As the Dunnhumby-Tesco saga and the
developments surrounding big data suggests, customer behavioural data is the
marketer’s gold mine. Some key strengths and benefits of disaggregate
continuous behavioural data are listed as follows:
- The potency of the data is largely due to its complexion — continuous,
disaggregate. Disaggregate data is far more revealing than aggregate data;
therefore, better suited for diagnosing consumer behaviour.
- Size. These databases tend to be large enabling the data analyst
to drill down into proportionately small customer segments. In particular,
transaction data and big data allow for micro segments, or even personalized
marketing (e.g., targeted promotions and communications).
- Though not always representative of total market, the data is
highly actionable. It allows for the execution of tactics at the customer
segment level and at location — i.e., store or bank or website, etc.
- Provides deeper understanding of consumers’ buying behaviour.
Whereas aggregate data for instance, can compute metrics like market share,
disaggregate data goes a step further revealing breadth and depth of
consumption, brand loyalty, switching behaviour, purchase baskets and so on.
- Reveals not only current and historical behaviour, it can also
predict future behaviour. For example, techniques based on disaggregate data
can accurately forecast market share of a new product soon after its launch.
- Estimates growth as well as the sources of growth. (Disaggregate
data reveals switching patterns. Refer to gain–loss analysis in
Chapter Consumer Analytics Consumer Panels).
- Uncovers the impact of marketing activities in the current time
period as well as in the future. Reveals the long term impact of some of these
activities.
- Reveals most valuable customers.
- The union of people’s physical and the digital world via data
integration,
yields valuable insights that help better target consumers.
- Accurate and complete information provides for greater transparency
and accountability.
