A full SCV is usually achieved in market sectors where frequent customer interaction sits alongside real-time transactional and behavioural data. Typically, a customer uses one main provider (eg, mobile telecoms or subscription TV) and the resultant rich data can generate a detailed customer understanding to underpin CRM programmes.
But in situations where customer interactions are less frequent, the data can only provide a partial picture. You can have an SCV, but will have to accept it won’t be perfect. A much clearer upfront strategy is required and greater discipline is needed to set objectives. For example, realising data will only be indicative rather than a perfect customer description at an individual level.
The compromise could be on recency, accuracy, coverage, or a combination of these factors. Determining the compromise is dependent on the objectives of the project and available budget. In this way, the new compromise SCV is agreed with clear understanding.
Recency will apply mainly in market sectors where customer interactions are less frequent and the most up-to-date situation may be unknown, eg, automotive – where was the vehicle last serviced? To counter this, a compromise SCV, more limited in scope but able to provide results focusing on answering objectives, can be developed to deliver on specific business targets. This may necessitate categorising customers based on a specific time when a more complete picture of them was available. We are in an imperfect world of missing and inaccurate data, so it is about creating the right balance.
In terms of accuracy internal data, however well integrated, can remain insufficient for understanding customers. It may need enhancing from external data sources such as lifestyle data or online surveys. Data matching in these circumstances may be better applied on a segmented basis, rather than one-to-one. Whether this represents SCV is debatable, but the same steps of integrating all data sources of potential value still applies.
It may be that only a small proportion of customers have data populated in fields relevant for the campaign objective. For example, you may want to learn from customer complaints which areas to focus on to improve customer satisfaction, but complaint data may only be present for 5 per cent of customers. A further set of records for non-complainers should be used to compare and contrast.
So well-planned steps are needed to create an SCV specific for the task in hand. It doesn’t have to be a perfect solution. As marketers, we should all engage in single customer thinking, using the data available to ensure SCV successfully underpins CRM programmes.
By Simon Steel, head of insight, Eclipse Marketing