Lead Generation Engine
A B2B services firm with a CPL [Cost Per Lead] of $180 and a pipeline bottleneck that had persisted for six quarters. The mandate: engineer a scalable lead capture architecture that reduced Cost Per Acquisition without sacrificing SQL [Sales Qualified Lead] quality.
The firm's pipeline was structurally broken. Cost-per-lead had inflated 60% over 18 months — driven by undifferentiated Google Ads spend, zero negative keyword discipline, and a single generic landing page converting at 2.1%. There was no MQL [Marketing Qualified Lead]-to-SQL scoring framework, no nurture infrastructure, and no CRM [Customer Relationship Management] tagging to identify which channels were producing closeable pipeline versus low-intent form fills. The sales team was calling leads that had gone cold 72 hours prior. Attribution was last-click only — masking the true ROAS [Return on Ad Spend] of individual channels and making budget reallocation impossible.
Hypothesis: the pipeline bottleneck was a friction problem, not a traffic problem. The existing funnel was collapsing at the point of capture — a generic page, a high-cognitive-load form, and no behavioral trigger to qualify intent before the sales team engaged. Target: CPL below $65 and landing page conversion rate above 6% within 60 days. Secondary target: a lead scoring model that allowed the sales team to prioritize SQLs in real time.
Conducted a full account audit and identified 60% of Google Ads spend flowing to broad-match irrelevant queries. Rebuilt the keyword architecture around high-intent commercial terms — 'pricing,' 'comparison,' and 'hire' modifiers only. Introduced a negative keyword suppression list of 340 terms to eliminate TOFU [Top of Funnel] waste. Restructured ad groups for Quality Score recovery — ad relevance scores lifted from 4/10 to 8/10 across the primary service lines, compressing CPL from the media side before a single landing page change was made.
Deployed dedicated landing pages per service line — each engineered for minimal cognitive load, a single conversion objective, and maximum perceived value exchange. Removed navigation, reduced form fields from seven to three, and introduced a lead magnet (proprietary benchmarking report) as the conversion hook. A/B tested headline framing, CTA copy, and trust signal placement across six variants in 30 days. The control page converted at 2.1% — the winning variant reached 7.4% within 60 days of launch. Page speed was optimised to sub-1.8s TTI [Time to Interactive] to eliminate drop-off at load.
Built a three-stage automated nurture sequence triggered by lead magnet download events, integrating directly with the client's CRM via API. Each lead was tagged by source channel, entry page, and behavioural signal — creating a functional lead scoring model that classified MQLs and SQLs automatically. The sales team received real-time CRM alerts only for leads scoring above threshold, eliminating cold outreach entirely. Average time from lead capture to qualified sales conversation compressed by three weeks. Pipeline velocity — defined as deals moving from MQL to closed — improved measurably in quarter one post-launch.
THE RESULT
67% reduction in cost per lead
A B2B services firm with a CPL of $180 and a pipeline bottleneck that had persisted for six quarters. The mandate: engineer a scalable lead capture architecture that reduced Cost Per Acquisition without sacrificing SQL quality.
SERVICES USED
67% reduction in cost per lead
TECHNICAL TAKEAWAY
Lead generation is not an event — it is a system. Reducing friction at the point of capture, scoring intent before human contact, and attributing spend to closed pipeline turns passive traffic into compounding business equity.
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