These case studies represent actual client work from 2024–2025. Results vary based on industry, budget, competition, and execution quality.
Nexus Dynamics struggled with low-quality inbound leads and high cost-per-opportunity from generic paid campaigns. Their sales team was spending too much time on unqualified prospects.
Fragmented data sources, no unified lead scoring, and broad audience targeting resulted in CPL of $112 and only 38% of leads passing sales qualification.
Summit Advisory wanted to expand their enterprise consulting practice but were getting inconsistent lead quality from LinkedIn and Google campaigns managed in-house.
High CPL ($124), long sales cycles (5–8 months), and difficulty reaching CFOs and COOs with relevant messaging.
Predictive buyer intent model + AI-optimized LinkedIn + Google campaigns + personalized nurture sequences triggered by engagement signals.
Forge was spending heavily on broad Google and Meta campaigns but seeing diminishing returns and inconsistent demo bookings for their complex equipment sales process.
LedgerFlow needed to accelerate enterprise pipeline while maintaining strict CAC targets. Previous agency was focused on volume rather than quality.
Implemented full-funnel AI attribution, built custom lead scoring model tied to closed revenue, launched high-intent LinkedIn + Google campaigns with real-time creative optimization, and deployed personalized nurture paths based on firmographic + behavioral signals.
These results are from real client engagements but are not typical or guaranteed. Marketing performance depends on many variables. We share these to illustrate the type of work we do and the level of transparency we provide.
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