How Enterprise B2B Marketers Can Make Meta Work

"Primer helped us box in Meta’s algorithm — and boost enterprise conversions by 37%.” — Marcus Moraes, Head of Paid Media, Superside

Company & GTM Profile

The Challenge: Teaching Meta to Think B2B

By late 2024, Superside had shifted its focus to enterprise accounts. Company size was now the strongest predictor of lifetime value, and smaller companies converted at lower rates due to pricing.

Meta was a key inbound channel, but the algorithm favored low-cost conversions rather than qualified enterprise buyers.

"Most of our lookalike conversions came from micro and SMB segments,” Marcus said. “There’s a big difference in LTV when we compare segments.”

Meta’s native targeting can’t filter by firmographic quality, so high-volume campaigns produced too many low-value leads. The team needed a way to keep Meta’s reach but make the algorithm learn only from the right users.

How Superside Optimizes Meta for Enterprise Demand Gen

Superside runs Meta as a system. Their approach combines Primer’s audience intelligence with disciplined creative and bidding strategy across three pillars: Constrain, Focus, and Sustain. Together, they form a repeatable framework any B2B marketer can use to make Meta work for enterprise acquisition.

Pillar 1 · Constrain the Algorithm

Meta’s algorithm performs best when it has freedom to learn—but only within clear boundaries. Superside used Primer to define those boundaries.

They began by replacing Meta’s native lookalikes with Primer-seeded audiences, then measured how well each delivered enterprise-grade conversions. The result: a +28.9% increase in the share of enterprise conversions and a –43.2% reduction in cost per enterprise conversion compared with Meta’s default lookalike audiences.

Once they layered on Anti-ICP suppression—excluding agencies, students, and companies with fewer than 1,000 employees—the performance improved even further, driving a +40.8% increase in the share of enterprise registrants versus running the same campaigns without suppression.

"Primer helped us box in the algorithm so it only learned from the right data,” Marcus said.

Instead of using bid multipliers, Superside runs separate ad sets by company size, allocating higher budgets to the segments that represent the greatest enterprise value. This structure keeps learning clean across tiers while ensuring spend scales with business impact. Each segment also carries a distinct conversion value, allowing Meta to optimize toward return on ad spend (ROAS) and prioritize the share of high-value enterprise conversions that matter most.

Pillar 2 · Focus on the Right ICP

Once Meta’s learning universe was constrained, Superside turned its focus toward bottom-of-funnel performance.

Here, the team went inclusion-only—serving ads exclusively to Primer audiences of verified enterprise accounts. There was no lookalike expansion, no Advantage+, and no retargeting. Every conversion came directly from the ICP.

This setup removed waste from recycled or irrelevant traffic and forced Meta’s optimization loop to learn solely from qualified buyers. The result: a +37.2 % improvement in the share of enterprise sales-qualified leads (SQLs) using Primer audiences versus Meta’s native targeting options.

Superside also re-weighted its conversion tracking to reflect value, not volume. Every conversion now fires through both browser- and server-side CAPI, and each is assigned a value based on company size—a practical proxy for LTV. Meta learns which conversions matter most and allocates spend accordingly.

"We measure success by share of enterprise conversions,” Marcus said. “Primer audiences consistently drove the highest share.”

Pillar 3 · Sustain and Scale

Enterprise markets are finite. Sustaining performance requires constant creative refresh and learning stability.

Superside’s creative team produces a steady flow of static, motion, UGC, and influencer assets, introducing new ads weekly to avoid fatigue. “We have too many ads to publish at once—a good problem,” Marcus said. The consistent rotation keeps engagement strong and ensures Meta always has fresh data to learn from.

As match rates and audience data continue to improve, the next step is to move toward persona-specific campaigns—separate creative and landing pages for Growth Marketers, Creative Directors, and CMOs. With quality targeting in place, message relevance becomes the next driver of efficiency.

Practical Guidance from Superside

• Better signals beat broader targeting. Feed Meta a clean enterprise seed and suppress noise.
• Optimize for value, not volume. Use company size as a conversion-value proxy to guide learning.
• Redundant tracking improves feedback. Fire conversions through both browser and server CAPI.
• Creative freshness sustains reach. Rotate ad formats weekly to prevent fatigue.
• Start broad, then specialize. Allow Meta to learn before narrowing to high-performing segments.

"It’s not intuitive that Meta can drive B2B pipeline,” Marcus said, “but with Primer, it can.”

The Outcome

By combining Primer’s audience intelligence with disciplined optimization, Superside turned Meta from a high-volume channel into a predictable enterprise engine.

Enterprise SQL share rose 37 percent, cost per enterprise conversion fell 43 percent, and audience performance remained steady over 12 months without fatigue.

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