Data is like archeology, we search for hidden pieces to build a story. This is my new perspective on how data can help strategy and why we need to make the shift from operational data (oData) to experiential data (xData).

The value of an insight depends on the intelligence of the question, not the tools.

First part of my job is to explain to people how to work with data in the marketing and creative process. I faced two challenges:

1. Rejection of data analysis in contrast to intuition.

2. Naivety in thinking that data can provide answers to any generic question, like asking "Hey Siri".

Second part of my job is explaining to data people how to talk to other teams and to other cross-functional teams how to use data.

To overcome these challenges, I built a model based on three pillars:

1. Defining the real problem to be solved and make a difference between significant questions and shitty ones.

2. Co-creating best cases with cross-functional teams to drive adoption.

3. Build an iterative and collaborative process between strategy and data.

Data is like archeology, we search for hidden pieces to build a story.

Most valuable data insights are a result of our gut feeling combined with data proof points. To embrace evidence-based practices, we need to be self-critical and curious. Data without meaning is useless and intuitions without facts are pointless. Data won’t tell you everything. Intuition won’t tell you everything either. But data + intuition = fire.

Wait a minute, how to (re)define data by the way ?

1. What data is : multiform spontaneous human traces left unconsciously on online platforms and devices.

2. What is data isn’t : cold numbers, raw statistics, flat charts, dark magic, obscure clouds, robots.

Data are organic pieces left by humans that provides empathy and utility to strategy if we look at the right places and measure what really matters, beyound vanity metrics.

One cool example of how I effectively used data and artificial intelligence to inform strategy is by collaborating with cross-functional teams at Twitter. We worked with brand strategists, marketing and sales teams to identify starting points to explore and billions of Tweets. This helped us predict future trends and create the Twitter Trends yearly eBook. By analyzing historical data patterns, growth and conversation volatility with different experts, we were able to gain a deeper understanding of trending topics and bring more context to our findings.

Another interesting example of effective data planning was during my time at Publicis Conseil as the data lead. We collaborated with strategic planning by analyzing conversations on Twitter expressed by night and utilizing search insights from Google to uncover cultural trends and opportunities that could represent a new territory of expression for brands. This helped us to tap into the humanity of the audience and fuel the content and cultural relevance.

We need to look where the human stories exist.

The transition from operational data (oData) to experiential data (xData) allows for a more human-centric approach in strategy development.

Organizations often rely heavily on technology and programmatic targeting to reach their audience, this approach based on Operational data (oData) can fall short in providing a deeper understanding of consumer behavior and fueling content with cultural relevance. This has led to some audiences developing a communications fatigue and an increase in the use of ad blockers.

To address this challenge, there is an opportunity to shift towards a more human-centric perspective using experiential data (xData). This type of data takes into account qualitative insights from social conversations, interactions, tribes and search trends such as passion points, mindset, spirit, emotions, values, questions, daily life moments or pain points.

By combining emotional metrics with xData, organizations can tap into the humanity of their audience and improve empathy, cultural relevance and impact. A study* by MAGNA, commissioned by Twitter, found that cultural involvement plays a significant role in a consumer's purchase decision, with it accounting for 25% of the decision. When we bring oData + xData together we will have something powerful.

Seddik Cherif - Head of Insights Twitter France

*MAGNA, commissioned by Twitter, “Impact of Culture,” 2019, US