It’s intuitively obvious that they should be, but what may not be so clear are which actual metrics you need, and how to connect them to different areas of your business decision making processes.
Let’s take four key ways in which you can take advantage of customer value metrics:
1. High level business planning
Your turnover is equal to the sum of the customer value provided in any period. So, to look forward to how your customer value is going to be provided in the future you need to be able to project from your current customer base, remove those that are going to attrite, and add those that you are going to recruit.
The metric to support this is the average value per customer in each year since they were recruited. So how much value in their first, second third year etc. This allows you to very easily roll customer value forward for planning purposes.
When you start from your planned turnover in say next year, you can then tell how much of that is going to be provided by the exiting customer base, and how much will need to be provided by how many new recruits.
You will also want to apply some assumptions about how value is going to be altered by improvements to the way you look after your customers, and then you will have the basics of a customer-based business plan.
2. Understanding which customer groups provide what level of value
You will be very aware that not all customers are equal when it comes to their level of spend with you.
So, you will need to dissect your average customer value by the type of customer they are. Factors such as age, gender, and product categories purchased can all be used to profile the value of your customers.
The benefit then is that you will know what groups to target your recruitment efforts at.
3. Examining the customer value provided by different channels and media
This type of analysis leads you directly to understanding the ROI provided by different channels and media.
Indeed, we like to use a metric which is the amount of longer-term customer value derived from every £1000 spent in a particular recruitment mode.
You can undertake this at a very micro level, such as individual media, or more macro level, such as a channel.
There is though a caveat; many customers are now recruited as a result of contacts from multiple channels. However, this does not prevent you from looking at the customer value obtained from each recruit for whom the channel has played a part.
4. Where to focus retention?
This is a harder question to answer as your higher value customers will often be the most loyal.
What you need to know is which of your higher value customers are more at risk than others.
For this you will need an individual level predictive model for risk of attrition with which to score customers, and find the higher value, higher risk, group.
– Understanding all aspects of longer-term customer value is critical for every successful marketeer.
– To achieve this, you need a single customer view that can track customer behaviour through time.
– You will then need to be able to obtain the metrics.
– It won’t come as a surprise to regular readers of our newsletters that our customer data platform UniFida has been designed to provide most of the metrics we have been describing on demand.
In some cases further analysis will be required, and our data scientists are happy to help with this.
If you would like to talk to us about how to get the customer metrics you need, then please email to say when and how you would like to be contacted.
UniFida is the trading name of Marketing Planning Services Ltd, a London based technology and data science company set up in 2014. Our overall aim is to help organisations build more customer value at less marketing cost.
Our technology focus has been to develop UniFida. Our data science business comes both from existing users of UniFida, and from clients looking to us to solve their more complex data related marketing questions.
Marketing is changing at an explosive speed, and our ambition is to help our clients stay empowered and ahead in this challenging environment.