Overview
ShareGate came to Omni Lab with a paid media program that was delivering inconsistent results and lacked a clear path to scaling. Ninety days later, they hit consecutive all-time highs in TOFU demand and a 44% YoY increase in SQLs.
The Challenge
ShareGate's paid media program had real potential but structural problems holding it back. Conversion tracking was partially broken, campaign architecture was creating internal competition between keyword match types, and bidding strategies were misconfigured for the account's actual maturity. The result was inflated CPAs, misallocated budgets, and optimization algorithms making decisions based on bad data.
The business needed two things at once: near-term efficiency gains and a foundation strong enough to support scale. Getting there required fixing what was broken before layering on anything new.
The Approach
Fixing the foundation first. In early May, a sharp drop in reported sign-up conversions was identified during a routine review. The root cause: a backend code change at ShareGate shifted the GTM data layer action, breaking the conversion trigger entirely. Omni Lab diagnosed the mismatch, drafted a corrected GTM configuration, and coordinated the fix with ShareGate's team. Without this catch, the account would have continued optimizing against corrupted data indefinitely.
Restructuring campaigns to match buyer intent. Exact Match and Phrase Match keywords were running in the same campaigns, causing high-intent, lower-volume exact terms to be crowded out by broader phrase traffic. Separating them into dedicated campaigns with tailored bidding gave each match type the budget and optimization logic it warranted. The result was a cleaner funnel across both high- and mid-intent segments.
Calibrating bidding strategy to account for maturity. Early in the engagement, Target CPA caps were constraining conversion volume at a stage when the account needed data, not guardrails. Omni Lab removed caps from high-performing campaigns to let Google's algorithms bid aggressively, while applying tighter controls where waste was more likely. As volume grew and data stabilized, efficiency targets were reintroduced. Protect campaigns scaled spend by roughly 70% while growing conversions by more than 40%. Competitor campaigns saw CPL fall more than 25%.
Refining audience quality on LinkedIn. Non-IT roles, including founders and board members, were excluded from LinkedIn targeting to concentrate impression share among IT decision-makers. These profiles were inflating cost-per-engagement without contributing meaningfully to pipeline. The reallocation shifted the budget toward the buyers most likely to become SQLs.
Matching channel to goal on social. Webinar campaign budget was shifted from LinkedIn to Meta after Meta's lower CPM proved better suited to driving registrations at scale. LinkedIn remained the right channel for brand awareness among technical buyers; pushing aggressive conversion goals there was producing inefficient spend. The channel mix was adjusted to reflect actual unit economics rather than platform preference.
The Results
ShareGate's demand metrics hit consecutive all-time highs during the engagement period, with SQLs growing 44% year over year. Monthly SQL counts climbed steadily from December through April, reflecting compounding improvements rather than a single spike.
Over the 90-day period, the account generated meaningful revenue at a ROAS well above breakeven, with thousands of conversions feeding the sales funnel across both Migrate and Protect product lines. The most efficient campaigns came from tightly structured non-brand search, where incremental spend produced incremental pipeline at predictable unit economics.
"This wasn't done by implementing some brand-new flashy marketing playbook, but by focusing on marketing fundamentals. It was done by making slow, incremental changes." — Kaushik Kumar, Head of Demand Gen, Workleap
Snapshot: Results from December 2025 to March 2026
Strategic Takeaway
ShareGate's results demonstrate what happens when execution discipline catches up to growth ambition. The gains here came from correcting structural problems and making data-driven decisions with patience rather than urgency. Each optimization compounded on the last. The account is now positioned to scale with confidence: tracking is accurate, campaign architecture is clean, and budget is allocated to the channels and segments that have proven they can produce.
