How to use customer lifecyle analysis to drive innovation
Customer strategists, CRM leads and the data scientists that they work with, all have a key role in shaping innovation and ensuring it is commercially successful.
Existing businesses have an innovation advantage over new entrants due to the customer data that they hold and the customer analyses this data enables. Taking advantage of this advantage requires three teams to work together – CRM, data science and product (or the team with overall responsibility for innovation) – with the shared objective of grounding innovation initiatives in data-driven customer strategy.
In this way, the business case for innovation is integral rather than an afterthought.
The need for a new approach to innovation
According to McKinsey’s research, only 6% of executives are satisfied with their company’s innovation performance. Also, in making his case for a Jobs-to-be-done approach to innovation, Harvard Business School professor Clayton Christensen highlighted that 95% (or 19 out of 20) product innovations fail.
Elsewhere, Christensen’s HBS colleague, Josh Lerner, similarly found that the median life of corporate venturing fund is around one year. All of which indicates there is substantial room for improving the rate of success of innovation initiatives.
Inverting the innovation process
Perhaps one reason for the limited commercial success of corporate innovation is that the business case is typically the last item to be addressed. As a collector of innovation frameworks over the past twenty years, I believe it would be fair to say that the majority begin with some form of creative thinking and ideation, then proceed into concept or initiative design and finish with the generation of a business case for what they have devised.
This ordering gives lots of time for people to invest emotionally in the new product, service or business model that they have created and become overly optimistic about what they think it can achieve. Perhaps it is not surprising then that the rate of success is limited?
An alternative approach is to start by identifying financial opportunity and then create the new products and services required to unlock these opportunities – begin the process with an analysis phase before getting creative. By focusing on commercial opportunity, the business case is baked in from the start, rather than icing piped on at the end for decoration and sweetening the case for investment.
Such an approach may not identify breakthrough offerings or business models but will help to ensure the commercial viability of sustaining and incremental innovation initiatives that are the bread and butter of revenue growth.
Identifying commercial opportunity – customer lifecycle analysis
A great way to identify commercial opportunities for innovation is to use customer lifecycle analysis (CLA) – a customer strategy staple.
In its traditional context this analysis is typically used to identify where marketing interventions are required to maximise customer lifetime value. But it can equally be used to identify where innovation efforts should be focused.
For the uninitiated, CLA involves segmenting target customers according to where they are in the lifecycle – e.g. prospects, acquired, activated, loyal, multi-product users, multi-brand users, etc. – and calculating the expected lifetime value of customers at each stage.
The traditional use of CLA
At an aggregate level, CLA highlights the full potential of the existing customer base – how much enterprise value could be generated if all customers were transitioned to the most valuable category – making it appealing to growth-minded CEOs and investors.
At a disaggregated level, CLA identifies the financial opportunity from moving customers from one stage in the customer lifecycle to the next, based on the number of customers in each stage and the incremental value of moving them (e.g. from loyal to multi-product). It also seeks to determine the relative ease of moving different customers through the lifecycle and the costs of doing so.
With some customers, it may not be financially viable to move them to the next stage while others will get there without any intervention. So a key part of the analysis is identifying what early signals will communicate whether the customer can be moved and what intervention (if one is needed or viable) is most likely to work for each customer at each stage.
As such, CLA can be an eye opener. The metrics a business prioritises can often create organisational blind spots and lead to under-investment in opportunities with high potential value. For example, one client we worked with was primarily focused on customer acquisition and it was only once we had undertaken CLA that they realised the scale of the potential uplift from activating customers that had registered but were not actively using their service.
Adapting CLA to identify innovation opportunities
Moving customers though the lifecycle is about growing engagement as more engaged customers are more likely to stick with you and take up new products. In its traditional CRM application, this is attempted using outbound and inbound marketing interventions - prompts, offers, recommendations, etc. But at certain stages, CRM interventions will be a less effective engagement trigger than improving the service provided or creating complementary offerings – which is where innovation comes in.
By highlighting the relative value of different opportunities, and where innovation will be the most effective engagement trigger, CLA defines what customers should be addressed, what the objective with those customers should be and the value of success. This provides a commercially solid underpinning for the next stage in the innovation process – developing a deep understanding of the needs of target customers, which I will cover in a later post.
Key questions for customer strategy and CRM executives
- How are you contributing to your company’s innovation efforts?
- Do you have a driving role or do you think it is another team’s responsibility?
- Have you undertaken CLA or something similar?
- How are you using it?
- If not, what additional value could it add?
- With whom are you sharing analyses such as CLA?
- Do other teams know the valuable analyses you are undertaking that they may be able to use for their purposes?
Jack Springman is Innovation Practice Director for Optima Partners. Optima delivers customer value optimisation, supporting clients in three ways - using data science to drive innovation for customers; developing customer, decisioning and interaction strategies; and delivering marketing transformation initiatives.