App optimisation that improves activation and retention

Find where users drop off, test fixes fast, and lift key metrics across onboarding, engagement and monetisation.

Evidence-led testing, weekly
Real-time performance dashboard
Top 1% growth talent

Diagnose the real bottleneck

App optimisation starts by finding the constraint, not guessing. We map your user journey from install to first value, then to retention and revenue. Using funnel and cohort analysis, we identify the biggest drop-offs and the behaviours that predict long-term value. You get a prioritised roadmap of experiments, with clear hypotheses and success criteria. This turns optimisation into a repeatable system rather than one-off tweaks.

Funnel mapping and events

Define critical steps like sign-up, onboarding completion and first value. Confirm tracking is consistent so you can trust drop-off points and compare cohorts fairly.

Cohort and segment analysis

Break performance down by channel, device, geo and user intent. Identify segments with strong retention and monetisation, then prioritise optimisations that move those cohorts.

Prioritised test backlog

Rank opportunities by impact and effort, then plan a weekly cadence. Each experiment has a hypothesis, metric and decision rule so the team can scale winners confidently.

Optimisation, not guesswork

Apps often stall because teams make changes without a clear hypothesis and cannot tell what worked. We run an evidence-led approach: define the problem, choose a lever, test, and keep a written learning log. This turns optimisation into compounding progress, because wins are rolled into playbooks and applied across flows. You get fewer debates and more clarity on what to build next.
  • Hypothesis-led experiment backlog
  • Weekly iteration and learning
  • Playbooks that compound results

Onboarding and activation wins

Most apps lose users before they experience value. We optimise onboarding by reducing steps, improving guidance, and removing friction in sign-up, permissions and first actions. We use in-app experiments to test different flows, prompts and value framing, then measure impact on activation and early retention. Where paid acquisition is running, we align ad promises with in-app reality to reduce low-quality installs and early churn.

Reduce time to first value

Identify the shortest path to a meaningful outcome and make it obvious. Simplify screens, remove optional steps, and guide users to the core action that predicts retention.

Test onboarding flows in-app

Run controlled tests on sign-up methods, permissions timing, tutorials and empty states. Measure impact on activation, not just completion, so changes create real behavioural improvement.

Align ads with experience

Match acquisition messaging to what users actually get in the first session. This reduces expectation gaps, improves early retention, and helps paid campaigns scale on higher-quality cohorts.

Retention, revenue and re-engagement

App optimisation is retention-first: improving what happens after day one is often the fastest route to sustainable growth. We build segmented lifecycle journeys across push, email and in-app messaging, with timing and frequency designed around user behaviour. We also optimise monetisation by testing pricing, paywalls and prompts in a controlled way, so revenue rises without damaging retention. The result is stronger LTV and more efficient acquisition.

Lifecycle messaging by behaviour

Segment users by actions and intent, then trigger messages that help them progress. Use re-engagement journeys that bring users back at the right moments, not generic blasts.

Monetisation and paywall testing

Test paywall timing, packaging and value framing with clear guardrails. Track revenue per user alongside retention so monetisation improvements do not create hidden churn.

Reacquisition and retargeting loops

Build win-back audiences from first-party behaviour and run retargeting that reflects where users dropped off. This can be more efficient than cold acquisition when LTV is proven.

Speed with transparency

App optimisation requires fast cycles and clear visibility. We operate in weekly sprints with a real-time dashboard, so you can see what is being tested and what is changing in performance. Our team integrates like in-house, so product, marketing and analytics are aligned rather than working in silos. This is how you break through plateaus without adding management overhead.
  • Weekly sprint operating system
  • Real-time performance dashboard
  • Integrates as internal team

SEO that compounds, not a checklist

Organic growth is a mix of technical hygiene, content that earns clicks, and authority building that is genuinely deserved. We treat SEO as a product, with a backlog and a cadence, rather than a one-off project. Technical work covers crawlability, site architecture, Core Web Vitals, schema markup and index management. On-page work is driven by search intent and the real questions buyers ask at each stage. Off-page focuses on link earning through useful assets, partnerships and digital PR rather than spam. For example, for a B2B brand we might build a set of comparison pages for demand capture, a small research piece to earn links, and a library of problem-led articles that support sales calls. The outcome is more qualified traffic, better brand credibility, and lower dependency on paid media over time.

More leverage than hiring

Building an in-house team for app analytics, lifecycle, paid growth and experimentation is expensive and slow. Growthcurve gives you a complete marketing department in one package, with specialists you can scale up or down. Engagements are monthly rolling, so you keep flexibility. You also avoid commission-based pricing on ad spend, keeping incentives aligned to results.
  • Complete team in one package
  • Monthly rolling flexibility
  • No commission on ad spend
What does app optimisation mean in practice?
App optimisation means improving the user journey so more people reach value, stick around, and generate revenue. It typically includes onboarding, activation, retention, monetisation, and the measurement needed to make good decisions. Instead of making changes based on opinion, you run controlled tests with clear success metrics. The outcome is a repeatable system for improving performance over time.
Which metrics matter most for app optimisation?
Start with metrics that reflect real behaviour: activation rate, retention by cohort, and revenue per user where relevant. Supporting metrics include funnel conversion between key events, time to first value, and reactivation rate. Avoid relying on vanity numbers like total installs without quality context. A smaller cohort with higher retention often produces better outcomes than larger low-quality acquisition.
How do you decide what to optimise first?
We identify the biggest constraint in the funnel by mapping events and cohort performance. If users do not reach first value, we focus on onboarding and activation. If activation is strong but retention is weak, we focus on engagement loops and lifecycle. We then prioritise experiments by expected impact and effort, so you get quick wins without losing sight of larger structural improvements.
How do you run experiments inside an app?
We start with a clear hypothesis and define one primary metric, such as activation or retention for a specific cohort. Then we ship a controlled change, like an onboarding flow variation, a new prompt, or adjusted paywall timing. We monitor results by segment and timeframe, and we log learnings. If results are positive and stable, we roll out more widely and build follow-up tests to extend the win.
Can app optimisation help paid acquisition performance?
Yes, because acquisition performance depends on what happens after the install. Better onboarding and retention raise LTV, which gives you room to bid more aggressively and scale campaigns. We also align ad messaging with the in-app experience, so users get what they expect in the first session. This reduces early churn and improves cohort quality, which platforms often reward over time.
How do you improve retention without spamming users?
We use behavioural segmentation and timing rules so messages are triggered by user actions, not a fixed schedule. That means prompts are relevant, and frequency stays controlled. We also test content and timing, and measure impact on retention and engagement, not just opens or clicks. The aim is to help users progress and return, while protecting trust and long-term value.
How do you optimise monetisation without hurting retention?
We set guardrails before testing, usually tracking retention alongside revenue per user. Monetisation changes like paywall timing, pricing and packaging are tested in controlled cohorts so negative side effects are detected early. We also improve value communication, not just pressure. Clearer benefits and better product education can lift monetisation while keeping users engaged and reducing buyer regret.
What tools or access do you need to start?
We typically need access to your analytics and event tracking, plus any lifecycle tools used for push, email or in-app messaging. We also align on the key events that define activation and retention for your product. If tracking is incomplete, we start by fixing measurement so optimisation decisions are reliable. From there, we build the first sprint backlog and ship tests quickly.
What do we get when working with Growthcurve?
You get a cross-functional team that plugs into your business and runs a structured optimisation cadence. That includes strategy, experimentation, analytics, lifecycle and paid growth where relevant, supported by a real-time dashboard. Engagements are monthly rolling, so you can scale support up or down. There are no commission fees on your ad spend, keeping incentives aligned to performance.

Lifecycle marketing that increases LTV

If you only optimise acquisition, you end up paying more for the same customers. We build lifecycle systems that raise retention and expansion, using email, SMS where relevant, and CRM workflows that feel personal without being creepy. We set up segmentation based on behaviour and value, then design flows for onboarding, activation, replenishment, win-back and referral. In practice that can include RFM modelling for ecommerce, lead scoring for B2B, or product usage triggers for SaaS. We also help you capture first-party and zero-party data with preference centres and progressive profiling, so targeting stays resilient as privacy changes. When we ran a lifecycle audit for one team, we found revenue sitting in overlooked moments, like post-purchase education and renewal risk signals. The outcome is a healthier blended CAC and a marketing engine that keeps paying you back.

Measurement you can trust and use

Attribution arguments waste time and block good decisions. We set measurement up so it is good enough to guide spend, creative and roadmap choices, and we are honest about what is knowable. Tracking work can include GA4 hygiene, conversion event design, server-side tracking where appropriate, and consistent UTMs. Reporting lives in a real-time dashboard, with views that match how you run the business, such as channel performance, funnel conversion, cohort retention and creative learnings. We also use incrementality thinking where it matters, like geo holdouts or controlled tests for bigger budget shifts. For example, if brand search rises after a video push, we look at the whole picture rather than declaring victory based on last click. The outcome is faster iteration and fewer surprises in board meetings.

Operating rhythm, SLAs and ways of working

Good marketing is mostly good operations. We set a working rhythm that keeps delivery moving and prevents strategy decks from becoming a comfort blanket. You get a named lead, specialist channel owners, and access to top-tier US and UK talent, scaled up or down based on your needs. We agree response times, approval flows and who owns what across creative, landing pages, tracking and budget changes. Campaign planning happens in short cycles, with clear priorities and a shared backlog, so work does not disappear into a black box. We also help your internal stakeholders, like product, sales and finance, stay aligned with what marketing is doing and why. The outcome is a calm, consistent cadence, less context switching, and a team that behaves like your internal staff while staying on a monthly rolling basis.

Why Growthcurve

Growthcurve is built for teams who want senior thinking and fast delivery without the overhead of building it all in-house. Our marketers have scaled startups to nine-figure valuations, and our clients have raised over $700M in funding, so we understand what investors and boards look for. You get a complete marketing department in one package, with specialists who integrate as your internal staff and can scale up or down as priorities change. We are an official Meta, Google, TikTok and Snap agency partner, and we have a deep creative engine, including unlimited ad creative production, because most growth ceilings are creative ceilings. You also get a proprietary suite of AI marketing tools and a real-time performance dashboard to keep decisions grounded. No long-term contracts, no commission fees on ad spend, just accountable work on a monthly rolling basis.

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