Founded in 2013 and based in Copenhagen, Denmark, Moodings is an online lifestyle and design store which curates and sells interior design, and art from upcoming designers, artists, and established brands.

“The more the AI learns about our current customers, that knowledge immediately informs our audience building in Google and Meta to retarget with consistent messaging and to build even better lookalike audiences for finding new customers.” - Daniel Selde, former CM

‍

The challenge

Being a company based on creating unique stories around your home, Moodings was facing a plethora of challenges in order to not only personalize but also scale their target audiences and find better look-a-like audiences on their advertising platforms.

With a multichannel mix built around internationalization, segmentation has been a key point in their commercial messaging and targeting.

However, as the company kept growing bigger and became more advanced and ambitious, the platform that Moodings were using beforehand, was not able to properly collect, analyze, and segment on a level that Moodings needed it to.

The platform was not built around CDP capabilities in its essence, and it meant that the data processed in this platform started raising doubts.

They feared that the look-a-like audiences would not be as accurate as Moodings needed them to be. On top of that, the segmentation was not able to account for those customers who brought the most value to the business.

This created 3 major challenges for Moodings in relation to their Black Friday campaigns and ultimately led to them testing out their current setup against Custimy’s segmentation engine.

The 3 challenges were:

• Identify and segment based on which customers bring the most value to their business
• Identify look-a-like audiences that fit their most valuable customers
• Create relevant advertising campaigns for those customers

‍

The solution

This year’s Black Friday Week must have felt extra special for Daniel Selde, CMO Moodings, and the rest of his team, as they tested out different ways of segmenting their customers for advertisement targeting.

The team ran multiple campaigns in order to see which ones would yield the best results based on a number of factors. But it all revolved around proper segmentation

To create the best possible segmentation for Facebook Audiences Moodings used not only Klaviyo and Facebook’s algorithms but also Custimy.

The way it was done was quite simple;  run two different campaigns:

• One with Klaviyo/Facebook created audiences based on their algorithm
• Another case with Custimy created audiences based on behavioral data from segments built in Custimy.

The segmentation in Custimy is based on a multitude of advanced variables and features that allows for much more precise insights into the customers within the segments.

The 3 different segments there was used from Custimy was:

• Most Valuable Customers
• Promising Customers
• High Spend Customers

‍Most Valuable Customers is a segment built up around some key factors that we have pre-build to find the best and most profitable customers you have.

‍

Promising Customers is a segment that is built up around some of the same key factors as your Most Valuable – these customers are looking promising for ending up in the same segment as your best customers.

‍

‍High Spend Customers is a segment with customers that don’t place that many orders, but they are having big cart sizes with a high profit from the start.

‍

Using first-party data on existing customers, Custimy is able to create a segmentation based on more variables and thus create better insights.

Moodings were able to use the insights to build more accurate and relevant look-a-like audiences on exactly the type of customers they were looking to activate.

These segments and the data from Custimy were exported and used for a reverse enrichment of Facebook look-a-like audiences in order to target those customers who bring the most value to their business.

During the week of Black Friday Moodings ran both campaigns both on their owned channels and paid channels and in the end compared the two campaigns to see the results of the different audiences and segmentation.