Crypto companies lose momentum when growth relies on engineering resources permanently committed to protocol development. Dedicated growth engineering creates the experimentation infrastructure, analytics pipeline, and conversion optimization layer your growth team needs to move as fast as your market.
The Challenge
Growth experiments sit in the engineering backlog
Your growth team identified a hypothesis about onboarding flow that could double activation rates. The engineering ticket has been sitting in the backlog for three months because protocol development always wins the sprint. Every week the experiment stays untested costs you users, but the core engineering team has legitimate priorities. Without dedicated growth engineering capacity, growth hypotheses die in the backlog.
Your analytics infrastructure was not designed for growth
Your data pipeline tracks on-chain activity because that is what the protocol team needs. But your growth team needs to understand off-chain behavior – where users come from, where they drop off in onboarding, which acquisition channels produce users who retain versus users who churn after one transaction. The analytics gap between what your data infra captures and what growth decisions require means your team is making investment decisions with incomplete information.
Wallet connect friction hurts conversion, and nobody owns the solution
The gap between clicking a CTA and completing a first transaction involves wallet selection, gas estimation, network switching, and transaction signing. Each step loses users, and the total drop-off from landing page to completed action is often 85% or higher. This is a technical problem that sits between product engineering and marketing, and because nobody owns it, nobody fixes it. Growth engineering closes that gap.
A/B testing for web3 products is structurally more difficult
Standard A/B testing tools assume you can identify users by cookies or login. In crypto, users are pseudonymous wallets, sessions are fragmented across devices, and the line between your product and a third-party aggregator is blurred. Running clean experiments requires custom instrumentation that accounts for wallet-based identity, cross-platform attribution, and on-chain conversion events. Off-the-shelf tools do not support this.
How We Can Help
We begin by auditing your growth funnel from initial touchpoint to retained user. That means mapping each step from ad impression or referral through wallet connect, first transaction, and continued engagement – pinpointing where users drop off and measuring the revenue impact of every bottleneck. Most crypto companies have not approached this systematically because their analytics infrastructure was not designed to support it.
Using the audit findings, we build the growth engineering stack. This includes event tracking that connects off-chain behavior to on-chain actions, experimentation infrastructure designed for wallet-based identity, and dashboards that provide your growth team with real-time insight into funnel performance. The stack supports fast experimentation, rather than reporting alone.
Once the infrastructure is ready, we run the experiments. Common early wins include optimizing onboarding flows, reducing wallet connect friction, improving gas estimation, and personalizing landing pages by traffic source. Every experiment follows a disciplined hypothesis-test-measure cycle, with statistical significance required before a change becomes permanent.
We also develop the referral and viral mechanics specific to crypto – token-incentivized referral programs, ambassador systems, and protocol-level growth loops in which product usage naturally generates further adoption. These require engineering expertise in both growth mechanics and smart contract interactions.
The engagement expands your internal team's capacity. We teach your engineers growth engineering practices, document the experimentation framework, and create the CI/CD pipeline needed to ship growth experiments independently from protocol releases. The objective is a self-sufficient growth engineering function, not an ongoing reliance on external support.
What we deliver
- Full-funnel growth audit from acquisition through retention with quantified bottlenecks
- Growth analytics stack bridging off-chain behavior and on-chain conversion events
- Experimentation infrastructure supporting wallet-based A/B testing
- Onboarding and wallet connect optimization for conversion rate improvement
- Growth engineering playbook and team training for internal capability building
In crypto, the greatest growth lever is not marketing spend – it is removing the technical friction between intent and action. A user who clicked your CTA already wants to try the product. Growth engineering makes sure they actually can.
Our Methodology
The first two weeks focus on the growth audit. We instrument your entire funnel, locate the biggest drop-off points, and quantify the potential effect of resolving each one. The result is a prioritized experiment backlog ranked by expected lift and engineering effort.
During weeks three through six, we build the growth engineering stack and execute the first round of experiments. We deploy the analytics infrastructure, establish the experimentation framework, and ship the first three to five experiments aimed at the highest-priority bottlenecks uncovered in the audit. We measure results weekly using statistically rigorous analysis.
The last four weeks are dedicated to scaling the function. We document the experimentation process, train your engineering team in growth engineering practices, and set the operating cadence – weekly experiment reviews, monthly growth engineering retrospectives, and quarterly roadmap planning. By day 90, your team can independently run three to five growth experiments per sprint.
Our Working Process
The first 30 days focus on audit and infrastructure. We map the funnel, deploy analytics, and create the experimentation framework. Your engineering team joins architecture decisions to ensure the stack integrates smoothly with your existing infrastructure. Deliverable: a prioritized experiment backlog and an operational growth analytics dashboard.
Days 30-60 focus on experiment execution. We run the initial wave of high-impact experiments, release changes weekly, and measure outcomes with statistical rigor. Every experiment includes a defined hypothesis, success metric, and minimum sample size before we reach a conclusion. Your growth and engineering teams take part in experiment reviews.
Days 60-90 cover scaling and handoff. We increase experiment velocity, train your team on the complete process, and establish the operating rhythm. The engagement concludes with a working growth engineering capability within your company – not a collection of one-off optimizations that deteriorate over time.
Team structure: a senior growth engineer leads the engagement, supported by a data engineer and front-end optimization specialist. You provide access to your codebase and data infrastructure, plus at least one engineer who will own the growth function over the long term.
- Increased activation and onboarding completion rates
- Reduced wallet connect and transaction friction
- Sustained experiment velocity of three to five tests per sprint
- Growth analytics infrastructure with real-time funnel visibility
If your crypto / defi company needs growth engineering leadership, we should talk.
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Frequently asked questions
What does a growth engineering engagement cost for a crypto company?
A 90-day growth engineering sprint generally costs $50K-$100K, based on your product's complexity and the condition of your current analytics infrastructure. This includes the complete audit, stack buildout, initial experiment wave, and team training. Companies with mature engineering teams but no dedicated growth engineering function can begin with a targeted 30-day audit and infrastructure build for $20K-$35K.
How soon does growth engineering deliver measurable results?
Initial experiment results emerge within three to four weeks after the engagement begins. Improvements to onboarding and conversion rates often produce statistically significant lifts during the first month. The overall impact compounds as experiment velocity grows and more tests run concurrently. Most clients achieve their highest-impact wins within the first 60 days, as the obvious bottlenecks are addressed.
How will the growth engineering team collaborate with our current engineers?
We embed into your engineering team, working within your current codebase, CI/CD pipeline, and development processes. Growth engineering runs as a parallel workstream without competing against protocol development for resources. Your engineers join architecture reviews and experiment analysis, developing the skills needed to own the function once we leave. We contribute production code directly to your repo, not disposable prototypes.
How is Winston Francois different from directly hiring growth engineers?
Recruiting a growth engineer with expertise in both web3 and experimentation methodology can take months. We provide a team that has already developed growth engineering functions for crypto companies and can begin delivering results within weeks. We also supply the frameworks, analytics patterns, and experiment playbooks a solo hire would otherwise have to create from scratch. After establishing the function, we help you recruit the permanent team to operate it.
Can growth engineering integrate with our current analytics tools?
Yes. We work with any analytics and data infrastructure already in place – Mixpanel, Amplitude, Dune, custom on-chain indexers – filling gaps instead of replacing what already works. The growth analytics layer we create sits above your existing data pipeline, adding the off-chain-to-on-chain connection that standard tools cannot deliver. We avoid vendor lock-in and favor open-source solutions whenever possible.
Which experiments do you typically run for crypto products?
The most frequent early experiments focus on onboarding completion, wallet connect friction, first-transaction success rate, and referral program mechanics. From there, we test landing page personalization based on traffic source, gas estimation transparency, notification timing for re-engagement, and token-incentivized retention loops. Each experiment is tailored to your product and funnel data – we never apply a generic playbook.
