SCHEMA® toolset. In each blog he reveals some of the thinking behind the individual practices that make up one part of the SCHEMA® Capability Assessment, which is fast becoming the World’s leading customer management benchmarking tool. There are 110 capabilities in the assessment, containing almost 400 individual practices that together provide a comprehensive definition of what ‘Good’ looks like in today’s “Customer World”. It is this definition against which organisations can be assessed and benchmarked.
In the “KEEP” area of the assessment SCHEMA® has a specific capability called “Implementing Special Care for ‘At Risk’ Customers” and this is what it looks for:
Scoring of all customers for their likelihood to leave
A propensity model has been developed, tested and is refined on an ongoing basis to predict the likelihood of customers being lost, either within a defined time period or at their next re-purchase / renewal. Where appropriate this has been carried out on a product loss basis as well as at the overall customer loss level (i.e. losing their whole business). All customers are scored using the model with this score being updated on a very regular basis using the latest data available and the latest version of the algorithms.
Identification and monitoring for risk-of-loss indicators
Research and analysis has been carried out into the pre-loss behaviours of customers just before leaving the organisation. This will have identified thresholds for changes in ongoing behaviours such as a percentage drop in business levels or increase in returns. It will also have identified specific individual events that predict customer loss such as complaints, pricing enquiries, enquiries about contract terms etc. Responsibility for monitoring for these indicators and triggers has been clearly allocated to a team with access to the right data and analysis tools to carry out this task.
Flagging of customers at risk-of-loss on interaction systems
Customers who are either identified as being of a type or at a lifestage that are more likely to leave or who have activated some form of ‘risk-of-loss’ trigger are prominently flagged on the systems used by staff and channels to support interactions with them. For off-line interactions this will be recognised and acted upon by the relevant staff. For on-line interactions algorithms are built into the supporting systems to use the flag to modify the interaction to some degree, possibly offering an extra ‘one-off’ discount or a faster promised delivery / service visit appointment. In either case the processes are also in place to ensure that system flags are regularly reviewed and re-set where they are no longer relevant.
Flexibility to bend the rules or use ‘random’ acts of kindness
Customer-impacting (not just customer-facing) staff are given the information, powers and guidance that they need to ‘go the extra mile’ in a more tangible form than just by tone and effort. Customers who are identified as being at risk of loss and attractive to retain are flagged as such on the systems used by these staff. Where inbound contact is received from these customers the staff are enabled (within strict limits) to bend rules or exceed limits etc. in order to satisfy them. Where appropriate, outbound contact is made to these people with what appear to them the be ‘random acts of kindness’ such as upgrades, vouchers, extended credit etc. In the design of the rule-bending limits and the acts of kindness extreme care is taken to avoid setting precedents for the future or giving the impression of an on-going entitlement.
For a great illustration of Random Acts of Kindness take a look at this link but imagine if the activity was targeted at customers known to be using or considering other airlines!
