"Customer insight' is one of those terms in the marketing lexicon which is particularly vulnerable to multiple interpretations or mis-interpretation. Akin to 'proposition' (or marketing mix) which some marketers treat as if it means product, whilst others use as another word for promotion, customer insight is in danger of meaning all things to all men. In this extract from Holistic customer insight as an engine of growth in the current issue of the IDM Journal, I look at the four essential elements required for true customer insight.
Surprisingly, for a discipline which has been practised in business for over 20 years, there is still no consistent definition. I have heard customer insight described as equivalent to just research, analytics, data or database marketing. Even Marketing gurus like Kotler, Peppers and Jobber avoid defining the term and instead reference component parts like data, analysis and research. To clarify what I mean by customer insight, after over 13 years of creating and leading such teams, I offer this definition:
'A non-obvious understanding about your customers, which if acted upon, has the potential to change their behaviour for mutual benefit.'
Four critical technical areas go to make up such a holistic definition of customer insight.
1. Data quality
Customer data management is a foundational requirement to the work of all the other teams. The quality of any behavioural analysis, predictive analytics or database marketing targeting is dependent on the use of quality data. Data quality also impacts the work of much of today's research. From targeted samples to data capture, data quality is vital. Given that, it is concerning that data teams are too often viewed and treated as the 'Cinderella service' within Customer Insight functions.
2. Analytics teams
The focus of recent hype regarding 'big data' and 'predictive analytics' has more often been analytics teams. Data Scientist roles, although claimed to require more IT skills, overlap strongly with the mixture of SQL programming and statistical skills. Behind the hype and long before it, the role of data analytics teams was essential to understanding how your customers are behaving and how they might behave in future. Demographic and behavioural profiling are still very important to increase customer understanding, complemented by segmentation where appropriate. But forecasting, identification of triggers and predictive models enable targeted actions that will improve customer engagement and value share in future.
Having spoken at a number of analytics conferences this year, the data scientist skill set appears to be in greater demand than ever. I hear many businesses now worrying about recruitment, retention or outsourcing of skilled analysts; even if they don't yet have a clear plan of application areas.
3. Consumer research
Such recent enthusiasm for data and analytics should not cause us to forget, however, the crucial role that intelligent consumer research has played in the maturity of marketing over the last 50 years.
Although there is great power in being able to spot patterns in customer behaviour, or to predict their response, without an understanding of customers' perception of their behaviour, there is a significant risk of mis-interpretation. In other words it is not just enough to know how customers behave, one also needs to know why.
At this point, you might rightly raise lessons learnt from behavioural psychology as to the irrational biases in how we all make decisions, and thus the unreliability of 'self report' to predict behaviour. However, companies can get it badly wrong if they ignore a customer's perception of their behaviour as well as how they may actually be making choices. Effective marketing communication requires both accurate targeting and a design which engages a customer accessibly and emotionally.
4. Database marketing
Sometimes viewed as the preserve of direct marketing businesses, with its long history of enriching direct mail and catalogue companies, database marketing is also a vital skill to realise customer insight. As with most change endeavours, a culture of test & learn is needed to test actions and refine them until an optimal return is generated. Because even if analysis and research converged can reveal an accurate understanding of customers and of the offers and communications that would be welcomed at the right time, without a robust way of testing such a hypothesis, it remains theoretical.
Database Marketing brings the scientific method to bear on customer insight work. Effective control groups, feedback loops, statistical significance and measurement ensure an understanding of marketing payback as evidenced by Shaw & Merrick. As most businesses now operate multi-channel, with through-the-line media mixes, this discipline has expanded to benefit from econometrics and other more complex measurement techniques.
Building the engine
It is vitally important to keep customers engaged at every stage of the purchase journey; from engaging the right customers in the start of the relationship through to building loyalty and winning brand advocates.
To learn more on this topic, consider the IDM's Customer Insight training course.
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