The context
Undergold is a brand created by designers passionate about the world of fashion, inspired by Streetwear and Luxury Lifestyle.
It was born in Medellin in 2016, with the aim of reaching those people looking for authentic designs that go beyond fashion, always prioritizing quality and differentiation.
They stand out for developing collections in which they align their essence with international trends in urban fashion and haute couture houses.
Thanks to this identity, recognized personalities such as Nicky Jam, Karol G and Manuel Turizo, find in the brand a unique proposal within the national and international market.
The brand started with only a physical store, WhatsApp sales, Instagram profile and website.
Being a venture the investment of the company must be managed as efficiently as possible. Before thinking about expansion through physical outlets, they had to make the digital channel more powerful. Through advertising they managed to create a significant national recognition and reach, which allowed them to grow in the digital channel, achieving a weight in sales of 33.42%.
The challenge
From growth, Undergold needed:
The strategy
In August 2022, Data4Sales started working in partnership with Undergold and Vieli Digital Agency.
In each customer success session we analyzed together the data (coming from our tool) and the opportunities we found in them. These meetings were key to planning a strategy.
What pains do we perceive in the campaigns in Meta?
The solution
During the process, we detected an opportunity to implement personalized audiences in Meta Ads campaigns.
In Data4Sales, the "rules engine" feature allows you to visualize in detail the characteristics of a group of buyers and then develop a personalized communication strategy based on that audience.
With Undergold, we decided to delve deeper into audiences with the following buying behaviors:
Once the audiences have been taken to Meta Ads, we launch the personalized campaigns and in Data4Sales, we configure the Marketing Actions.
This function allows us to visualize and understand the people who bought or did not buy in the campaign time window, and then re-create audiences before the end of the commercial action, with those people who did not generate conversions.