Preboot for marketing
Ad platforms claim the sale. Analytics disagrees. The conversation where the customer decided is invisible to both. Preboot captures the chain — ad, message, reply, order — as one record. Loop watches spend against it and says what to cut while the budget lasts.
Sound familiar?
I can't tell which campaign actually made money.
The platform takes credit, analytics disagrees, and the sale happened in a WhatsApp thread neither sees.
By the time I know a campaign failed, the money's gone.
Month-end reporting is an autopsy. The budget was spent two weeks before anyone read the number.
When sales drop, I get theories.
The ad, the courier, the price, the season — everyone has one, nobody has evidence.
None of that is a reporting problem. It's a context problem — and it's the one we built the company around.
Where the money came from
Not modeled. Not attributed by a last-click rule. Captured — because the campaign, the conversation, and the order live in the same system.
Campaign → conversation → order is captured natively, so “which message made money” is a number — per campaign, per segment, per product.
Messages and orders share one warehouse — no pixel stitching, no attribution model to defend.
Real lift, separated from what would have sold anyway — no doubling down on coincidence.
Ad → DM → booking, captured end to end. Channels priced by what they produced — a booked visit, a viewing, an order.
“Cost per booked visit by campaign,” in plain words — charted, saved to your dashboard.
Budget shifts arrive with expected outcome and risk — a decision, not a hunch.
Tired creative, a saturated audience, a price objection — Loop names the driver, and the campaigns that bring buyers back.
Repeat revenue per source, as fact: the expensive channel may be sending customers twice.
Shifts arrive as a brief — this much to retention, expected CAC change, payback window.
Loop, on the spend
Every live campaign is watched while it runs. What arrives is not an alert — it is a call, with reasoning attached.
“Kill it, keep it, or rework it” — expected outcome and risk attached, in minutes rather than at month-end.
Verdicts rest on revenue per message, not opens — captured to the order, not modeled.
Fatigue is separated from a bad week — you never kill a winner by mistake.
A stockout, a slipping courier, creative fatigue, a competitor down the road — causes ranked with evidence before money moves.
Messages searched at scale for when complaints shifted — the why sits in the inbox.
It lands as a decision: the fix, expected recovery, the cost of doing nothing.
When a source stops performing, Loop arrives with the reallocation itself — numbers, reasoning, expected result, risk. You approve or hold.
Did the channel decline, or did your offer? Separated before any budget moves.
Which source sells: a fact from the chain, not an argument with the invoice.
Campaigns that earn their send
Blasting the whole list burns money and risks the number your business runs on. Both are avoidable.
Segments are mined from behavior, rebuilt continuously — every send lands on who the customer is now, not a stale export.
Warm-up, quality monitoring, and segment-first sending protect the number everything else depends on.
Loop drafts, targets, launches, watches; you approve. Losers get flagged before waste compounds.
Asked once, never bought — an audience you already paid for. Loop rebuilds that segment daily and launches to it.
Delivery, read, reply — tracked per message: measured like media, priced like a conversation.
Everything is approval-gated and reversible — including the decision to stop.
Running marketing on the record
The reviews that get skipped in a busy month are exactly the ones that would have caught the leak.
Sales, campaign returns, what changed, what you’ve been ignoring for weeks — delivered every Monday morning, through busy season and holidays.
It leads with what changed and what is unresolved — not a wall of numbers.
It ends in ranked decisions — fifteen minutes to act, not a day to analyze.
Plenty of messages, no orders. Loop finds where they stall — price shock, slow reply, missing photo — and drafts the fix.
The objection pattern is read from every stalled conversation — not a sample someone remembered.
The fix is concrete: reframed price, new anchor, a bundle — for your approval, reversible.
Before & after
Five more moments from the map — run by hand, and run on Preboot.
Reviews and reputation
You find out from a public one-star
Unhappy visits surface from the inbox first — apologies before it’s public, review requests only to the happy ones
Any marketing number
A request to someone, then a wait of days
Asked in plain words, charted in seconds, saved to your dashboard — no report builder to learn
Campaigns tied to bookings
Reach, likes, and a feeling
The message → conversation → booking chain captured natively, so a campaign is priced by what it filled
Ad budget decisions
Decided monthly, on last month’s numbers
Kill-or-scale briefs per ad, with reasoning and expected outcome — you approve, it executes
Product and offer launches
Gut feel, then a week of asking around
The launch reaches the customers whose history fits it, and its revenue is a fact by Friday
"Published averages" are industry benchmarks from public studies, not Preboot results. Your own numbers will live on your dashboard — that's rather the point.
In your industry
Every line above is industry-neutral on purpose. Here is what it turns into where you work.
We'll show you the chain behind it on your own data — the ad, the conversation, and the order it became. Message us on WhatsApp; our own number runs on Preboot.