or revenue to each cohort.

Retention rates

• The simple ratio for the retention rate is the number of customers retained as a % of the number at the start of the cohort.
• The straight retention rate for customers from 1993 , in the year of 1995 is 57.8% (166/287)
• Likewise for customers from 1994 the rate is 41.1%. (308/750)

The Average retention rate is thus;

• Simply put it is the average retention across the cohorts.
• In 1995 the average rate of retention is therefore 49.5% ((57.8 + 41.1)/2)

Then we get a duration adjusted rate of retention.

• This rate accounts for the changes over time of the firms’ rate of efficacy.
• First identify the number of repeat customers per cohort as a % of the total. (See the table below. E.g. 1993 customers remaining in 1995 = 166 or 35% of the total (166/474) (474 = 166 + 308))
• The DARR in 1995 = (57.8%*35%)+(41.1%*65%) = 46.9%

Myth Busters: You can’t manage what you can’t measure
I don’t like this cliché because it is so often exploited in corporate boardrooms by people jostling for position. The implication is usually that if something can be easily measured it is ‘better’ than something that can’t be measured easily or at all. This gives rise to what people refer to as the soft issues.

Let’s first take a look outside of customer service and experience. Ergonomics, style, elegance and sophistication are all attributes that are very difficult to measure. Even if we use people’s perceptions as a basis of measurement we might find out if a product seems to be ergonomically better than another. But we are very unlikely to be able to accurately quantify it. Yet it is these attributes that set a product apart from its competitors.

Likewise the case is similar with customer service and experiences. You may go to a popular fast food restaurant where you are greeted with a rehearsed welcome and farewell. Do you take this interaction to heart? Of course you don’t. There is no authenticity or sincerity. However, when a person communicates with you and demonstrates some interest in you then your response is different.

Can you measure authenticity, enthusiasm?
Can you manage these things?
Damn right you can.