B2B · ABM · Performance · SEO · Organic Growth
"Before running paid ads, I study organic traffic — because what performs organically tends to perform in paid. Every media investment must be intelligent, not a shot in the dark."
Keyword analysis, search behavior, and content strategy before activating any paid campaign. Organic is the map; paid is the accelerator.
Full tracking stack (GA4, GTM, pixels), CPC analysis, Quality Score monitoring, and ad lifecycle management for evidence-based decisions.
TOFU → MOFU → BOFU journeys aligned to the buying cycle. Each stage has its own creative, bid strategy, and objective — no wasted spend.
Long-term SEO strategy with robust link building and persona-segmented content. Surgical integration between SEO and paid media — organic dictated the highest-intent keywords; paid amplified what was already converting. Real-time performance dashboards for agile decision-making. Result: +30% in qualified inbound leads.
Managed massive paid traffic budget for high-ticket information products — R$1.5M+/month with full-funnel campaigns. From brand awareness with YouTube and Display Ads to conversion via Search. Data-driven creative with constant A/B testing before scaling. Solid Google network expansion with ad lifecycle monitoring at every stage.
Complete digital transformation: paid traffic restructuring with clear conversion goals, new e-commerce launch, Inside Sales structure, CRM implementation, AI and WhatsApp automation. Financial dashboards with projections, team training and full alignment between marketing and sales.
Operationally aligned CRM tailored to the real sales cycle. Sales process structured from scratch — from lead to close. Automation flows for lead generation and qualification. Complete alignment between marketing journey and sales teams, eliminating the MQL-to-SQL gap.
A structured, repeatable framework — not luck-based, but built on funnel architecture, data intelligence, and continuous optimization cycles. Here's everything behind each campaign I run.
Before spending a single cent on paid, I analyze organic performance data as the world's most honest focus group. Organic search tells you what your audience actually wants — not what you assume they want.
Which keywords convert organically. Search intent mapping (informational, navigational, transactional, commercial). Keyword gap vs competitors. Volume vs difficulty scoring per cluster.
Pages generating most engagement, longest session, lowest bounce. Topics with existing authority. Content gaps for MOFU and BOFU stages. High organic CTR → paid ad copy angles.
Device split, peak engagement hours, geo performance, page flow analysis. This directly informs bid adjustments, dayparting, and targeting parameters in paid campaigns.
Key insight: Organic data eliminates guesswork in paid. When I launch a Search campaign, I already know which keywords convert, which landing pages work, and at what hours the audience is most active. This alone can cut CPC waste by 30–40% versus starting blind.
I design the complete funnel before touching any campaign settings. Each stage has a specific audience temperature, creative format, objective, and success metric. Mixing temperatures is the #1 reason paid campaigns fail.
Architecture rule: Never push a conversion objective to a cold audience. Never use broad awareness creatives for retargeting. Each funnel stage has budget isolation — audiences never overlap. I build exclusion lists at every layer to prevent cannibalization.
A well-structured campaign is the difference between a budget that burns and a budget that compounds. I segment by audience temperature, isolate variables for testing, and only scale what is proven — never gut feelings.
Campaign → Ad Set → Ad hierarchy. One objective per campaign. Audience segmentation at ad set level. Creative variants isolated so data is clean and learnings are clearly attributable.
Test one variable at a time: creative vs creative, headline vs headline, LP-A vs LP-B. Never scale without a statistical winner. Min 500–1,000 impressions per variant before declaring a test.
Scale winning ad sets by max 20–30% every 3–5 days to avoid triggering new learning phases. Duplicate high-performers instead of editing them — edits reset the algorithm clock.
Google Ads specifics: Tightly-themed ad groups (3–5 keywords max per group), RSAs with pinned headlines for brand consistency, ad extensions (sitelinks, callouts, structured snippets) to maximize impression share. Search Terms Report audited weekly for negative keyword additions.
Every campaign goes through predictable lifecycle phases. Missing these signals means either killing campaigns too early or burning budget on fatigued creatives. I monitor each phase with defined action triggers.
Adhering to the 50+ events rule is non-negotiable. I've seen accounts pause campaigns at day 3 because "CPA is too high" — only to miss the conversion window that opens at day 7. Patience during the learning phase is a competitive advantage most advertisers simply don't have.
Optimization isn't a one-time fix — it's a weekly discipline. I run a structured audit cycle covering bid adjustments, Quality Score signals, impression share analysis, and creative refresh cadence.
Device modifiers (mobile CVR ~30–40% lower → apply bid reduction). Dayparting — peak hours get +20–40% bid. Geo modifiers — top-converting cities get budget priority. Remarketing list bid layers.
Expected CTR, ad relevance, LP experience — the three QS pillars. QS 7+ means lower CPC for same position. I audit QS weekly and align ad copy to keyword themes and LP content for maximum relevance.
IS lost to budget vs IS lost to rank require different actions. Budget loss → increase budget or reduce bids on low-performers. Rank loss → improve QS, increase bids on key terms, tighten match types.
Top organic keywords → seed keywords for Search campaigns
High-engagement pages → proven landing pages for paid (real CVR data)
Organic audience behavior (device, hour, geo) → paid bid adjustments
High organic CTR blog topics → paid ad copy angles and messaging
Organic branded search volume → brand health & paid brand defense strategy
Paid search data validates keyword conversion rate → guides SEO prioritization
Paid ad copy winners → inform organic meta titles & descriptions
Paid audience segments → inform organic content calendar topics
Paid LP CVR data → guides organic CRO improvements
Paid funnel drop-off data → identifies content gaps for organic MOFU/BOFU
Ideal CPC varies by segment, device, and funnel stage. I set CPC targets per keyword group based on historical CVR and average order value — never platform defaults.
I work backward from CAC targets: if CAC target is R$500 and Lead-to-Customer rate is 20%, max CPL = R$100. Every CPL target is calculated, not guessed.
Target CPA is set based on LTV and margin, not arbitrary budgets. I activate tCPA bidding only after 50+ conversion events — never on fresh campaigns.
Break-even ROAS is calculated first. I consider scaling at 4x+ sustained over 3+ days. tROAS activates after 15–20 conversions/week minimum.
CTR is a proxy for creative relevance. Search benchmark: 5%+ for brand, 2–3% non-brand. Display: 0.35%+. Below benchmark signals ad copy or audience mismatch.
QS 7+ means paying less than competitors for the same position. Weekly QS audits optimize the three pillars: CTR, ad relevance, and landing page experience.
Target: 70%+ IS for branded terms, 40–50% for competitive non-brand. IS lost to budget and IS lost to rank require completely different strategic responses.
The multiplier metric. Moving from 2% to 4% CVR halves CPA without touching bids. LP optimization runs in parallel with every paid campaign I manage.
| Campaign Type | Funnel Stage | Best For | Key Signals to Monitor |
|---|---|---|---|
| Google SearchExact, Phrase, Broad Match | BOFUMOFU | High-intent prospects actively searching. Best ROI channel for B2B. Brand defense. Competitor targeting. | Quality Score, IS Lost to Rank, Search Terms Report, Auction Insights |
| Google DisplayResponsive Display Ads | TOFUMOFU | Brand awareness, retargeting, remarketing lists. Reaching audiences on publisher sites. | VCR, Frequency, Placement Report, View-Through Conversions |
| YouTube AdsIn-Stream, Bumper, Discovery | TOFUMOFU | Brand storytelling, product demos, warm audience remarketing. Powerful for high-ticket products. | VTR (View-Through Rate), CPV, Brand Lift, Earned Views |
| Meta AdsFacebook & Instagram | TOFUMOFUBOFU | Full-funnel capability. Interest-based cold, Lookalike, retargeting audiences. Lead Gen forms. Conversion campaigns. | Frequency (≤3.5), Ad Fatigue Score, CPM trend, ROAS at campaign level |
| LinkedIn AdsSponsored Content, Message Ads | TOFUMOFU | B2B demand generation, ABM targeting by job title/company/industry. Lead Gen Forms. | Lead Quality (MQL rate), CPL, Account Reach, Engagement Rate |
| Performance MaxGoogle All-Channels | BOFUMOFU | E-commerce with strong conversion history. Supplement Search, not replace it. Requires strong audience signals. | Asset Group Performance, Search Insights Report, Cannibalization vs Search |
| RetargetingAll Platforms | BOFU | Cart abandoners, LP visitors, video viewers, CRM uploads. Highest-intent audiences — typically 3–5× better CVR than cold. | Audience Size (min 1K), Frequency Cap, Overlap with Prospecting, ROAS vs Cold |
Algorithm optimizes to hit a target CPA. Most powerful with conversion history. Requires 50+ conversions in the past 30 days to be effective.
Best for e-commerce with varying order values. Algorithm maximizes conversion value rather than volume. Needs strong revenue data in tracking.
Spends full budget to get maximum conversions. No CPA constraint. Great for ramping new campaigns and feeding the algorithm during learning phase.
Manual CPC with algorithmic adjustments. Good middle ground where you want control but algorithmic assist. Less aggressive than fully automated strategies.
Unconstrained ROAS optimization. Algorithm chases highest-value conversions regardless of cost. Requires excellent revenue signal quality.
Awareness-focused bidding for TOFU campaigns. Optimize for reach and frequency, not clicks or conversions.
"7+ years transforming data into scalable, consistent growth."