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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
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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

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.

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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.

Improve activation

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.

Lift retention

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

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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.

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Which of our services do you need?

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Funding

We'll email you shortly
Prefer to call now?
USA
+1 (347) 657 3386
UK
+44 203 870 3186