As YOYABA began working with Proof's VP of Marketing Nick Bhutani on CRM architecture and tracking in 2024, the scale of the infrastructure gap became quickly visible.

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Proof was spending across paid search, social, and organic - but there was no reliable way to connect that spend to revenue. CRM data sat disconnected from advertising. Ad platforms often optimized toward sign-ups, not toward firms that actually became paying customers. On the sales side, inbound sign-ups arrived without structured scoring, routing, or prioritization. There was no account grading system tied to ICP, no territory & multi-state-client assignment logic, and no clearly defined funnel. Marketing generated sign-ups; what happened after that was largely manual. The sales team's biggest frustration was simply "identifying ICP prospects".

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The legal industry compounded the problem. Unlike most B2B SaaS verticals, the legal audience is lacking in data availability on tools like ZoomInfo or Clay that are provided elsewhere. Identifying the right law firms - by practice area, case volume, firm type, and decision-maker - required building something custom.

On the growth side, the paid program Proof had been running with a previous agency was heavily concentrated in SEM with inconsistent sign-up quality. Additionally, competitive pressure on paid channels was intensifying in 2025. Direct social media attempts produced poor-quality sign-ups that rarely converted to first jobs. There was no demand creation layer - the entire budget captured existing demand rather than building awareness.

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And as Proof had grown, their messaging had evolved across different teams and channels without a shared narrative to tie it together. Ad creative, landing pages, and SEO content were each telling a slightly different story about Proof’s advantages. On top, the vast majority of webpages were generating zero traffic, creating crawl inefficiency and diluting site authority while commercial pages remained deprioritized.

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"Just 6 months ago, 80% annual growth was imaginary. Today we're tracking towards it. The foundation we built together - the attribution, the enrichment, the analytics, the market & product knowledge - that's what makes the difference. We're making decisions based on data now, and we are in for a ride."

Nick Bhutani
VP Marketing @ Proof

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Together with Proof, we built a full revenue marketing engine spanning RevOps, Paid, and Organic - designed so that each layer reinforces the others. The RevOps infrastructure feeds paid targeting and sales prioritization. Paid performance data informs organic strategy. And the attribution layer lets every team measure against the same revenue metrics.

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To get there, the collaboration had to cover three key areas:

1. Revenue Operations & Infrastructure

Working with Proof's VP of Marketing, Head of RevOps and Sales Team, we built the operating layer that the GTM teams now run on.

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• Attribution & offline conversion tracking: Rebuilt the entire attribution model from the ground up - standardizing tracking across all channels, custom touchpoint handling for multi-touch attribution capabilities, implementing offline conversion signals, and shifting ad platform optimization from sign-up volume toward first job submitted (the actual revenue event).
• Enrichment & ICP scoring: In close collaboration with the Proof Team, designed a now deeply engrained - and still iterated on - ICP Scoring model with a waterfall enrichment architecture combining Clay, ZoomInfo and custom scripts, because standard tools couldn't reliably identify ICP.
• Account routing & sales funnel: Built a structured pre-deal and deal pipeline with defined exit criteria at each stage. An account scoring system powered by the enrichment & ICP scoring routes high-value inbounds to AEs and mid-market accounts to the SDR teams. Accounts get acted on by the right person swiftly, and every deal stage captures the data needed for pipeline visibility.
• Analytics & Forecasting: We worked closely with Proofs Data Team to connect platform, CRM and Ad channel data in Proofs own data warehouse. These efforts enabled reporting. By late 2025, when both teams knew the growth model worked - the question was how far to push it. Together, we built new forecasting models for ambitious 40%, 50% and 80% growth scenarios using a demand capture / demand creation framework. Budget decisions become informed by longer historical timeframes of clean data, allowing for bigger bets while still keeping control and managing risks.

2. Paid Growth: Demand Creation & Demand Capture

Proof was running on Demand Capture only. We also started here. Identifying optimization potentials through iterative testing and analytics, and restructuring the SEM program for precision, scale, and revenue-aligned optimization. After securing the demand already in market, we proposed a critical strategic shift: building a brand-led demand creation layer that feeds downstream demand - the demand capture <> demand creation symbiosis.

Demand Capture

• Campaign architecture: Single-keyword ad groups (SKAGs), low-intent keyword experiments to expand the demand pool, state-level and city-level campaigns for geographic targeting, and Bing scaling alongside Google.
• Navigating the competitive landscape: Tailored bidding strategies to meet Proof’s unique mix of local, regional and national competitors, with purpose-built comparison landing pages.
• Performance Max leverage: Tested PMax to unlock incremental volume - separated prospecting vs. retargeting into dedicated campaigns for cleaner attribution.‍
• Meticulous testing & scale: Iterative approaches and detail-orientation on all ends lead to +89% growth year-over-year (Q1 2025 → Q1 2026) sourced by paid channels.

Demand Creation

• Brand plays: Ongoing analysis of sales and Customer Success calls lead to the “Like Uber” social campaign. The concept came directly from Proof's sales team, who were already using the analogy in conversations: "In a world where we can track everything - like an Uber ride or a FedEx package - why can't we track legal operations?" Together, the teams turned this into a cross-channel brand awareness play across Meta, LinkedIn, and Reddit - one consistent message, reinvented across formats, building top-of-mind recognition rather than chasing direct response. Additionally, launched TLAs with Proof representatives as the face - outperforming all other social ad formats. New UGC campaigns are in testing. Overall, with proven effectiveness: The data shows a direct correlation (r=0.92) between social spend and branded search volume & conversions.
• Reverse engineering messaging: Deep-research analysis of customer calls across Proof's sales and CS teams. Ai-based visual categorization for target audience receptiveness analysis. These reshaped homepage positioning and ad creative direction.

3. Organic Growth & AI Visibility

We focused on making Proof's existing site infrastructure earn its keep - and preparing for a future where AI-generated answers matter as much as traditional search.

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• Content rebalancing: Shifted prioritization from ~90% blog / 10% commercial to a commercial-first approach, with page-by-page recommendations for commercial pages.
• Thin content consolidation: Identified over 1,000 local service area & process rules pages with underperforming traffic and engagement. Developed a consolidation strategy to redirect granular local pages to state-level parent pages, concentrating authority on pages with real ranking potential.
• Technical SEO: Resolved core crawlability and redirect issues affecting site performance. Executed internal linking using a custom Python tool, prioritizing commercial pages for authority consolidation.‍
• AI visibility: Implemented schema markup, entity optimization, and tracking infrastructure so Proof appears in AI-generated answers. Kicked off a dedicated SEO/LLM workstream targeting ChatGPT and other AI search surfaces in 2026.