What we build
Every layer of acquisition — built as one system.
Channels aren't bought in isolation. Planning, bidding, creative, measurement, and first-party data move together — because that's how the underlying system actually learns.
Multi-channel paid-media operations
Meta, Google, TikTok, Snap, Pinterest, and LINE — planned, bought, and measured together. One acquisition motion, not six disconnected ad accounts fighting over last-click.
LTV-based bidding + lookalike modelling
Bids, value-based audiences, and lookalikes seeded from predicted LTV — not just first-order revenue. iOS / Android / cohort-weighted so the platforms learn what actually compounds.
Attribution across paid, organic, marketplace
Platform reports reconciled against MMM, incrementality lifts, and post-purchase surveys. One blended ROAS your CFO trusts — with clear credit to organic and marketplace.
Creative-test infrastructure
Library-driven testing with a managed cadence, winner promotion, and fatigue alerts. Winning variants compound — losers retire before they bleed reach.
First-party data activation
CAPI, Enhanced Conversions, server-side tagging, and MMM-ready event streams wired through Segment or mParticle — match rates monitored, PII redacted before the hop.
Retargeting, suppression, influencer, affiliate
Behavioural retargeting with suppression of recent purchasers, influencer + affiliate orchestration, and organic SEO / content pipelines feeding the same funnel view.
Who this is for
Built for brands where the second order matters.
Same stack, tuned per motion — the playbooks below share the LTV forecaster, MMM, and creative infrastructure. Only the bid logic, creative cadence, and measurement priors change per brand type. We start with the acquisition motion that unlocks the rest.
Premium DTC brands
Mid-to-high-scale ecommerce (USD 5M+ revenue / year) running own-brand stores — unified acquisition motion across paid, organic, and marketplace, measured to blended LTV.
Multi-market rollouts
Brands expanding from home market into neighbouring regions — one acquisition stack, per-market creative, per-market bid logic, per-market consent and tracking posture.
App-first ecommerce
Hybrid web + app storefronts — AppsFlyer / Adjust SDK data feeding MMM alongside web events. Blended install-to-repeat-purchase economics instead of siloed app metrics.
Lifecycle-led brands
Retention-heavy brands where the first order is a loss-leader. LTV-based bidding actively defended for the second purchase, not just optimised for the first conversion.
Marketplace + own-brand hybrids
Shopify / Lazada / Shopee / TikTok Shop / Amazon merchants — marketplace halo credited properly, own-brand cannibalisation modelled, budget allocated on true incrementality.
Creator-led launches
Influencer + affiliate programmes run as a measured channel, not a black box — creator briefs, UTM discipline, coupon tracking, and contribution reconciled to MMM.
Model families we deploy
No single model runs the whole acquisition motion. So we ensemble.
LTV forecasting, mix optimisation, fatigue detection, and audience modelling each answer a different question — blended together they replace gut-feel planning with a system that actually compounds.
Projects 90/180/365-day cohort LTV from first-order signals — product, channel, region, margin, creative. The anchor for every bid, bid cap, and budget-allocation decision downstream.
Marketing mix model with saturation curves, adstock, and regional priors — reconciles platform-reported conversions with incrementality reads and organic baselines.
Detects CTR / CPA decay on winning creatives before platform reports catch it — triggers variant-queue activation and budget tapering on fatigued assets.
Value-weighted lookalike seeds built from high-LTV customers, not high-order-count. Reduces the iOS-era audience noise and keeps the platforms optimising for profit.
Data sources wired into every decision
Every signal that moves the budget — integrated.
First-party events, CRM signal, ad-platform spend, server-side conversions, competitive intelligence, and a structured creative library — normalised into one schema, versioned with the models that consume them.
Explainability, not just predictions
One blended ROAS. With the receipts to back it up.
Platform reports, MMM contributions, incrementality lifts, and post-purchase survey signal reconciled into one view — with channel-level credit you can defend to the board, the auditor, and the head of every paid-media team.
- MMM contribution + incrementality lift per channel
- Platform-report reconciliation and CAPI match rate
- Creative-level fatigue curves with winner promotion log
- LTV / CAC and payback tracked per cohort and campaign
Why Axccelerate for acquisition
Not a media buyer.
A growth system.
A pure media buyer optimises the click. Our stack models the customer, tests incrementally, runs MMM, and reconciles every channel to LTV — the infrastructure a real growth brand actually needs.
Pricing
Priced to the motion, not the impression.
Acquisition engagements are custom — we scope against your category, markets, and platform stack before quoting.
Glossary
The vocabulary behind every acquisition decision.
A quick reference for the acronyms that show up in growth reviews — the terms your CFO, performance team, and measurement stack will all use.
- LTV
- Lifetime value
Total gross or contribution profit a customer generates across their relationship with the brand — usually horizoned at 90, 180, or 365 days for acquisition decisions.
- CAC
- Customer acquisition cost
Fully-loaded cost of acquiring a new customer across paid, organic, and partnership spend. Meaningful only when compared against LTV over a defined horizon.
- LTV / CAC
- Ratio of LTV to CAC
Headline acquisition health metric. Healthy brands target 3× or better at a 12-month horizon; below 2× usually means you're spending to grow unprofitably.
- MMM
- Marketing mix model
Statistical model estimating each channel's contribution to sales using aggregate spend, impressions, and external variables — survives cookie loss and iOS ATT disruption.
- CAPI
- Conversions API
Server-to-server conversion endpoint (Meta / TikTok / Snap / Pinterest equivalents) that restores signal lost to browser privacy defaults and ad blockers.
- Enhanced Conversions
- Google's server-side signal
Google Ads' equivalent of CAPI — hashed first-party identifiers sent server-side to improve match rates and attribution accuracy under cookie-loss conditions.
- Lookalike
- Lookalike audience
Platform-built audience modelled on a seed list. Value-based lookalikes (seeded from high-LTV customers) consistently outperform volume-based seeds for acquisition.
- Server-side tracking
- Server-to-server event delivery
Events fire from your server — not the browser — to ad platforms and analytics. Resilient to adblockers, iOS ATT, and broken pixels; authoritative source of truth.
- iOS ATT
- App Tracking Transparency
Apple's opt-in prompt introduced in iOS 14.5. Materially disrupts deterministic attribution on iOS; MMM, CAPI, and value-based bidding are the workarounds.
- Cohort analysis
- Grouping by first-order period
Slicing customers by the week or month of first order so you can measure how their behaviour compounds (or decays) over time — the basis for LTV forecasting.
- Incrementality
- True causal lift
The portion of conversions that would NOT have happened without the spend. Measured via holdouts and geo-splits — separates correlation from real media impact.
- Holdout group
- Exposure-suppressed control
A group deliberately withheld from ad exposure so lift can be measured against a genuine counterfactual. The cleanest — though not only — way to prove incrementality.
- Payback period
- Months to recover CAC
How long it takes the average customer's contribution profit to pay back their CAC. 6 months or less is typically the threshold for healthy reinvestment velocity.
- Blended ROAS
- Spend-weighted return across channels
Total revenue divided by total paid-media spend — reconciles platform-reported ROAS with organic / direct / marketplace halo. The ROAS your CFO actually wants.
Your acquisition system, engineered.
30-minute scoping with a senior growth engineer. You'll leave with a channel plan, measurement sketch, and a realistic first-90-days timeline — not a media-buy pitch.