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Digital has exploded the quantum of data available to decision makers, but the challenge is to move from data to action. For that we need to combine a human level view from small data with a zoomed-out view from customer analytics. Together they form a powerful customer tool.

Our work with clients such as O2, the Financial Times, Lloyds Banking Group and HMRC is at the cutting edge of using small data* and analytics together to drive commercial performance.



*  See, for example, ‘Small data.
The tiny clues that uncover huge trends’
by Martin Lindstrom
(Hodder & Stoughton, 2016).

Analytics are brilliant at allowing us to see what happens, and putting £-values against this.

Small data are brilliant at helping us get close to customers and their lives, to help us understand what matters, and how we might influence this.

But it’s by using the two together that we are able to improve what results.

Integrating small data and analytics gives us a richer, more useful source of insight and understanding than either alone.  Data are brilliant at answering the who, what and how much types of questions relating to behaviour.  But only research can get to the why.

Data allow us to profile, quantify and put a £-value on customer behaviour, at any level of aggregation or dis-aggregation.

Research enables us to explore, and explain the motivations, value sets, etc. that sit behind and drive people’s behaviours.  And, from this, to work out how we can best influence future customer behaviour.

Using small data and analytics enables us to bridge from passively measuring performance, to actively improving it. This involves using the two together to, e.g.:

  • optimise pricing, propositions, products and servicing strategies;
  • inform operational decisions: service improvement, resource allocation, investment prioritisation, etc.;
  • raise commercial performance by: better aligning resources to £-value; reducing cost to win/serve; optimising high/low value customer churn, etc.

By integrating small data and analytics, we can link customer metrics – CX, CSat, etc. – to outcomes such as customer value and loyalty.

We are also able to develop diagnostic and predictive business applications, so customer strategies become oriented to the future, not the past.