Data

Customer & Marketing Analytics

The analytics behind acquisition, retention and customer value.

Marketing teams usually have plenty of data and very little of it arranged around the questions they need answered: who is worth acquiring, who is about to leave, what a customer is actually worth, and whether last quarter’s campaign did anything.

DeepTeal builds the analytical layer that answers those questions, and the models underneath it.

Areas of work

Customer lifecycle modelling Acquisition, segmentation and targeting, upsell and cross-sell propensity, churn and retention, and lifetime value. Modelled as a lifecycle rather than as unrelated one-off analyses.
Marketing data marts Structuring customer, campaign and transaction data so that campaign and commercial teams can work from one consistent view instead of reconciling exports.
Experimentation and A/B testing Designing tests that can actually support a conclusion: comparison groups, sample size and power worked out before the test runs, and a stopping rule agreed in advance rather than decided once the numbers look encouraging. Measuring outcomes honestly, including when the result is that a campaign made no difference.
Self-service tooling for commercial teams Putting segmentation and measurement into the hands of the people running campaigns, so routine questions do not queue behind an analyst.

A simulated sequential test. Both intervals narrow as evidence accumulates, but for most of the run they overlap and no conclusion is available, however far apart the two point estimates look. The dashed marker is the first point at which they separate. Deciding before that line is where most A/B testing goes wrong.

If this is close to something you are considering, a short description of the problem and the systems already involved is the most useful place to start. Get in touch.