Decoding Data: Transforming Insights Into Actionable Strategies
Today, we navigate an ocean of data, from market to media consumption, pre-test/post-test, digital interactions, audience analysis, and social media reports. But to build a creative strategy, only one will break the surface.
Beyond uncovering this pivotal revelation, the challenge lies in making it rigorous enough for planners, intuitive for creatives, and tangible enough for brands to embrace and follow through.
It’s not what’s out there, but how it connects
A few years back, it was common for creative agencies to interrogate random people through vox-pop street interviews to take the pulse of what people are truly thinking about. Today, while the proliferation of data sources presents new opportunities, it also makes navigating them more challenging and can easily overwhelm a strategy department.
It is important to understand that data isn’t some magic wand we can wave around and transform every number into actionable insight overnight, especially if we don’t want the same insight as our competitors.
It might take time to mine and refine, but by multiplying sources in a clear brief framework, data will help planners go further into their research and gain greater accuracy. And the moment we cross this exhaustive data research with brand and market knowledge, something clicks to bring the right data to creative teams.
Since each data has as many interpretations as interpreters, it is key to have the right people on board who can make it actionable in the advertising process and more importantly – specific to the market, the consumers, and the problem we are trying to solve.
The truth behind the numbers
Usually when starting research with declarative data, we rarely get to the bottom of that human truth we are looking for, which will become the foundation for our insight. It will offer the answer to the question we are asking about, no more, no less. And even with more accurate and developed panels, it will still be dependent on the trend identified by the ones writing the questions.
These quantitative data points can be a key source of observation to better understand society, a market, a target…, a starting point which will often lack the complexity and uniqueness of human emotions.
Between an opinion poll of France’s favourite comedians and the reality of who people are watching, there is a massive discrepancy. The poll was only listing historical comedians while online activity suggested a more nuanced ranking based on clusters and audiences; with comedians being representative of introverts, depressive forty-year-olds, young couples. If both methods have biases, their complementarity is undeniable, but going further down into what makes this data compelling is what will bring texture to it.
The same applies to our research on people’s behaviour, because every quantitative data can either be too generic or just another question asked by someone with an agenda. We often lack qualitative and spontaneous signals, and we need to dig elsewhere to bring something more to the table.
Learning to manage the tension
If quantitative analysis will help bring context, qualitative signals will offer texture and depth into the understanding of consumers' lives. By mixing spontaneous with declarative and quantitative with qualitative data, we offer a solid frame for a more nuanced and complex picture.
When considering buying a refurbished phone, consumers answered they have done it mainly for budget reasons and might choose a specialist over a phone operator. To position Orange as a leader on sustainable behaviour in the sector, we needed to go deeper into what people were saying about their devices in general. We found the same reason for choice, but we also unveiled many behaviours like the tight bond consumers build with their phone during the life cycle – from a first rendezvous to the final break-up. Finally, we found people weren’t keeping phones in a drawer for no reason, but often to give them to their growing kids. From there, this collection of quantitative and qualitative data helped draw the path for the emotional creative story of the second life campaign, highlighting the handover of the famous phone toy from a mother to its daughter.
Tailoring data analysis for different audiences
One of the main challenges for successfully transforming raw data into a creative strategy is the ability to bring a variety of profiles on board. Globally in creative agencies, the easier it is to digest for everyone and the less we enter the complexity of the data process, the better.
Project teams need reassurance of utility and methodology to face a potential client defiance.
For planners, it’s about compiling knowledge to have an exhaustive view and be able to pick the right signals.
Creative will look for a new starting point and won’t care too much about data itself.
Our business is learning and there are new frontiers we need to reach. With the widespread adoption of AI, it will become much easier for various agency profiles to be able to play with data. The recent announcement of CoreAI at Publicis Group is going into this direction by offering a platform tailored for every role to optimise their process, facilitate collaboration, enhance exploration, help find inspiration, improve analysis accuracy, and unlock new usage. By simplifying data access and adoption at scale, agencies will not solely improve efficiency, they will also empower many roles in their daily tasks to build more creative campaigns.
