The marketing-attribution
glossary.

ROAS measures how much revenue you earn for every dollar spent on advertising. It is calculated as revenue divided by ad spend: a ROAS of 4 means you generated $4 for every $1 spent. A higher ROAS does not always mean a campaign is profitable; you also need to account for your margins and other costs.

Blended ROAS divides your total revenue by your total ad spend across all channels combined, rather than reporting ROAS per platform. Because each ad platform tends to over-count its own conversions, blended ROAS gives a more honest, whole-business view of whether your paid advertising is generating a return. Cavor calculates blended ROAS by reconciling actual payment data against spend across every connected platform.

MER compares total revenue to total marketing spend. It uses the same formula as blended ROAS (total revenue ÷ total spend) and most people use the two terms interchangeably; "MER" is simply the preferred label when you want to be explicit that all marketing investment counts (organic, email, and anything else), not just paid ads. MER is a useful top-line health check: if it falls, your overall marketing is getting less efficient even when individual channel ROAS numbers look fine.

CPM is the cost to show an ad one thousand times. It is the standard pricing unit for impression-based advertising on platforms like Meta and Google. A rising CPM means it is becoming more expensive to reach your audience, which typically raises all downstream costs like CPL and CAC.

CPC is the average amount you pay each time someone clicks on your ad. It is calculated by dividing total ad spend by the number of clicks. CPC is a key efficiency signal: lower CPC means more traffic per dollar, but traffic quality matters. A low CPC that does not convert still costs money.

CTR is the percentage of people who saw your ad and clicked on it, calculated as clicks divided by impressions. A higher CTR usually means your ad creative and targeting are well matched to the audience. CTR does not tell you whether those clicks converted. For that you need to look further down the funnel.

Impressions count how many times your ad was displayed, regardless of whether it was clicked. One person seeing the same ad three times counts as three impressions. Impressions are the starting point of the ad funnel: they measure reach and frequency but say nothing about engagement or conversion.

Reach is the number of unique people who saw your ad at least once during a given period. Unlike impressions, reach does not double-count the same person. The ratio of impressions to reach tells you your average frequency: how many times each person saw your ad.

CAC is the total cost to acquire one new paying customer, including all marketing and sales spend. It is calculated by dividing total acquisition costs by the number of new customers in a given period. CAC should always be compared to LTV. If it costs more to acquire a customer than they are worth, the business model does not work.

CPL is the average cost to generate one lead (a form fill, a call booked, or any other defined top-of-funnel action). It is calculated by dividing total ad or marketing spend by the number of leads produced. CPL is a useful mid-funnel metric but does not capture lead quality; you need conversion rate and revenue data to judge whether a CPL is actually good.

AOV is the average revenue generated per transaction, calculated as total revenue divided by number of orders. Increasing AOV (through upsells, bundles, or pricing changes) can improve profitability without acquiring more customers. AOV multiplied by purchase frequency is a simple first approximation of LTV.

LTV (sometimes called CLV or CLTV) is the total revenue a business can expect from a single customer over the entire relationship. It can be calculated historically or predicted using AOV, purchase frequency, and average customer lifespan. LTV is the ceiling on how much you can rationally spend to acquire a customer while remaining profitable.

The LTV:CAC ratio compares how much a customer is worth over their lifetime against what it cost to acquire them. A ratio of 3:1 is commonly cited as a healthy benchmark for SaaS and subscription businesses, meaning each customer returns three times their acquisition cost. A ratio below 1 means you are spending more to get customers than they generate in return.

Conversion rate is the percentage of people who complete a desired action (clicking an ad, submitting a form, purchasing, or booking a call) out of the total who had the opportunity. It can be measured at any stage of the funnel. Improving conversion rate compounds across the whole funnel: a higher lead-to-sale rate lowers effective CAC without changing ad spend.

Churn rate is the percentage of customers who stop doing business with you over a given period. High churn erodes LTV and forces you to acquire more customers just to maintain the same revenue level. Reducing churn often has a larger impact on profitability than increasing acquisition.

Attribution is the process of assigning credit for a conversion (a sale, a lead, or another outcome) to the marketing touchpoints that contributed to it. Because customers often interact with multiple ads, emails, and channels before converting, attribution is rarely straightforward. The model you choose determines which touchpoints get credit and therefore which campaigns look effective.

First-touch attribution gives 100% of the conversion credit to the very first interaction a customer had with your brand: the ad they clicked or the page they landed on before anything else. It is simple to understand and good for measuring what is bringing new people into the funnel, but it ignores everything that happened between first touch and the sale.

Last-touch attribution gives 100% of the conversion credit to the final touchpoint before the customer converted. It is the default model on most ad platforms and easy to implement, but it tends to favour retargeting and bottom-of-funnel channels while undervaluing awareness campaigns that introduced the customer in the first place.

Multi-touch attribution distributes conversion credit across multiple touchpoints in the customer journey rather than awarding all credit to a single interaction. There are several sub-models (linear, time-decay, position-based), each using a different logic for how to divide the credit. Multi-touch models give a more complete picture of which channels are working together to drive revenue.

Linear attribution is a multi-touch model that divides conversion credit equally across every touchpoint in the customer journey. If a customer touched four channels before buying, each receives 25% of the credit. It avoids the all-or-nothing problem of first- and last-touch models and is a reasonable baseline for businesses with longer, multi-step sales cycles.

Time-decay attribution assigns more credit to touchpoints that occurred closer in time to the conversion, and less credit to earlier interactions. The logic is that the final nudges before a purchase were the most influential. It is particularly useful for businesses with short sales cycles where recency genuinely matters more than first awareness.

The customer journey is the full sequence of interactions a person has with a business from first awareness to purchase and beyond. In a marketing analytics context, mapping the customer journey means tracking every ad click, page visit, lead form, call, and transaction in chronological order. A complete journey view makes it possible to apply attribution models accurately and to understand where drop-off happens.

A cohort is a group of customers who share a common characteristic, usually the time period in which they first purchased or signed up. Cohort analysis tracks how those groups behave over time, making it easier to measure retention, LTV, and churn at a level of detail that aggregate averages obscure. Comparing cohorts acquired from different channels can reveal which sources produce the highest-value customers.

A first-party pixel is tracking code hosted on your own domain that collects visitor and conversion data directly, without routing it through a third-party ad platform. Because the data is yours and originates from your server or domain, it is not affected by browser cookie restrictions or ad blockers in the same way third-party pixels are. First-party pixels also allow you to attribute conversions over longer windows than ad platforms typically support. Cavor's pixel uses this approach to capture click-to-revenue attribution across your full sales cycle.

Server-side tracking means sending conversion and event data directly from your server to an ad platform or analytics system, rather than relying on JavaScript running in the visitor's browser. It bypasses ad blockers and browser privacy restrictions, and gives you more control over what data is sent and how. Server-side tracking is increasingly important as browsers restrict third-party cookies.

The Conversions API (originally Meta's term, now common across platforms) is a server-side integration that lets you send conversion events directly from your server to an ad platform's API. It complements or replaces browser-based pixels and improves signal quality for ad platform optimization algorithms. Sending rich, matched conversion data via CAPI typically improves attribution accuracy and ad delivery performance.

UTM parameters are tags added to the end of a URL to identify the source, medium, campaign, and other attributes of incoming traffic. When someone clicks a link with UTM tags, analytics tools read those parameters and attribute the session to the correct source. Consistent UTM tagging across all campaigns is the foundation of reliable attribution, allowing you to trace leads and revenue back to specific ads and campaigns.