FLOW: Continuous intelligence for your brand



FLOW: Continuous intelligence for your brand

The amount of data that people leave in the digital universe has reached unprecedented volumes, and it keeps on growing due to cheaper smartphones and data packages for internet usage. Google searches, social media updates, e-commerce purchases, or interactions with chatbots are a few of the examples of available sources to know better your specific consumer groups.

However, the approach that still dominates the development of market studies is still based on concepts from 1935, the year when George Gallup founded the institute with the same name, and who was responsible for the popularization of public opinion surveys to predict election results or to understand the perception of consumers about a product.

In E.life, we believe that the time has come to retire Mr. Gallup and look at market research from another perspective. Instead of trying to predict the behavior of a 12-people group, we want to analyze millions of daily Google searches. Instead of placing a student in the middle of a busy street or the airport asking what your favorite yoghurt is, we want to invite consumers to interact with chatbots from the comfort of their homes or offices.


If we were to make an analogy, the time has come to leave behind the Gallup world and enter the GAFT world (Google, Amazon, Facebook, and Twitter), just like movie theaters took the lead on taking the art of storytelling to the great masses, which, for many years, was dominated by theater plays.

For 14 years, E.life has been helping great companies take this step by using social media monitoring. Each year, we revolutionize our models and processes to adapt to the speed in which consumers access new technologies. This year, we bring an important novelty to the market, a concept that we have named FLOW: continuous intelligence through the analysis of data that is collected on digital touchpoints of a specific audience.



Flow encompasses two key ideas:

  • The delivery of shorter analysis focused on topics and subtopics related to the brand during the entire year (for example, for a shampoo brand, we also analyze what happens in the universe of gray-haired people).
  • The identification of themes out of the radar (hidden gems) through the deliverables mentioned in the previous point (for example, allergic reactions to hair dye).

How the FLOW model is applied to a company’s daily life:

  1. Monthly meetings: the E.life intelligence team meets with the client on a monthly basis. In these meetings, we present hypotheses that arise from the first digital data that were extracted. The hypotheses are rejected or confirmed by the client, and others are posed. In these monthly meetings, E.life and the client must agree as to what is the priority for the first month’s research. On the next month, the data that have been studied in depth will be presented, and new challenges and hypotheses will be discussed between the client and E.life.
  2. Creation of Concept Maps: for each monthly meeting, new topics of interest will be added, and we will create a concept map that will represent not only the analyzed topics, but also what the results can be.

Main advantages:


  1. A new outline that allows you to study consumers’ behavior quicker. With traditional market research, this would take us approximately 6 months, while with digital delivery, this time would be reduced to one month.
  2. Lower costs: the access to digital data is simpler and wider. Therefore, it is possible to analyze different scenarios and confirm hypotheses with fewer costs. Most consumer data are available for free on platforms such as Facebook and Google.
  3. End retroactive analysis: the client and E.life will analyze the data and trends that could be interesting for the company, their businesses, and future positioning.


FLOW is, therefore, a process: from the analysis of the universe we know, we then identify what is outside our visual field, but that is there for us to find, hidden under terabytes of data that are generated every day by millions of people.

Do you accept the challenge to redesign the way your company analyzes scenarios and data?


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