2013 Bronze Best Online Display Advertising

Client Which?

How did the campaign make a difference? Understanding online audiences presented a significantly different challenge for Which?, requiring an innovative profiling approach with new data segmentation and analysis solutions. This delivered invaluable insight into the audience profile, for evolving optimisation and target refinement.

What details of the strategy make this a winning entry? Which? has never been short on user insight: customers are discerning detectives always seeking expert advice, looking to make the most informed decision. They're ambitious sense-checkers, needing guidance on practical things, such as choosing a tradesman, or are socially active safety-netters looking at those with similar experience for reassurance. While developing the Which? acquisition model through online display, it was felt that a deeper understanding of who these people were, and where they could be reached, was needed. A new strategy aimed to build this profile by setting out on a Which? user doppelganger search. It involved implementing a comprehensive tagging system, collecting cookie data from across the Which? site and using it to analyse and model typical converter behaviour. This data allowed for sophisticated prospect targeting to find trialist lookalikes, concentrating on audiences most likely to convert, reducing wastage and continuously feeding optimisation.

How did creativity bring the strategy to life? The strategy involved abandoning routes previously considered gospel and testing a completely new approach. It enabled Which? to evolve display into a standalone acquisition mechanism, and at the same time learn more about its online audience. Instead of employing a complex channel mix, one single strong channel was selected to generate robust audience insight. Part of the solution was employing Quantcast's profiling algorithm, using extensive site visitor cookie data to feed its lookalike targeting model. The model then analysed Which? converters' online behaviours, mapping them against Quantcast's vast user datapool to discover lookalike pockets. The algorithm looked at search behaviours and content consumption, which revealed some unexpected findings, such as a strong parenting element and interest in white goods. Unexplored channels, such as religious sites, opened up a new potential audience.

Results Initial low-weight testing produced remarkable results in a relatively short time, so activity and budgets were expanded. This generated a cost-per-trialist over 70% lower than the last mixed-channel display campaign and challenged the traditional display nemesis of PPC across some categories, such as electronics.