About The Luxury Closet
Based in Dubai and founded in 2011, The Luxury Closet is a leading online boutique for buying and selling new and pre-loved luxury items like handbags, clothes, watches, and jewelry. It features top brands such as Louis Vuitton, Chanel, Van Cleef and Arpels, Cartier, Rolex, and more.
Great Challenges Come With Great Success
The Luxury Closet is an established player in the high-end fashion industry. This was achieved by systematically improving internal processes and focusing on using the right data to drive decisions. In the complicated world of modern online marketing, they had been feeling that using only Google Analytics data is holding them back and preventing them from further growth, and so they decided to do something about this.
The main challenge was correctly evaluating the ROI of their marketing activities. Google Analytics shows the revenue for each campaign but it is not good at assigning the revenue fairly in cases of the potential buyer visiting the website multiple times and taking longer to decide to make a purchase. Google Analytics assigns credit only to the last visit of a buyer.
This is a huge problem for TLC because over 55% of their revenue comes from customers who visit the page at least 3 times before placing an order. This means that these visits which are at the beginning of the acquisition funnel have been assigned no credit by Google Analytics even though they play a crucial role in building the awareness that leads to a purchase. The Luxury Closet decided that a more sophisticated approach needed to be taken in order to evaluate the acquisition activities based on data and not just feelings.
Seeing Improvements Immediately After Implementation
The Luxury Closet decided to implement Roivenue, a specialized data-driven attribution tool which excels in its ability to evaluate the real performance of each campaign using AI-based data driven attribution modeling. Another big advantage is its versatility, allowing for the implementation of custom demographic data segments pulled from Google Analytics f.e. Country.
After a 4 day implementation, TLC prepared the needed views which segmented their marketing data by platform, campaign, and especially country. All together this allowed for identification of what works for different countries and what does not. This was very easy thanks to the Custom Dimensions features in Roivenue which allows users to easily slice their data based on any custom rule.
One of the first stops for them was the Attribution Analysis page, which compares the results of channels in the Last Click model and Roivenue’s data-driven model. The analysis showed big potential for Google Shopping campaigns, which played a big acquisition role in the marketing mix. The data-driven model attributed more than double the amount of revenue to the channel than last click had. Some other channels which identified as being candidates for optimization included Microsoft Ads, which was small in the total amount of revenue but was bringing in a 38x return on investment, as well as some Facebook campaigns.
Being sure that these channels actually help customer acquisition, they felt comfortable to start optimizing. The first round of optimizations focused on higher effectiveness and by the end of December, the ROI of Google Shopping campaigns increased by 23% while keeping investments at the same level. In Q1 of 2022, ROI further improved by another 21% while spending increased by around 10%.
Further changes have been made on different channels in a similar way leading to an overall improvement of marketing ROI by 17% within 2 months from the start of the cooperation.
Therefore, the total ROI of one year of Roivenue’s License was 1300% within the first 10 weeks of cooperation - including the implementation period.
Thanks to Roivenue Attribution, The Luxury Closet has been able to optimize their acquisition funnel and improve ROI by 17% in the first two rounds of optimization based on recommendations provided by the data-driven model. This was just the first step in marketing decisions becoming completely data driven. The next step is the automation of provision and aggregation of all marketing data, in order to establish a single source of truth to consult whenever there comes time to make a decision.