Comment la créativité basée sur les données peut-elle aider à identifier de nouvelles opportunités pour la stratégie créative ?

There's no such thing as 'non data-driven creativity'. Using data to inform creativity isn't enough. You have to make leaps, look for the gaps, look at the reason behind the data. Creativity has to have a leap. Otherwise it's just best practise.

My agency leverages data-driven creativity constantly. around 6 months ago we were asked to enhance a beauty salon's brand presence in Barcelona's competitive market, our agency turned to data-driven creativity. We tried to look at local beauty trends and customer feedback, we identified a rising demand for Eastern European beauty procedures. Using this data, we tailored the salon's offerings to include treatments that were popular in Eastern Europe (ex. Russian manicures). We then created campaigns targeted to these specific services. Which led to 9 new bookings for that procedure in the spread of 1.5 months.

I usually create the templates according to the project. I find it a very good way to kick off a new project, generate engagement, and promote collaboration. After explaining the goals of the project and writing an agreement that will guide the dynamics of the group, building the template to collect and filter the relevant data is a very nice next step.

Data-driven creativity fuses analytics with imagination, revealing untapped avenues in Creative Strategy. By analyzing consumer behaviors, preferences, and feedback, creatives can tailor content that resonates deeply, ensuring messages hit the mark. Trend analysis identifies emerging patterns, guiding timely and relevant campaigns. A/B testing refines ideas, revealing what truly engages an audience. Sentiment analysis offers insights into emotional reactions, helping craft compelling narratives. When data informs creativity, it illuminates blind spots, reduces guesswork, and propels innovation, enabling strategists to navigate the dynamic marketing landscape confidently and effectively.

For paid social, breakdown creatives into hard and soft metrics. Hard Metrics are those that are directly impacting on your bottom line (e.g. Cost Per Acquisition, ROAS). Soft Metrics are those that can help us to diagnose the ad itself (e.g. Hook Rate, Hold Rate, Engagement Rate). Always prioritize hard metrics first when it comes to paid social and then look at soft metrics on how we can further optimize it only if it has already hit our hard metric goals.

Data-driven creativity can be powerful, but when over-relied upon, it risks stifling innovation and overlooking nuances. It's imperative to strike a balance, using data as a guiding tool while still valuing human intuition, cultural contexts, and the serendipity of raw creativity.

It's so easy for us to fall into our own biases. Aside from the psychological bias (e.g. Choice Supportive Bias where we have the tendency to find relevant data to support our stance)... Simpson paradox can come into effect where an association between two variables in a population emerges, disappears or reverses when we break down into sub-divided populations. For example, 1 creative might work well at an overall level but if we were to break down into genders, it might only work for male.

For paid social, we would need to consider different data sources (e.g. Paid Social Platform, Store Data, Data Aggregate Platforms such as Triple Whale) to identify the data discrepancies and account for those differences. As consumer journey are incredibly complicated, don't always rely on 1 specific platform for your decision making for creatives.