Marketing role
AI Growth Hacker
An AI growth agent that finds where your funnel leaks, designs the experiment that tests the fix, and reads the result honestly.
Point it at your product analytics, your billing data and your signup numbers and it does the analytical half of growth work: mapping the funnel stage by stage, finding the step where most people leave, proposing experiments ranked by how much they could move, and reading the results without calling a coin flip a win. It writes the hypothesis before the test, not after.
Things you could ask for
Written the way you would actually say them. The agent plans the steps itself.
- “Using our PostHog funnels, show me signup to first value to paid, by week, for the last eight weeks — and tell me which step lost the most people.”
- “Here is our Stripe data for the year. Work out retention by monthly cohort and tell me whether churn is getting better or worse.”
- “Propose ten growth experiments for our onboarding, each with a hypothesis, the metric it moves, the sample size it needs and how long it would take to read.”
- “This A/B test ran for nine days. Read the export and tell me whether the difference is real, and what you would need to be sure.”
- “Every Monday, compare last week’s funnel with the four before it and send me a short note on anything that moved more than noise.”
What you get back
Funnel and cohort tables with the query or formula behind each number, a ranked experiment backlog in a Google Sheet or Notion page — hypothesis, metric, sample size, duration — and plain-language reads of finished tests that say what was learned, including when the answer is “not enough data”.
Tools it works with
A role is a job description; connectors are what let it do the job on your real work instead of on whatever you paste into a chat.
Where it is the wrong tool
- It does not change your product or your ad accounts. There are no advertising connectors, and the PostHog connector reads insights and events; launching a test, flipping a flag or moving budget stays with you.
- A cause it offers is a hypothesis. Ask for the events and queries behind any “why”, and treat an answer with no data under it as an opinion.
- Small numbers do not support big claims. On a few hundred users a week, most tests cannot reach significance in a reasonable time, and it will tell you so rather than declare a winner.
- Benchmarks it quotes from memory — “good” retention, typical conversion rates — are guesses. Ask for a source, or compare against your own history instead.
Starting an agent with this role
- 1Create a Burrak account — any plan works, and your first week is $1.
- 2In the Marketplace, open the Roles tab, find Growth Hacker and choose “Start an agent as Growth Hacker”. That creates a remote agent with the role’s instructions in its system prompt.
- 3Connect the tools it needs — PostHog, Stripe, Google Sheets, Notion, Attio, Tavily Web Search — from Connectors.
- 4Give it a brief. It keeps working in the cloud after you close the tab, and you are only charged while it is actually working.
The Growth Hacker role, in practice
- Will it run growth experiments for me?
- It designs them, sizes them and reads the results. Setting up the variant and launching it happens in your product or your testing tool. That split is deliberate: the design and the read are where most experiments go wrong, and they are the parts an agent can do well against your real data.
- Does it do growth hacks like fake scarcity or spam invites?
- No. It works on the funnel, the onboarding and the offer, and it will not design dark patterns, fake urgency, bought reviews or invite flows that message people without consent. Those tactics trade a short spike for trust you then have to rebuild.
- How is this different from the SEO Specialist?
- The SEO Specialist works on one channel — search. The Growth Hacker looks across the whole funnel, from where users come from to whether they stay and pay, and decides which channel or step deserves the next experiment. Use them together when search is the channel it picks.
Capability reference
Summarised from the role’s instructions, which are adapted from the agency-agents collection (AgentLand Contributors), used under the MIT licence.
- Funnel analysis and conversion optimisation at each stage, from acquisition to retention
- Growth experiment design: hypothesis, A/B and multivariate tests, statistical analysis
- Cohort analysis, attribution and North Star metric definition
- Referral programmes and viral loop design
- CAC against lifetime value, and payback period, as the test of a channel
Your AI assistant is waiting.
Put it to work today.
Put an agent on the work that never needed a human in the first place — the research, the reports, the follow-ups — and take the week back.
$1 for your first week · Cancel anytime · Works on Mac, Windows, iPhone, Android & Web