With consumption and buying habits growing in a way never seen before, Data Analytics has assumed high importance in retail companies’ marketing and business strategies, both online and offline.

Measurement activities, data analysis or statistical analysis, have several years and variants but, the raising of channels and our clients’ Customer Journey complexity made it vital for retail companies to know their consumers and their habits, leading more and more professionals to dedicate themselves to these sciences.

This race to obtain more results and know the consumers better has generated a very positive hype in the market for the growth and improvement of our solutions’ quality. However, the lack of strategic thinking and channels’ knowledge created difficulty in adopting viable, useful and efficient strategies to join and analyze the countless data as well as making their adoption difficult by some companies in the market.

The approach we have been following in the retail market with clients like Auchan, Delta, or KASA (Sonae), is based on a methodology set on 4 concepts essential in the current market, which we denominate ESE(P):

1. Enrichment

Context is essential for a solid and relevant analysis. With even more and more information in various systems, it is essential to have the right context on Data Analytics tools, to take the best conclusions. The data enrichment allied to existent information in several tools and an integrated vision of data, allows us to analyze even more relevant perspectives to know our users. In the retail industry, data like the ownership of a loyalty card, information about category and product market, classification of the client type, among others, are precious information for the analysis of the users’ or clients’ behavior.

2. Segmentation

In an ever more competitive market, segmentation becomes essential, both in a users’ behavior analysis, as in a marketing strategy approach, focused on the target audiences in segmented marketing strategies. The possibility to segment our user to analyze the specific behaviors, segmenting the data in a specialized way, often focused in niches, is a powerful data analysis tool and strategy evaluation.

3. Experimentation

Promoting testing and experimentation is the best approach in the constant search for improving our digital experiences’ quality and maximize results. With well-known activities like A/B or multi-variant testing, available in many channels like websites, advertising, email marketing, among others, in a more and more accessible and free way, makes the possibility of testing new approaches to finding result improvement alternatives a reality that any company can reach.

4. Personalization

As the last step of our evolution, setting on the base built for Data Analytics with the previous steps, we want to offer experiences even more personalized and adapted to the needs of our users, through the use of data obtained with Data Analytics and, in some cases, machine learning solutions.

Diamond Analytics Model

Diamond Analytics Model - Bruno Amaral

Fig.1 – Diamond Analytics Model by Bruno Amaral

With this simplified and evolutive approach, which adapts itself to the company’s maturity, we are able to adopt Digital Analytics step-by-step and in a solid way. The ESE(P) can, this way, adapt to the current reality, joining new concepts set on the previous concepts, in four adoption steps: three of them are basic, and one is optional.

This way, Data Analytics allows us to better know our new users and analyze new opportunities and threats to our digital strategy, giving us the essential insights to maximize our results and the return on investment (ROI).

The impact of good planning and a good measurement strategy can be really high, allowing us to direct our investments and efforts for tactics and more efficient channels and aligned with our goals.

For example, knowing that the audience that generates more return is the non-food consumers with certain characteristics, why not bet on these clients’ retention, instead of investing indiscriminately and with no strategy? And what are our clients with loyalty card’s behavior? These are just brief examples of useful, rich and relevant data to any retailer.

Have you looked at your results today? Keeping track of tour KPIs allows you to know the current state towards the goal and to adapt the strategy to raise the results, being them revenue, involvement, sales, leads, or any other goal that is relevant to your company.

By Bruno Amaral, Diamond by BOLD’s CEO & Founder and Digital Analytics’ teacher at NOVA IMS