iOS Custom Product Pages built for intent, not guesswork
iOS CPP design is how you turn the App Store into a conversion system, not a static listing. We create up to 35 Custom Product Page variants per app, then route Apple Search Ads and inbound traffic to the right page based on keyword intent, audience, and placement. You get a modular creative system, a testing roadmap, and measurement stitched to Apple reporting and SKAdNetwork realities. We integrate like your internal team, move fast on a monthly rolling basis, and give you a real-time dashboard with no commission on ad spend.
Segment intent first, then design the page
Most App Store pages try to speak to everyone and end up converting no one as well as they should. We start by mapping query and audience intent into clear cohorts: brand, competitor, category, long-tail feature, and problem-oriented terms. Each cohort has a different job-to-be-done and a different level of awareness, so the CPP narrative changes accordingly. Competitor cohorts often need switching benefits, feature gaps, value framing, and social proof. Category and generic cohorts typically need use cases, outcomes, and a simple story that makes the category click. High-intent feature terms benefit from specificity, paywall or onboarding transparency, and proof near the decision. Once cohorts are defined, we write a CPP brief per cohort with a single message anchor, key objections, and the proof required. The outcome is tighter relevance, higher conversion, and better cohort quality downstream.
Why this matters now
Creative that wins the first three screenshots
On iOS, the above-the-fold sequence does most of the work: icon, title, subtitle, the first three screenshots, and the preview poster frame. We design CPPs like a storyboard, with one clear narrative per ad group theme. For discovery traffic, we prioritise thumb-stopping first frames with high contrast, simple composition, and an outcome-led promise that is legible on smaller iPhones. For consideration, we build multi-frame walkthroughs that show how the app works, what you get, and why it is worth paying for, without stuffing text into every image. For conversion-focused CPPs, we reduce cognitive load and highlight reassurance, such as ratings, reviews, trust cues, and paywall clarity when it improves quality. We also ensure semantic consistency between screenshots, captions, and metadata so keyword-to-creative relevance holds. The outcome is better tap-through and tap-to-install efficiency without inflating bids.
Routing and ASA structure that keeps data clean
CPP performance is hard to interpret when your account structure is messy. We build a disciplined Apple Search Ads setup where each ad group maps to one CPP via Creative Sets, so lift is attributable. We separate placements into dedicated campaigns, typically Search Results, Search Tab, Product Pages, and Today Tab, because intent and creative requirements differ. We use match type controls, search match for controlled discovery, and negative keyword sculpting to stop intent bands bleeding into each other. Bids are tiered by funnel stage and CPA or tROAS targets where available, so you do not treat generic discovery the same as brand demand capture. We also extend routing beyond ASA when relevant, using unique App Store URLs for web-to-app ads, owned media, influencer links, and partner placements. The outcome is cleaner learning, safer scaling, and fewer false conclusions.
Where this fits
Localisation and device realities, handled properly
CPPs that perform in one country can fall flat in another because pricing sensitivity, cultural cues, and language density change how people read screenshots. We design localisation with intent, not direct translation: adapting value props, testimonials, and iconography to local context, and supporting right-to-left layouts when required. We also account for device-specific breakpoints, safe areas, and adaptive text, so screenshots remain legible across iPhone sizes and OS versions. Where regulatory or pricing constraints differ by region, we structure CPPs and campaigns country-by-country to avoid mismatched offers. Localisation is treated as part of the testing roadmap, not a one-off production task: we launch a baseline per region, then iterate based on CPP-level store metrics and downstream cohort signals. The outcome is more consistent global performance and fewer wasted taps caused by creative that does not travel.
What success looks like
Measurement under SKAdNetwork, without overpromising
CPPs give useful page-level signals, but not user-level truth, so measurement needs a practical blend of sources. We use App Store Connect CPP metrics such as impressions, product page views, conversion rate, and proceeds, then join them to Apple Search Ads reporting via disciplined naming and structure. For privacy-constrained attribution, we work with your SKAdNetwork setup, including conversion value mapping strategy where applicable, so you can evaluate cohorts beyond installs. We define success metrics by funnel stage: tap-through, tap-to-install, install-to-purchase, retained payer rate, ARPU proxies, and payback indicators, depending on what your data can reliably support. Where signal is weak, we lean on controlled tests, pre-post with safeguards, and incrementality designs like geo or audience splits. The outcome is decision-grade learning rather than dashboards full of noise.
A testing roadmap that compounds, not randomises
iOS CPP design is most powerful when it is run like an experimentation programme with one clear hypothesis at a time. We build a backlog across creative levers that matter: headline framing, screenshot composition, persona emphasis, hero feature sequencing, onboarding previews, and paywall transparency cues. Tests are structured as A/B rotations with stable keyword sets, budgets, and bids to reduce auction-driven variance. We avoid mixing multiple changes into one variant unless volume is high enough for multivariate approaches. Each test has defined success metrics and guardrails, so wins do not come from misleading promises that increase churn. Results are documented, rolled into evergreen CPP stacks by core use case, and refreshed seasonally or for promotions where it makes sense. The outcome is faster learning velocity and a growing library of proven CPP patterns.
Operating model: tight feedback loops with product and monetisation
CPPs set expectations for onboarding and the paywall, so performance improves most when marketing and product work together. We run a cross-functional rhythm that links CPP learnings to onboarding, trial mechanics, and paywall messaging, so cohorts land on an experience that matches what they were sold. We share weekly insights on which intents and narratives produce higher-quality users, then prioritise changes that reduce drop-off and increase retained payers. Where possible, we add automation via rules or scripts to shift bids and budgets towards CPP and intent combinations that show better marginal efficiency, while keeping manual oversight for brand safety and edge cases. Risks we actively manage include cannibalisation between intent bands, low-volume noise under SKAN, and over-optimising for installs at the expense of LTV. The outcome is profitable growth with fewer surprises after scale.