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Glossary

The terms we count with

Thirty-four concepts from reports and media plans — with worked numbers, so you can read our reports without an interpreter.

Metrics

what the report counts · 19

Cost per thousand impressions

CPM

Cost per thousand ad impressions. In influencer marketing, it is calculated from the actual reach of a post, not the subscriber count: a channel with 200,000 subscribers may get anywhere from 30,000 to 90,000 views per post, which changes the CPM by a factor of three.

Example. A channel with 200,000 subscribers; the post got 46,000 views and cost $1,000. CPM = $1,000 / 46 = $21.70. Calculating from subscribers would give $5 — four times more optimistic and wrong.

Reach CPA ER

Cost per target action

CPA

Cost of one action you consider a result: a signup, a deposit, an install. This is the only metric we use to cut a placement — reach and views do not factor into that decision.

Example. A flight cost $13,000 and delivered 840 verified signups. CPA = $15.50. If the cap is $13, the flight is unprofitable overall — but within it, four channels delivered $10 and two came in at $34. We cut the two, not the flight.

CPM ROAS Postback

Revenue per unit of ad spend

ROAS

Revenue divided by ad spend. For long-cycle products (fintech, SaaS), measuring ROAS on day seven is meaningless: two months can pass before a deal closes, so we lock the attribution window upfront.

Example. Spent $9,000; revenue from acquired users over 60 days was $43,000. ROAS = 4.8x. On day seven it was 1.3x — if we had evaluated then, the channel would have been cut.

CPA LTV Attribution

Lifetime value of a customer

LTV

How much revenue a customer generates over their lifetime. Sets the CPA ceiling: if LTV is $90, paying $100 for acquisition only works at a loss.

Example. Average order $27, purchases per year 3.1, margin 42%. LTV = $27 x 3.1 x 0.42 = $35. The CPA ceiling for one-year payback is $35, not $27.

CPA ROAS Retention

Engagement relative to reach

ER

Share of the audience that reacted to a post. A high ER on a large channel more often signals fraud than genuine engagement — we look at ER together with the distribution of reactions over time.

Example. A post with 46,000 views, 1,200 reactions and 40 comments. ER = 1,240 / 46,000 = 2.7%. The number itself is fine; what matters is the pattern: if 900 reactions arrived in the first ten minutes, the engagement was purchased.

Reach Fraud Audience audit

How many people saw it

Reach

Number of unique people who saw a placement. On Telegram it is post views over 48 hours; on YouTube it is video views; for stories it is unique viewers. These cannot be added together across platforms.

Where it breaks. A Telegram post got 46,000 views, a YouTube video — 120,000, stories — 18,000 unique viewers. Adding them up to 184,000 is wrong: some people saw both, and a story view and a completed video view are different events. They get added anyway, and the report says "reach 184,000" — a number that never existed.

CPM Impressions ER

How many times it was shown

Impressions

Total number of times an ad was shown, including repeat exposures to the same person. Always higher than reach. Confusing impressions with reach is the easiest way to inflate a report by a factor of two.

Where it breaks. The platform report says "1,400,000 impressions." Unique people behind them — 300,000. If the presentation labels the first number as reach, the figure grows almost fivefold without a single additional person actually seeing the ad.

Reach CPM

How many times per person

Frequency

Average number of times one person sees the ad. Above four is usually wasted budget and irritation.

Example. Reach of 300,000 with 1,400,000 impressions gives a frequency of 4.7. Above four, response usually drops and annoyance rises — the budget is better moved to a new audience.

Reach Impressions Creative burnout

Share of viewers who clicked

CTR

Share of viewers who clicked. In influencer marketing, a low CTR does not mean failure: part of the audience arrives via search, not through the link.

Example. Of 46,000 views, 690 clicked through — CTR 1.5%. Yet sign-ups totaled 210, of which 90 arrived via a branded search. Counting clicks only would miss 43% of the result.

CPA Attribution Creative

The same people counted twice

Audience overlap

Share of subscribers common to two channels. When buying across ten channels in the same niche, overlap can reach 40% — you pay twice for the same person.

Example. Ten channels in the same niche delivered a combined 610,000 views, but unique viewers totaled 380,000. Overlap of 38% — every third viewer was paid for twice.

Audience audit Frequency Reach

The watch-through curve

Retention

Share of viewers still watching at each second. A drop at second fifteen says more about the script than the total view count.

Example. Of 10,000 who started the video, 4,100 made it to second 15 and 1,800 to the end. The drop between seconds 12 and 18 means the script loses the viewer there, and that is the segment to reshoot.

Hook LTV ER

Cost per install

CPI

Price of one app install. In iGaming and crypto it means nothing on its own: half of the installs never reach registration, and cheap installs from incentivised traffic almost never reach a deposit. We look at CPI only next to the share of installs that reached the target action.

Example. Network A gives installs at $0.90, network B at $2.40. From A, 1.1% reach a deposit; from B, 6%. A deposit costs $82 via A and $40 via B. The cheap install turned out twice as expensive.

CPA Retention Deep link

Average revenue per user

ARPU

Revenue for a period divided by the number of active users. It shows how much an average player or trader brings and, together with CPA, answers the main question: does acquisition pay off. Do not compute ARPU over all registrations — half of them never pay.

Example. In a month, 2,400 active players brought $61,000. ARPU = $25. A deposit costs $40, so payback comes no earlier than the second month, and keeping the channel makes sense only if retention confirms it.

LTV Retention CPA

Share of users lost in a period

Churn

The share of users who stopped being active during a period. The flip side of retention: if 30 of 100 players are still playing after a month, churn is 70%. Churn shows which source brings people for the long run and which — for a single bonus.

Example. Channel A: of 500 players, 190 are active after 30 days, churn 62%. Channel B: of 500, 60 are active, churn 88%. At the same CPA, channel B is three times more expensive per player who stayed.

Retention LTV ARPU

A group of users from one week

Cohort

Users who arrived in the same period and are then counted together: how many of them pay on day 7, day 30, day 90. Only cohorts show whether traffic got better — total revenue grows from old players too.

Example. Week-one cohort: 1,000 registrations, 90 paying by day 30. Week-four cohort after new creatives: 1,000 registrations, 140 paying. Monthly revenue grew 20%, but it was the cohorts that showed the creatives did it, not the season.

Retention Churn LTV

The uplift that would not exist without the ads

Incrementality

The difference between what happened with advertising and what would have happened without it. Attribution credits a source with everything that passed through it; incrementality asks how much of that would have come anyway. Tested by switching a channel off in some geos or for part of the audience.

Example. Retargeting showed 1,200 deposits a month by attribution. Switched off in two of six countries: deposits there dropped by 140, not by the 400 expected from its share. The incremental contribution was a third of what was credited.

Attribution ROAS Cohort

Gross gaming revenue

GGR

Bets minus player winnings for a period — what the operator earned before bonuses, taxes and payment fees. In affiliate programmes the partner’s share is calculated from GGR or NGR, so it matters to fix in advance what gets deducted.

Example. Players wagered $400,000 and won $352,000. GGR = $48,000. If the contract is a share of GGR, the base is $48,000; if of NGR, bonuses and fees are deducted first, and the base may be half that.

NGR ARPU Rev-share

Net gaming revenue

NGR

GGR minus bonuses, gaming taxes, payment fees and sometimes anti-fraud costs. The base of most rev-share deals. Every deduction must be listed in the contract: “other operator expenses” without a list eats half the base.

Example. Monthly GGR $48,000. Bonuses $9,000, tax $6,000, payment fees $2,400. NGR = $30,600. A partner on 30% of NGR gets $9,180; on GGR they would get $14,400.

GGR Rev-share ARPU

Tagging and tracking

what is set up before launch · 10

Assigning a result to the source that produced it

Attribution

The rule that assigns a conversion to a source. With influencers, a direct click is rare: someone watches a video, then finds you through search the next day. That is why we use promo codes, deep links, and post-view windows.

Where it breaks. A person watches a video on their TV in the evening. In the morning they recall the name, search for it, and sign up from a work laptop. A click-based model sees nothing at all. A promo code catches it — if they remembered to write it down. A spike in direct traffic shows something happened, but not who caused it.

Postback Promo code Deep link

A callback reporting a conversion

Postback

A server-to-server request from your system to the tracker at the moment of a target action. Without it, we see clicks but not outcomes, and there is nothing to optimize against.

Where it breaks. The tracker sees 840 clicks and says nothing about how many converted to a deposit. With a postback, the same tracker shows 96 deposits and which channels produced them. Without it, the only thing to optimize is cost per click — which means optimizing for cheapness, not performance.

Attribution Tracking CPA

A link into a screen inside the app

Deep link

A link that opens a specific screen inside the app, not the home page. It shortens the path between the video and the action: the user does not have to find the right section themselves.

Where it breaks. A video about sending money abroad. A regular link opens the app's home screen, and the user hunts for the right section — half never find it. A deep link opens the transfer screen directly, and the share of users who complete the first action grows by 1.5 to 2x, with zero changes to the video itself.

Attribution Postback

Source markers added to a link

UTM tag

Parameters in a URL that tell your analytics system where the visit came from. They break the moment someone copies the URL by hand, which is why in influencer buying they supplement the promo code rather than replace it.

Where it breaks. The tag survives exactly until someone copies the URL from the address bar and sends it to a friend. The friend arrives as direct traffic. So UTMs are set, but results are cross-checked against the promo code rather than relying on UTMs alone.

Attribution Tracking

The system that records what happened

Tracking

The combination of tags, postbacks, and reports that ties a placement to revenue. It is configured before the campaign starts — there is no way to reconstruct the data after the fact.

Where it breaks. First week of the flight: our numbers show 210 sign-ups, your system shows 178. A 15% gap is normal; we look for the cause at week three. A twofold discrepancy means a lost tag. It needs to be found this week: the gap only grows, and by the end of the flight the picture is unrecoverable.

Postback UTM tag Attribution

Server-to-server event delivery

S2S postback

The registration or deposit event goes from the client’s server straight to the tracker’s server, bypassing the browser and the app. It does not depend on ad blockers, cookies or whether the user closed the tab. The only reliable way to reconcile deposits by source.

Example. With pixel tracking, 74% of deposits reached the tracker; the rest were lost to blockers and closed tabs. After moving to S2S, reconciliation with the CRM matched at 99.6%, and three sources that looked unprofitable turned out fine.

Postback Tracking Click ID

Unique click identifier

Click ID

An identifier the tracker assigns to every click and passes to the site or app. When the user registers, this number goes back in the postback, and the tracker knows which click, ad and placement the person came from. Without it, the postback says “there was a deposit” but not from where.

Example. The placement link did not pass the click ID — all deposits fell into “unknown source”. After fixing the link template, it became clear that two of fourteen creators bring 60% of deposits.

S2S postback Postback Attribution

How many days an action counts for a source

Attribution window

The period after a click or impression during which a registration or deposit is credited to that source. Seven days for clicks and one for impressions is the usual starting point; for long cycles (forex, fintech) the window is widened to 30 days, otherwise half the deals go to “organic”.

Example. A 7-day window: the source has 210 deposits, CPA $57. The same source with a 30-day window: 290 deposits, CPA $41. People took three weeks to decide. The source did not change — what we agreed to see did.

Attribution S2S postback Cohort

A label inside one source

Sub ID

An extra parameter in the link with which a source marks its internal units: a specific placement in the network, a creator, a creative, a date. One source can give ten sub IDs, and they show which placement inside the network works and which burns the budget.

Example. An in-app network delivered traffic as a single source with CPA $48. We asked for the placement sub ID: of 60 apps, 9 gave deposits at $22 and 40 gave none. We kept the nine; the network’s CPA fell to $27.

UTM tag Click ID Tracking

Planning

what unfolds over time · 9

The buying plan itself

Media plan

A list of placements with dates, formats, prices, and a forecast. It is assembled before any money is spent and serves as the document against which actuals are later compared.

Where it breaks. Thirty rows: channel, date, format, price, forecast. A month later, an "actual" column appears next to each forecast. If the two diverge by a factor of two, the team investigates where the estimate went wrong — rather than adjusting the forecast retroactively to make the report look clean.

Seeding CPA Flight

One advertising period

Flight

The time window for which a media buy is planned. Measuring results mid-flight is premature: conversions from the first placements have not yet matured.

Where it breaks. A six-week flight; at week three, CPA looks twice the target. Stopping is premature: placements from week one have not matured, and some users will convert at week five. The decision to cut a channel is not made until at least two weeks after its last placement.

Media plan Attribution Wave launch

A schedule that builds rather than peaks

Wave launch

A media buy where placements ramp up toward an event date — a listing, a release, a sales launch. It creates a peak in awareness right when it is needed, not a spread-out reach.

Where it breaks. Three waves toward a listing date: one month out — analytical deep-dives; two weeks out — responses to objections from comments on the first wave; final ten days — streams and promo codes. Budget split 30/20/50. The temptation to put everything into the last wave is strong and costly: on decision day you would be talking to people hearing the name for the first time.

Flight Media plan Listing

Going live on an exchange

Listing

The moment a token is added to an exchange. A separate campaign type is built around it: before the date you need interest, on the day itself you need volume, and afterward you need retention.

Where it breaks. The buy is almost always turned off the morning after the event — and that is a mistake. People who came in go looking for reviews, and there is nothing to find: everything was said before the date. Ten to fifteen percent of budget should be reserved for exactly this moment.

Wave launch KOL

Buying placements across many channels at once

Seeding

Buying placements across many channels at once under a single brief. It provides volume and the data to see which audience segments respond at all.

Where it breaks. Fifteen channels, one brief, identical budget per channel. Two weeks later, three channels deliver CPA at half the average, four come in at double, the rest are around the mean. Budget shifts to the three; the rest stay on the list for when the top performers burn out.

KOL CPM Media plan

When an ad set stops paying back

Creative burnout

The point when the audience has seen the video enough and stops reacting. Visible as a steady CTR decline while reach stays flat.

Example. A creative held a CTR of 1.6% for two weeks; on day 15 it dropped to 0.9%. Reach and audience did not change, seasonality was not a factor. The video has been shown to everyone it could reach, and the next impression goes to someone who has already seen it.

Creative Frequency

Buying by time of day

Dayparting

Limiting impressions to certain hours and days. For betting it is the evening before a match and the match itself, for casino — evening and night, for trading — session opens. During the day the same budget buys clicks from people who are not in the mood to play.

Example. 24/7 delivery: CPA $54. Kept 19:00–01:00 local time and weekends from noon: half the impressions, 12% fewer deposits, CPA $38. The saved budget went to a second region.

Media plan Flight Frequency

An intermediate page before the offer

Pre-lander

A page between the ad and the product site: a review, a comparison, a player’s story. It warms up and filters out the random, so fewer clicks reach registration and more reach a deposit. Mandatory where the platform does not allow a direct link to the product.

Example. Direct link: 100 clicks, 9 registrations, 1 deposit. Via a pre-lander comparing operators: 100 clicks, 6 registrations, 2 deposits. A third fewer registrations, twice the deposits.

CTA Hook Creative

A list of placements we do not buy

Blacklist

A list of placements, apps and creators excluded from buying: for fraud, audience mismatch, tone. It lives next to the whitelist and grows after every week; without it, a switched-off placement returns in the next flight under a different sub ID.

Example. Over a quarter, 214 apps from in-app networks made the blacklist. A new flight in the same network started with the exclusions: the first week gave CPA $31 instead of $52 last time.

Whitelist Fraud Brand safety

Checked by eye

people and materials · 15

Key opinion leader

KOL

Key Opinion Leader — a creator whose opinion the audience transfers onto the product. In Web3 this is often an account with 20,000 followers, but with direct influence over purchase decisions.

Where it breaks. An account with 20,000 followers in crypto Twitter: its readers are the ones deciding whether to buy the token. An account with 400,000 in entertainment: its readers come for the jokes. The first one costs more and delivers more — because you are buying trust transfer, not reach.

KOB UGC Seeding

A creator who buys, not just posts

KOB

Key Opinion Buyer — a creator who speaks as a user, not an expert. Works where expert opinions raise suspicion: mass-market products, apps.

Where it breaks. An expert says "I checked the ingredients, they are good" — the audience looks for the catch. An ordinary buyer says "I tried it, here is what happened after a month" — the audience believes them. For mass-market products the second approach works better, and it is not about budget — it is about who the category trusts.

KOL UGC

Content shot as if by a user

UGC

A video shot to look like it was made by an ordinary customer. Used in performance buying as an ad creative, not as a creator placement.

Where it breaks. A video shot to look homemade: phone in hand, kitchen, natural light. The same script read by a voiceover artist on a white background gets half the view-through rate. The difference is not production quality — it is that people trust the first and recognize the second as an ad within two seconds.

KOB Script Creative

The ad material itself

Creative

A specific video or visual asset. It burns out: the same creative shown to the same audience loses CTR within 10 to 14 days, so you build the library in advance.

Where it breaks. One video held a cost per order of $4.20 for two weeks. On day fifteen it jumped to $7.10 with the same reach and audience. Nothing broke: it had been shown to everyone who would ever be interested. What is needed now is the next creative, not a higher bid.

UGC Hook Creative burnout

The first three seconds

Hook

The opening of a video that determines whether it gets watched or swiped past. In vertical video, the hook accounts for more of the result than everything else combined.

Where it breaks. Of 10,000 who opened the video, 4,800 make it to second five. That means less than half will hear anything you say afterward. Replacing the first three seconds lifts that number to 6,200 — and the entire rest of the video starts performing 1.5x better, even though nothing in it changed.

Creative Retention Script

What the creator says, agreed in advance

Script

A second-by-second breakdown: what to show, what to say, where to name the product. The wording stays with the creator — otherwise the audience hears an ad and leaves.

Where it breaks. The creator receives not a script but a second-by-second breakdown with notes on what should be on screen. They choose the words themselves — the audience follows them precisely for how they talk. A verbatim script will be rejected by a good creator and read aloud by a bad one, and the audience can tell.

Hook Creative UGC

The call to action itself

CTA

What the viewer should do. One per video — otherwise the choice between two actions ends in no action at all.

Where it breaks. Add "subscribe to the channel" alongside "click the link" — and clicks will drop below what they were. The viewer faces a choice and often does neither. It is cheaper to make two videos than to lose conversions on one.

Hook Script CPA

Activity that was bought, not earned

Fraud

Bots and purchased views. On Telegram, it shows as sharp spikes in views during the first minutes; on YouTube, as geography that does not match the channel's language.

Where it breaks. A post hit 40,000 views in the first twenty minutes and stalled. A genuine channel reaches the same 40,000 over 24 hours and keeps adding views for a week. The shape of the curve separates purchased traffic from real popularity more reliably than any number in a media kit.

Audience audit ER

Vetting a channel before buying it

Audience audit

A channel review before placement: subscriber growth dynamics, view distribution, overlap with other channels, previous ad placements.

Where it breaks. Out of thirty channels submitted for approval, ten to twelve make it into the media plan. Filtered out: abrupt steps in the subscriber graph, reach three times below the median, three competitors advertised in the past month, comments made up of identical emoji.

Fraud ER Audience overlap

The approved list of placements

Whitelist

A list of placements approved by the client before the campaign starts. It saves time on per-placement approvals and prevents the brand from appearing where it should not.

Where it breaks. A list of sixty placements approved before launch. Without it, every placement is approved individually, approval takes three to four days, and by then the slot goes to another advertiser. With the list, buying moves at the speed of the platforms, not of email.

Brand safety Media plan

Where the brand must not appear

Brand safety

Rules restricting the ad's proximity to unwanted content. In influencer buying, this is not automated — it is a manual review of the creator's recent output.

Where it breaks. The check is not automated: we watch the creator's last ten episodes with our own eyes. An algorithm cannot tell the difference between analyzing a problem and promoting it, and the advertiser is the one held accountable for the context. Roughly one in ten of those who pass all other checks gets filtered out here.

Whitelist Audience audit

Showing the moderator a different page

Cloaking

Showing one page to moderation and another to the user. A way to pass moderation where the category is banned, and the fastest way to lose the ad account, the domain and the brand’s reputation. We do not do it and do not take projects that cannot work without it.

Example. A client came after a contractor who “knew how to pass moderation” got three accounts banned. The accounts cannot be restored, the domain is blacklisted. The launch started over with a permitted offer and a pre-lander — a month longer, but with no risk of a repeat.

Pre-lander Brand safety Blacklist

Registrations for the sake of the bonus

Bonus abuse

Users who register for the welcome bonus and never return: multi-accounts, wagering schemes, whole communities of “bonus hunters”. By CPA such traffic looks excellent; by retention and second deposit it is empty. Caught with cohorts and the share of repeat deposits.

Example. A source gave 400 deposits at $19 — the best CPA in the report. After 30 days, 11 people made a second deposit; other sources had 35–50%. The source was cut; the bonus money was wasted.

Fraud Retention KYC rate

Share of registrations that passed verification

KYC rate

The percentage of registered users who uploaded documents and passed the check. The first traffic-quality metric after registration: bots and bonus hunters never reach verification. Normal values differ by region, so we compare sources with each other, not with an abstract norm.

Example. Three sources with the same $2 registration CPA. KYC rate: 61%, 44% and 9%. The third source delivered bots; per verified user its registration cost $22 against $3.30 for the first.

Bonus abuse Fraud CPA

A payment reversed through the bank

Chargeback

A cardholder disputing a deposit through the bank. Some chargebacks are fraud with stolen cards that arrives together with low-quality traffic. A high chargeback share on a source is a signal to cut it before the payment provider cuts the operator.

Example. A source gave deposits at $28, an excellent result. Six weeks later, chargebacks came on 14% of those deposits; on other sources, under 1%. The source was closed, and the payment provider raised the operator’s reserve.

Fraud Bonus abuse NGR