Questions, answered.

Product-level marketing allocation intelligence. It reads the true profit behind each of your products and gives you one clear call per product — where your next marketing dollar should go, and where it is being wasted.

Dashboards report revenue and platform ROAS and leave the interpreting to you. BOOLIC nets out COGS, returns, fulfilment, and fees to find true contribution margin, then issues a decision — Scale, Hold, Fix returns first, Reduce, or Pause — with the reasoning shown.

Per product, for two periods: revenue, units, customers/orders, landed COGS, returns, fulfilment cost, payment and platform fees, ad spend by product, and repeat-order rate. You can connect Shopify or drop in a two-month export — and during the pilot I help you assemble it.

Platform ROAS is built on revenue; true contribution margin nets out everything that actually eats the money. Net revenue comes after discounts, because promos quietly shrink what you really earned. Landed COGS — unit cost plus inbound freight and duties — is usually the biggest cost and the one most often understated. Returns net out refunded revenue and the cost of goods you can't resell, so a high-return product can't masquerade as a winner. Payment and platform fees are small per order but real. Fulfilment and shipping, net of what the customer paid, can flip a thin margin negative on heavy or bulky items. What's left is the money you actually have to spend on ads — so the call then weighs it against your CAC and scaling efficiency, and against repeat purchase value, because a thin first sale your customers reorder is worth more than a fat one they never repeat.

No — typing is the last resort. Most brands already keep costs in a spreadsheet, so you upload that sheet and BOOLIC maps the columns for you. If nothing's ready, you can start with rough estimates and get a first read immediately — the calls simply carry lower confidence until the numbers tighten, and BOOLIC fills in what it can work out itself (like payment fees) so you only supply what it can't. As BOOLIC grows it will also read costs straight from Shopify and pull them from your supplier invoices. Either way, you can correct and keep your costs current inside BOOLIC over time.

When you start, you tell BOOLIC what you're optimising for right now, and you can change it anytime. It shifts how the calls are weighted — it never changes the underlying margin math. Growth lowers the bar to scale products that still have room to run. Profitability raises that bar and protects margin, holding or reducing sooner when efficiency thins. Inventory efficiency aligns the calls with your stock — easing off products you're low on, leaning into clearing overstock. Product recovery is triage mode: it focuses on rescuing struggling products — fixing returns, flagging likely creative or acquisition problems, and pulling back to stop the bleeding while you address root causes. Same economics, different priority, sometimes a different call.

Each call comes with more than a label. You get the call (Scale, Hold, Fix returns first, Reduce, or Pause), the dollars of margin at stake, the numbers behind it, and — for Scale or Reduce — a suggested budget change shown as current versus proposed. Early on that suggestion is a conservative step toward the efficient point rather than a precise percentage, and it tightens as the system learns how your costs respond to spend. On timing, BOOLIC doesn't hand you a countdown: a Pause lasts until its cause is fixed (usually a price or cost change that makes the unit profitable again), and a Hold lasts until the economics move — it re-checks every period and tells you the condition that would change the call, not "pause for two weeks." When the real problem is returns or worn-out creative, the call says so and points you at it — but the operational fix is yours; BOOLIC makes the decision, not the ad.

Today, every call in the brief already carries its full reasoning — the drivers, the dollars at stake, and the condition that would change it — so "why this call?" is answered right on the page. Conversational ask-mode is on the roadmap as BOOLIC grows, and it will work through the AI assistant you already use rather than yet another chat window: you'll connect BOOLIC, ask "what should I scale this week?", and get BOOLIC's computed call relayed back. The important part is what stays the same: the assistant does the talking, BOOLIC's deterministic engine does the deciding. That's different from pointing an AI at your raw store data and letting it reason live — there, the analysis is the AI's and can vary. With BOOLIC, the answer exists before any AI is in the room: same inputs, same call, whichever assistant asks.

Your data is used only to produce your read. Nothing is shared, and nothing is published without your say-so.

No black box. BOOLIC is deterministic and transparent — every call traces back to numbers you can check yourself. The point is to show the work, not to ask you to trust the AI.

The calls are only as good as the margin data behind them, which is why the pilot includes building clean per-product margin and sanity-checking every call by hand. Treat each call as a decision aid: read the reasoning, and overrule it where you know something the data does not.

The pilot Allocation Read is free. I run these personally for a small number of brands while proving the calls in the real world.

About a week, mostly on me. You share the data, I build and run the read, and we meet for 45–60 minutes to walk the calls.

Scale (healthy margin, room to grow), Hold (steady, do not push yet), Fix returns first (returns are eating the margin), Reduce (pull spend back), and Pause (the economics are broken). See the full guide for what each one means.

A running record of each call, the choice you made, and what happened next — an accountable, compounding history of your allocation decisions that also helps the calls sharpen over time.

No. Shopify makes it quicker, but a simple two-month export works just as well — BOOLIC maps your columns for you.

Calls are blended across channels with a per-channel breakdown, so a product that does well on one store and loses money on another never hides inside an average.

Founder-led DTC brands (and the lean marketing teams who run their budget) that own their products, carry roughly 15–150 SKUs, and actively spend on Meta, Google, or TikTok.

The report — yours whatever you decide. No lock-in, no obligation, no pitch you did not ask for.

An optional follow-up where we look at whether the calls you acted on actually moved your contribution margin — the only proof that counts.

Send a note and I will set you up with the data template. Make an enquiry, or read about the pilot.