Case Study: How BSV Predicted the Bud Light x Dylan Mulvaney Campaign Fallout

In today’s marketing world, knowing your audience isn’t optional—it’s survival. When Bud Light partnered with transgender TikTok star Dylan Mulvaney, the campaign sparked both celebration and backlash. But what if Bud Light had known in advance how different audience segments would react?

That’s exactly what our BSV AI-powered brand analytics platform was built to do—and this case study shows how it works.

The Problem: Testing Campaigns Too Late

Traditionally, brands launch content first and measure the impact later. By the time the results come in, millions of dollars may already be spent on ads, PR, and sponsorships. For Bud Light, the Mulvaney collaboration highlighted this problem in real time—delighting some audiences but alienating others.

The BSV Solution

Our proprietary BSV Algorithm© helps brands test their campaigns before publishing:

• Create a Brand Persona: Model your brand as if it were a person, including its values, goals, and interests.
• Select Target Market: Choose your audience from hundreds of demographic and social value filters.
• Examine Results: See how your brand aligns (or clashes) with the chosen audience on social values, product benefits, and overall sentiment.
• Test Campaign Content: Upload marketing content (social posts, influencer collabs, commercials, etc.) and measure predicted impact.

The Bud Light x Dylan Mulvaney Results

When we ran the Bud Light campaign through BSV:

• Extremely Liberal Consumers → +15% Positive Impact
• Centrist Consumers → Conditional Pass (needed revision before publishing)
• Extremely Conservative Consumers → -26% Negative Impact

Our AI model recommended that the content be revised for broader audience acceptance.

Had Bud Light tested first, they could have predicted the backlash and adapted messaging accordingly—avoiding reputational risk while still supporting inclusivity.

Why It Matters

With real-time predictive analytics, BSV enables brands to:

• Save money (no wasted spend on failed campaigns)
• Reduce risk (know audience reactions before posting)
• Boost impact (content resonates with the right people)
• Stay ahead (track shifting social values and sentiment)

Watch the Case Study Video