Plenty of data, no priority
Reports show dozens of sagging metrics at once. Which to fix first — the worst CPA or the campaign burning the most money — ends up being decided by feel.
Valkiria reads the synced metrics of your campaigns over the last 30 days and turns them into a list of things worth fixing — each with a priority, a difficulty estimate and a link to the number it grew from. No recommendation is ever applied to the account by itself.
Reports show dozens of sagging metrics at once. Which to fix first — the worst CPA or the campaign burning the most money — ends up being decided by feel.
“Raise the bids” with no number attached reads as an opinion. The team quite reasonably asks for evidence, and the recommendation stalls indefinitely.
Recommendations scatter across threads and calls, and a week later nobody remembers what was done, what was rejected, and for what reason.
Campaign performance for the last 30 days is pulled from your connected platforms: CTR, CPC, CPA, ROAS, spend, conversions and revenue per campaign.
The model analyses only those numbers and returns tasks with impact, difficulty, confidence and a reference to the source behind each finding.
Mark a recommendation done or dismiss it, both behind a confirmation. Neither action writes anything into the advertising account.
A recommendation carries the platform, the campaign and the 30-day window it was derived from, so the reasoning can be checked in a minute.
Expected impact is signed as an estimate rather than a measured result: the fact is the metric the recommendation grew out of.
High, medium and low impact plus difficulty and confidence, so the work queue lines up without an argument about taste.
Targeting, budget and creative sit in separate tabs, so each task reaches the person who actually owns that part of the account.
Filter by status, category and impact, sort by date or impact: the ten lines you care about are two clicks away.
The whole list exports to PDF for a client report, and a new batch of recommendations arrives as an in-app notification.
From the synced metrics of your connected ad accounts over the last 30 days: CTR, CPC, CPA, ROAS, spend, conversions and revenue per campaign. The model analyses only that data, and every finding carries a reference to the campaign and the source of the number.
No. The button marks a recommendation as done in your list — it is a record of work, not a write into the ad account. Any change on the platform side goes down a separate path: new objects are created PAUSED, and edits to existing ones need explicit approval.
Expected impact is an estimate and it is labelled as one. The checkable fact is different: the campaign metric for the chosen period that the recommendation points at. That is the number to verify before you move a bid or a budget.
The list is still produced: when the provider cannot be reached, a threshold-based pass takes over — low CTR at sufficient impressions, high CPC, a campaign that has spent almost all of its budget. Those findings are tied to a specific campaign and its numbers too.
Yes, the whole recommendation list exports to PDF, either across all three tracks or for one selected campaign. You can filter by status, category and impact first, so only what matters ends up in the report.
Connect your accounts and get a list of what is worth fixing, with a source under every line. Your campaigns stay untouched while you read it.