Volkswagen - Integrating artificial intelligence into SEO strategy to optimize conversions

The context

The challenging economic environment, coupled with increasingly pressing ecological imperatives, has significantly altered consumer purchasing behavior within the automotive industry.
This shift is reflected in a widespread awareness of the importance of responsible consumption, prompting the automotive sector to innovate and transform in line with environmental challenges.
Since the announcement of the phase-out of internal combustion vehicles by 2030, the entire automotive industry has adopted a strong organic acquisition policy, particularly focusing on electromobility.

The objectives

Reducing Volkswagen’s dependency on key strategic keywords by expanding coverage of thematic and commercially valuable keywords.

Since 2023, automakers have intensified their SEO strategy and improved their positions on the same generic keywords. A loss of positions on Volkswagen’s strategic keywords would result in a significant traffic decline. Therefore, our team embarked on implementing a disruptive AI-based strategy aimed at maintaining and enhancing Volkswagen’s organic performance.

Leveraging long-tail keywords to reduce “competitive clutter” and improve Volkswagen’s visibility and organic traffic.

Publishers (such as Aramisauto, Automobile Propre, Turbo, etc.) capture significant traffic through long-tail search terms associated with Volkswagen models or brand. Although they are not direct competitors in car manufacturing, these publishers still compete with Volkswagen on its own turf. Our second objective was to identify ways to support the brand’s traffic to counteract this “clutter.”

Project in numbers

The challenges

The primary challenge was to model and build an AI-based solution within a very short timeframe, capable of interpreting the targeted SEO strategy and delivering the expected results.

To achieve this, our Data Scientists, in close collaboration with the SEO experts at Havas Market, designed an algorithmic flow (a visual representation of an algorithm) specifically aimed at optimizing Volkswagen’s internal linking structure. This flow outlined each step of the process, from content analysis to classification.
This algorithmic flow was then transcribed to feed the AI training model until the resulting model produced actionable and relevant recommendations, meeting the high-quality standards we had set.

Our Solution

Boosting the “Semantic Cocoon” with AI

Ekino brought together the data expertise of MFG Labs and SEO specialists from Havas Market for a project designed to unlock the full potential of Volkswagen’s internal linking structure using AI.

Also known as the “semantic cocoon,” this linking structure refers to a coherent organization of internal links between the pages of a website. Crucial for SEO, it directly influences search engine rankings, indexing, and user experience.
Leveraging AI, the solution developed was able to identify patterns and content relationships that had not been exploited, creating a stronger network of interconnected content and, as a result, enhancing Volkswagen’s ranking in search engines.

Results

Thanks to the advanced recommendations provided by AI, Volkswagen recorded remarkable progress in Google’s SERPs (Search Engine Results Pages), securing advantageous positions on strategic automotive industry keywords.

This SEO-focused approach enabled in-depth analyses made possible by AI, which would have required significantly more human time investment with no guarantee of equivalent return on investment (ROI).

The benefit of our AI solution for Volkswagen is twofold: a notable improvement in its organic ranking for strategic keywords such as “automotive innovation,” “Volkswagen electric vehicles,” and “sustainable mobility solutions,” coupled with enhanced operational efficiency.

These technological advancements create an undeniable competitive advantage for Volkswagen in developing optimized, targeted SEO strategies, strengthening its presence in the digital automotive ecosystem.