L’Oréal Social Commerce and AI Strategy

Turning social discovery into commerce growth.

The project centered on how L'Oréal could turn social discovery into measurable commerce growth across Instagram and TikTok Shop.

The main question: how to increase sales and improve the user journey from content engagement to native in-app checkout in a way that felt natural and aligned with platform behavior.

Note: Due to NDA constraints, the project is explained on a higher level, focusing on strategic processes and outcomes.

The approach — four phases

Not every follower shops the same way.

We analyzed audience behavior to identify how different consumer segments interact with beauty content, product discovery, and shopping intent on social platforms. This helped us distinguish between users and gave us a sharper view of which segments were most likely to convert.

This segmentation work informed the broader marketing analytics approach and helped ground the strategy in real user behavior rather than broad assumptions.→

Where each platform actually wins.

Conducted a detailed platform analysis of Instagram and TikTok Shop, comparing:

• Native Commerce Features→
• Content Formats→
• Algorithmic Recommendations→
• Ad Formats→
• Checkout flows→

I also benchmarked competitors to understand how other beauty brands were using social commerce strategy, platform-native messaging, and conversion-focused content:

→ This surfaced gaps and opportunities in how L'Oréal could better align with each platform's strengths while reducing friction in the purchase journey.

Content that sells without feeling like an ad.

Rather than treating content as only top-of-funnel awareness, we looked at how these could work together to support both discovery and checkout:

• →Brand storytelling — the emotional, top-of-funnel layer
• →Creator-led content — trust and relatability at scale
• →Product education — moving intent toward decision
• →Conversion-oriented copy — closing the loop at checkout

The strategy emphasized platform-native content, audience relevance, and consumer trust, with messaging tailored to different discovery behaviors and purchase mindsets.

Understanding how AI is shaping the future of social commerce

Explored AI-driven commerce tools to understand how these could improve conversion performance:

• Recommendation engines
• Personalization logic
• Audience targeting
• Ad optimization

The goal was to create a framework that could scale beyond a single campaign and support smarter content and media decisions over time.

Outcome and Marketing Strategy

The final strategy identified a $2M+ revenue opportunity by mapping user social discovery to native in-app checkout across Instagram and TikTok Shop. It also projected a 40% conversion increase through better user segmentation, stronger platform alignment, more effective brand messaging, and improved AI-driven content optimization.

It showed how consumer segmentation, platform strategy, competitor analysis, and brand messaging can combine to create measurable social commerce growth in a highly competitive beauty category.