Is your marketing focus product-centric or customer-centric? If you only sell products, it's time to realize that times have changed. With a wealth of products now available, customers look for the most memorable experience, not just the best product.
These days, a fun shopping experience, or no-question returns, often tips the scales over extra product features or a lower price.
As an example, most of the people I know who have switched to shopping online don't even mention the product, but are ecstatic about quickly finding exactly what they need on Amazon, with one-click ordering and overnight delivery, without ever leaving the comfort of their home.
Amazon is very customer-centric, but that can make all the difference in retail as well as online.
One of the keys to a successful customer-centric strategy is understanding and measuring your customers lifetime value (CLV), since customers are definitely not all the same.
I saw some great insights on this in a new book, The Customer Centricity Playbook by Peter Fader and Sarah Toms, who have been thought-leaders in this area for several years.
In addition to quantifying the positives of the customer lifetime value metric, they address the mistakes that I see regularly in my business advisory service relative to assessing the value of customers and value, including the following:
1. Failing to account for current customer status and stage.
Customer status can be one of three states - future new customer, current customer, or inactive past customer. The costs and lifetime value models are different for each of these types, so they shouldn't be lumped together.
Status factors are more important than demographics.
The customer lifetime value also must consider the customer stage (search, conversion, retention, advocate) and the profit you expect in total. Remember that it always costs less to get repeat business from existing customers than it does to acquire new ones.
2. Forgetting to distinguish contractual from other customers.
It's relatively simple to predict subscription-based and other contractual customers, but much harder to project retention and repeat purchases from customers with unpredictable transactions. Thus retention rates have to be adjusted down for non-contractual customers.
All this may sound very complex, but calculating customer values can actually be fairly simple if you have the data and tools. The message here is skip the gut feel estimates, and plan on using one of the many predictive analytic tools, such as Sisence or Azure.
3. Believing customer retention rates remain constant over time.
For a cohort of customers all acquired at the same time, the retention rate for those who stay longer actually goes up over time.
Thus incremental investments are better spent figuring out ways to extract further value from sticky customers at any given point in time.
Stepping aside from pure lifetime value concerns, customer retention is also the best way to measure how successfully your company is providing its solution. In addition, your loyal customers are the best source of referrals as a key source of new customers.
4. Assuming that customers fit a bell curve distribution.
The reality is that almost every CLV distribution curve is heavily skewed to the left, with lower-value customers making up the largest proportion.
These must be pruned out quickly or "fired," with extra effort put in to retain the long right trailing curve of high lifetime-value customers.
For example, you will often find some new customers who want to test your limits by demanding extra service or concessions, leaving you with little or no lifetime value. These need to be excluded as early as possible, to prevent CLV values from being skewed low.
5. Omitting lifetime value beyond dollars and cents.
In many businesses, customer value goes beyond financial considerations. In community organizations (non-profits), the value of volunteering and other positive types of engagement must to be added.
These may be missed by existing tools, and require adjustment to prevent strategic errors.
In addition, in industries such as healthcare, the idea of predicting the CLV also carries some obvious ethical and legal considerations. What are the implications if the best customers are the least healthy? Lifetime value is not intended to relate to length of life.
I predict that one day soon customer-centric strategies, and metrics like customer lifetime value, will be seen as the standard in business management, rather than an exception in a product-centric world.
With the advice in this book, and by avoiding the mistakes discussed here, you can get started today with a big leg up on your competition.