# Your idea backlog, in production every week. > Bixlow for growth teams is an experimentation system with an AI agent that turns a queue of prioritized hypotheses into A/B and A/B/n tests on the live site, and only declares a winner when the Bayesian engine has enough evidence. - Source: https://bixlow.com/en/solutions/growth - Language: en - Publisher: Bixlow You have more ideas than capacity to test them. Bixlow prioritizes the queue, the agent builds every test on your real site and the statistics engine tells you what worked. Your team decides; the heavy lifting no longer waits on anyone. - **Prioritization:** Reach × impact × confidence ÷ difficulty - **Tests:** A/B and A/B/n - **Who builds it:** The agent, no developer - **Verdict:** Bayesian, with guardrails ## What slows a growth team down isn't ideas It's the time between having an idea and knowing whether it worked. ### The backlog grows faster than it empties Ten ideas come in each week and one test goes out, if any. The dev queue decides what gets tested, not the expected impact. ### Priority goes to whoever shouts loudest Without a shared score, the idea that ships is the one pushed hardest in the meeting, not the one most likely to move the business. ### Results that don't survive a question A test gets stopped on day three because it's "winning", and nobody can explain later why it didn't repeat. ### Learning gets lost The hypothesis lives in a doc, the test in another tool and the result in a screenshot. Six months later nobody knows what was tested. ## A growth team's week with Bixlow A short loop that repeats: prioritize, build, launch, read. Every hypothesis stays linked to its workflow and its result. 1. **Prioritize the queue.** Each idea is a guided brief with a score from 1 to 100. Attach evidence, including CSV exports from GA or Shopify, and the agent analyzes it. 2. **The agent builds the tests.** Take the hypotheses at the top and the agent builds the Original and the variants as injected code. You review them in the preview. 3. **Launch without overlap.** Choose weights and traffic. Mutual exclusion groups keep a visitor out of two tests that overlap. 4. **Read the verdict and repeat.** The engine declares a winner only after minimum sample, minimum duration and probability gates. The agent reads the result and proposes the next hypothesis. ## What a growth team does with Bixlow Three pieces that turn a list of ideas into an experimentation program with a weekly rhythm. ### Hypothesis queue: One shared score for every idea Each hypothesis has its brief, its evidence and a score for reach, impact, confidence and difficulty on a 1–100 scale. - A step-by-step brief, linked 1:1 to its workflow. - An assistant that interviews you, drafts and edits the brief. - Evidence attachments, including CSVs the AI analyzes. ### A/B/n tests: More tests per week, same team The agent builds every variant on the live site. The Original is still your page, and each variant is a draft of its own. - Weight per variant and share of traffic that enters the test. - Deterministic assignment: every visitor always sees the same variant. - Mutual exclusion groups for tests that overlap. ### Bayesian verdict: Results that hold up under review Probability to be best, expected loss and a 95% credible interval, with gates that stop anyone calling a winner too early. - Minimum sample, a 7-day minimum duration and probability ≥ 95%. - Guardrails that warn if a secondary metric gets worse. - Automatic sample ratio mismatch (SRM) check. ## The agent clears the queue; your team decides what ships It doesn't replace your team's judgment: it removes the work that was slowing it down. ### You decide - Which business goal moves this quarter. - Which hypotheses go into this week's tests. - Which metrics must not get worse. - Publishing and declaring winners. ### The agent does - Drafts and scores hypotheses from your data. - Builds the Original and the variants of each test. - Sets up goals and guardrails. - Reads the engine's verdict and proposes the next idea. ### A hypothesis in the queue - **Hypothesis:** Showing free shipping on the product page reduces drop-off - **Evidence:** Shopify CSV: high drop-off on mobile - **Score:** 72 / 100 - **Test:** A/B/n · Original + 2 variants - **Guardrail:** Revenue per session - **Status:** Day 5 of 7 · 88% probability ## Bixlow Studio: Want more capacity without hiring? Bixlow Studio is senior strategists working alongside the agents. They can join your growth team or run the whole program. - Conversion audit and a prioritized roadmap. - New tests and changes every week on your site. - A monthly program report reviewed with a strategist. ## FAQ ### How is the priority score calculated? Reach times impact times confidence, divided by difficulty, on a 1–100 scale. The assistant helps you fill in each factor from the evidence you attach. ### Can I run several tests at once? Yes. Mutual exclusion groups guarantee a visitor never enters two overlapping tests, so results don't contaminate each other. ### How do I know a test is done? When the engine clears its three gates: minimum sample per variant, minimum duration (7 days by default), and a probability to be best of at least 95% with expected loss under the threshold. ### Does the AI decide who wins? No. The statistics engine computes the verdict. Neither the interface nor the agent computes its own; both show you the engine's, and declaring a winner is your call. ### Do I need a lot of traffic? Bixlow works for sites of any size. The engine accounts for traffic and the number of variants, and won't declare a winner until the evidence is there. ### Which plan includes A/B tests? A/B tests are part of the Premium plan. Goals and analytics are on every plan, so you can start by measuring. ## Put your backlog to work Install the script, load your first hypotheses and let the agent build the first test.