Case study: Maximizing clicks for Audi’s E-tron Launch Site During a Pandemic

13 January 2023

Helping Audi and PHD discover new interest groups outside of their typical target market and gain a new perspective on their personas from the perspective of an AI.

In December 2020, Audi Taiwan officially unveiled the Audi e-tron to much fanfare, both offline and online. But just like the rest of the world, Taiwan saw a decline in car sales as a result of the pandemic. Despite the excitement surrounding the new launch, the majority of people did not prioritize test-driving a new car.

The challenge:

Audi Taiwan has been working with their incumbent media agency, PHD, to push for test drives on Meta. Although they had some success generating leads, their cost per link click (CPC) was too high, making it an inefficient use of their marketing budget and lowering their ROI.

This allowed SoMin to help both PHD and Audi through AI-driven optimization solution to further optimize, lower Audi’s CPC and conserve their marketing budget.

To help Audi and PHD lower their cost per link click (CPC) and maximize their advertising budget, here is what we did:

  • We used our proprietary Omni-Sourced User Profiling algorithm to gather anonymized audience data from a variety of sources, including Audi’s own historical campaign results, the subscribers of their rivals' Meta (Facebook and Instagram) pages, and Google search queries and results. Through this, we were able to analyze more than 366K social accounts across Meta that were associated with the brand and the industry to identify new opportunities to reach our consumers.
  • Our tool then analyzed approximately 6.1 million posts from these accounts using computer vision (CV) and natural language processing (NLP) and collected 11.8 million data points for the collaborative filtering (CF) process.
  • Based on the campaign's objective, SoMin generated 12 campaigns, 738 ad sets, and 850 ads and audiences were clustered based on their likelihood to convert into leads using long-tail targeting.
  • Finally, with Ad Management Automation, all 12 campaigns were managed and optimized automatically throughout the campaign period.

By the end of the campaign period, SoMin and PHD were able to successfully reduced Audi Taiwan's cost per click by 42.6%, which resulted in budget savings of more than 45%. 

As a result of the success of this campaign, Audi increased the scope of its partnership with SoMin by becoming the company's first client to incorporate SoMin's competitor and content analysis tool into their social media management.

Download the case study: here


Prof. Aleks Farseev PhD

Aleks Farseev is a machine learning wizard who can teach a computer to sing "Bohemian Rhapsody" in binary code. He loves conjuring up new creations and is on a quest to figure out how machine learning can make the world a better place. When not tinkering with technology, Aleks can be found serenading his friends with his accordion skills, which he claims are only slightly less impressive than his machine learning prowess.

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