We build SaaS acquisition around payback period and LTV:CAC — not vanity signups. Product-qualified events fed back to Meta, Google, LinkedIn and YouTube so the algorithm bids for subscribers who stay.
Tell us your product, motion and monthly ad budget. You get a concrete plan with expected CAC and payback ranges — no obligation.
Beauty & aesthetics — B2C lead gen
Cost per lead down 74% while volume climbed
Read the case studyB2B — point of sale & checkout solutions
Cost per lead down 38% while CTR tripled
Read the case studyTrial starts, activation, paid conversion and churn events fed back server-side so bidding targets revenue, not form fills.
Free trial vs demo vs freemium, pricing-page routing and onboarding hand-off tested until payback improves.
Google Search for intent, Meta and LinkedIn for ICP reach, YouTube for education — one senior team, one budget logic.
Weekly blended CAC, LTV:CAC and months-to-payback by channel so finance and growth read the same number.
Audit, tracking rebuild and a clean campaign structure so the platforms optimise on the outcome that actually matters to you.
Creative volume and funnel coverage expand: new angles tested weekly, retargeting sequenced by intent.
Budget compounds into proven winners while the cost per outcome keeps trending down.
"By far the most professional agency we've worked with. They increased our number of leads by 128% and improved the quality without increased ad spend generating an additional revenue of 182% in less than 6 months. I strongly recommend Vibe Digital."
Jonas Wenzel
CEO, B2B lead generation
"During our 2 year cooperation, they've lowered the cost per lead by 68% while simultaneously have delivered higher quality leads. By far the most proactive, communicative and professional agency we've worked with."
Christofer Skoogh
CEO, B2B lead generation
"Highly professional, communicative and competent, they helped us get 160% more leads on Google and YouTube."
Anna Dahlberg
CMO, B2B lead generation
Month to month. You own every account, pixel and conversion dataset.