Your stack has the data and still can't answer. beetree builds an AI you can ask: a warehouse in your cloud and a knowledge base that teaches it your business, with your metrics, your definitions, your prompts. Owned by you, so the next time you ask, you get an answer with receipts. And a growth agent that reads the books every morning and tells you what to do next.
Every tool sees a piece. No tool sees your customer.
Shopify sees the cancellations, never the reason. Klaviyo sees engagement dropping, but only for its list. Support tickets and reviews hold the “why,” in prose no dashboard reads. And wiring AI into each tool one connector at a time doesn't fix it: the model visits one silo at a time, with none of your definitions. The answer exists in your data. Nothing can find it.
Generic AI doesn't know what your contribution margin includes, when a subscriber counts as churned, or which of your three revenue tables is the truth. That knowledge lives in your team's heads and nowhere else, so the AI improvises: plausible SQL, confidently wrong. beetree writes it down as a knowledge base of your definitions, your metrics, and your prompts, and the guessing stops.
The accuracy isn't in the model. It's in the knowledge base. beetree builds it. You own it.
Land small, prove value, expand: greenfield-friendly, built beside the platforms you already run, and yours at every step.
The Customer Data AI Audit: a fixed-fee, two-to-three-week diagnostic: what can't your stack answer today, and what revenue hides in that gap? Value first, commitment later.
Your AI query layer: a warehouse in your cloud, a knowledge base that encodes your business, and a portal where you chat with your data, get answers with receipts, and wake up to a growth agent's recommendations. No rip-and-replace, and yours forever.
Your fractional data team: new sources, new questions, a knowledge base that keeps learning your business, expanding only as the ROI proves out.
Chat answers the questions you think to ask. The growth agent asks its own: every morning it reads your trusted layer, sizes the moves worth making, and keeps a short feed of recommendations. Open one for the evidence. Dismiss what doesn't fit. Mark what you did. It learns from every tap.
Shopify, Webflow, Amazon, Stripe, Square, Recharge, Klaviyo, Braze, Mailchimp, HubSpot, Gorgias, Zendesk, GA4, QuickBooks, plus the wholesale feeds and ops spreadsheets no dashboard reads. If it has an API or an export, it joins: modeled once, in your warehouse, feeding every tool downstream.
We go deepest on Shopify, Klaviyo, Stripe, and Braze. The point of an owned layer is that the list above never has to be complete. Run something we haven't named? It joins anyway.
We join your sources, benchmark what your current stack can and can't answer, quantify the revenue hiding in the gaps, and hand you the build spec for your owned AI data layer, yours whether or not we build it.
A benchmark of what your stack can and can't answer today: churn drivers, cohort LTV, the revenue your reports disagree on, with a dollar frame on every gap.
Every leak the join surfaces, priced: duplicate profiles, cancels your email tool never sees, renewals counted twice. The first answers usually pay for the audit.
A source inventory, data-quality read, and knowledge-base blueprint for your owned AI layer, plus a fixed-fee build proposal, whoever does the next phase.
Read-only access to start, roughly two hours of your team's time end to end, and a findings ledger that's yours to keep, nothing vendor-locked. See a real ledger →
Pick a question, we answer it: do your cancels reach your email tool? Do your revenue reports agree? What does your billing-tier math say?
The full diagnostic: sources joined, the ten-questions benchmark, retention and CLV baseline, and the build spec for your owned layer.
The AI query layer: warehouse in your cloud, a knowledge base of your business, and a portal where your team chats with the data and a growth agent volunteers the next move. Then a fractional data team to keep it compounding.
A recent build: a specialty coffee company: storefront, Stripe billing, a subscription app, Mailchimp for email. Healthy business, tidy-looking dashboards, and four questions its own stack couldn't answer. Today it runs an owned warehouse and a chat-with-your-data portal across orders, subscriptions, and customer records.
None of this was visible from inside any single tool: every dashboard looked fine on its own. The fixes ran on the stack the brand already owned: profiles merged, cancel events wired from billing into email, revenue reconciled to one number, and a win-back flow launched at subscribers who had never received a single message after cancelling. The stack was Webflow and Mailchimp rather than Shopify and Klaviyo: different logos, same physics. Your cancel events, duplicates, and double-counted renewals behave exactly the same way.
beetree is a customer data consultancy for growing commerce brands, founded on a simple idea: enterprise brands pay six figures a year for systems without a unified view of customer data or an AI layer on top. beetree builds you the version you own.
With 20 years in customer data and advertising, including enterprise customer data systems for major consumer brands, I've spent my career making customer data answer questions. beetree brings that discipline to your stack, whatever it's built on. AI does the heavy lifting behind the scenes, which is how beetree moves at agency speed; a real person stays accountable for the result.
Start with a free leak check (no call needed) or book twenty minutes for an honest read on what your stack can't answer today. No pitch deck either way.