Analytics
Read launch results, creator attribution, revenue evidence, objections, and the next product decision.
Analytics closes the launch loop
Analytics should connect the launch hypothesis to what happened: traffic, conversion, revenue, refunds, creator activity, objections, customer language, and next-step decisions. It should be context-aware for the selected product, launch batch, creator, or deal.
Payment events are the revenue source
Revenue should come from checkout, subscription, invoice, order, or imported payment events. A manual estimate can be useful for planning, but it should not be presented as confirmed revenue.
Data quality must be visible
Analytics should distinguish live connected data from imported, manual, fixture, or not-yet-wired data. Reports, exports, filters, and attribution views should be disabled or labeled when the underlying data is incomplete.
Measure more than sales
Launch learning often appears before clean revenue. Track the evidence that explains why a launch worked or did not work.
- Traffic quality: source, creator, campaign, link, code, and audience fit.
- Offer quality: click-through, checkout starts, objections, replies, and saves.
- Product quality: purchases, refunds, support questions, completion, and repeat demand.
- Creator quality: accepted deals, published deliverables, conversion, and audience feedback.
Creator attribution should be reviewable
Creator analytics should show which links, codes, content, and deal records contributed to the result. Attribution can be imperfect, so the interface should preserve the evidence behind a commission or performance claim.
Decide what happens next
Analytics should make the next decision easier: iterate the offer, change price, improve delivery, recruit different creators, relaunch, archive, or move the product into a larger build track.
FAQ
Can Analytics show real revenue before checkout is connected?
No. Without connected checkout, imported orders, or verified manual records, revenue should be treated as planning or placeholder data.
Why might platform analytics and TrendRise attribution differ?
Different systems use different windows, cookies, codes, click rules, refund handling, and event timing. TrendRise should keep enough source detail to explain the difference.
What should I do with a weak launch result?
Separate traffic problems from offer problems. If qualified people never saw it, fix distribution. If qualified people saw it and did not act, revisit the promise, format, price, or audience.