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A report lands on the fifth of the month. Spend is flat, conversions are up, cost per lead is down, and the last slide is a screenshot of an ad that did well. You read it, you feel vaguely reassured, and you approve the same budget again. Three months later nobody in the room can name a single decision that report changed.

That is the ordinary failure mode of marketing agency reporting, and it carries a price. TransUnion's research with EMARKETER found that 60% of marketers say internal stakeholders question the validity of their metrics at least sometimes, and nearly 29% report that up to 20% of their marketing budgets have been reallocated or put at risk due to doubts about measurement accuracy. Budget moves on suspicion. A better-looking dashboard does nothing about suspicion; a stated method does.

The conversions column is partly an estimate

Start with the headline count, because it is the number most owners read as a ledger. It is not one. Google uses data that doesn't identify individual users to estimate conversions that Google is unable to observe directly, and those estimates sit in the same Conversions column as the ones the platform did observe. The documentation is open about the reasoning: without modeling, reported conversions would only reflect the observable portion of conversions rather than the true campaign performance.

This is not a scandal, and it is worth saying so plainly before anyone gets excited. Google states that modeled conversions are included in your total reported conversions only when there's a high confidence that your ad resulted in conversions, that the rigor is there to avoid systematically over-reporting, and that where there isn't enough data to model confidently, no conversion modeling is provided. So treat it as a measurement method with a confidence threshold attached, then ask the operator's question: what share of this month's count was observed, and what share was inferred?

Then ask when the report was pulled. Google says modeled conversions can take up to 5 days to fully process and stabilize in Google Ads reporting, and that conversion values are subject to retroactive increases for a period of several days as data modeling is finalized. A month-end report compiled on the first or second understates the final week and will quietly disagree with the same report pulled a fortnight later. Neither version is wrong. The timing simply went unstated.

Good marketing agency reporting states its own settings

Attribution is a configuration, not a fact about your business. Google has gone as far as removing options: the first click, linear, time decay and position-based attribution models are no longer supported, and conversion actions that used them have been upgraded to data-driven attribution, which distributes credit based on your past data for that conversion action, using your account's data to calculate the actual contribution of each interaction across the conversion path. Google's own commentary on the habit most advertisers still carry is blunt: measuring on a last click basis gives all the credit for a conversion to the last-clicked ad and corresponding keyword, which ignores the other ad interactions customers may have had along the way.

LinkedIn puts the same choice in a dropdown where you can see it. Its Revenue Attribution Report lets the advertiser select a lookback window of 30, 60, 90, 180 or 365 days, and choose between impression-based and engagement-based attribution, specifying how many touchpoints are needed within that window to count as LinkedIn marketing influence.

Sit with what that means for a monthly deck. One account can produce materially different pictures of one month depending on settings a human selected. Two reports can disagree and both be honest. A report that does not state its model, its window and its pull date has not finished telling you what its numbers mean, and if any of the three changed mid-engagement, that belongs on page one rather than in an appendix.

Ask where the money physically went

The results line gets the scrutiny. The spend line usually gets a single figure and a nod. Give it the same treatment, because waste tends to pool rather than spread. The ANA's Q2 2025 Programmatic Transparency Benchmark reports that $26.8 billion in global media value is still lost each year to inefficiencies, that the TrueCPM Index dropped from 37.8% to 36.5% even as paid CPMs remained steady, and that while median made-for-advertising spend fell from 2.3% to 0.8%, top-quartile marketers still spent up to 28.7% on MFA domains.

That benchmark covers programmatic buying among large national advertisers, so it is not a description of your search and social account and its efficiency measures do not transfer to one. Borrow the principle instead: the median looks reassuring while the tail is ugly, and averages hide the specific account you own. What that buys you in a reporting conversation is a demand for itemisation. Media by campaign, platform and ad-tech fees, production costs, and the agency's own retainer, each on its own line. One blended spend number is a request to trust a total. If the fee structure itself is doing some of the hiding, our breakdown of what each agency fee model rewards is the other half of this question.

The five questions to ask in the meeting

More reporting is often a response to pressure rather than to a question. The CMO Survey's 2026 edition finds that pressure from CEOs, boards, and CFOs is reinforcing a short-term orientation, with the predominant response being a shift toward short-term impact over long-run gains (70.6%) and a return to established strategies (47.1%), and that rather than investing in deeper customer insights, most marketers focus on developing stronger performance tracking as the primary way to demonstrate value. Tracking becomes the deliverable. The five questions below are Arcane's operating standard, argued from the mechanics above rather than drawn from any study. Ask them out loud on the call, where the hesitation is visible.

  1. What in this number is observed and what is modeled, and when was it pulled? You want two figures and a timestamp. By the platform's own documentation, a month-end pull on the first is provisional.
  2. What attribution model and lookback window produced it, and did either change since last month? A switch to data-driven, or a window stretched from 30 days to 90, can bend a trend line while nothing at all happened in the market.
  3. Where did the money physically go? Itemised, including fees. If the answer arrives as one number, you have been handed a total rather than an account.
  4. What happened after the lead? Contact rate, booking rate, show rate, close rate, revenue. LinkedIn's documentation describes a CRM-joined report that surfaces revenue won, return on ad spend, and pipeline amount, so joining ad data to business outcomes is a configuration decision somebody either made or skipped. A report that stops at cost per lead stops just before the part that pays you, which is the whole argument in which numbers actually predict revenue.
  5. What decision does this report ask me to make, and what would have to be true for you to recommend the opposite? A report with no recommendation is a receipt. A recommendation that cannot be falsified is a sales document.

A model you can re-run on your own numbers

What follows is arithmetic, not a result. No account produced these figures, and nothing here is a benchmark. Swap in your own.

Assume a month with $20,000 of media spend and 400 reported conversions. That is $50 per reported conversion. Now ask question one, and assume the answer comes back that 300 of the 400 were observed. Measured against observed conversions alone, the cost is $66.67 each, a third above the headline. Same month, same spend, different sentence in the meeting.

Carry those 300 down the chain using four rates your CRM should know better than any ad platform does. Assume 70% are reachable, giving 210 contacts. Assume 40% of those book, giving 84 appointments. Assume 60% show, giving roughly 50 held calls. Assume 20% close, giving 10 customers. Divide $20,000 by 10 and you are at $2,000 of media per customer.

Now freeze the media and move one internal number. Lift the show rate from 60% to 75% and the same 84 appointments produce 63 held calls, which at the same 20% close rate is about 12 customers and roughly $1,587 of media per customer. Call it a 25% gain in customers with no change to budget, no new creative, and nothing for an agency to put in a deck. That is usually where to look when cost per lead is flat and revenue is flat alongside it, and it is why speed to lead belongs in this calculation rather than in a separate conversation about sales.

Read the next report with a pen. Circle every figure you could not reproduce from a method stated somewhere on the page, send that list over before the call, and watch what comes back. An operator-grade partner tends to welcome the list, because a stated method is what lets them defend a flat month that was actually a good one. A partner who treats the list as an accusation has told you something useful about the engagement, and it is far better to learn it in month two than in the month six fight. If you want these questions run against a live account rather than a deck, that is roughly what our diagnostic consists of.

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