Marketing Metrics

Click-through rate measures the percentage of people who click on a link, ad, or call-to-action after seeing it. It is one of the most fundamental engagement metrics in digital marketing, connecting impressions to action and serving as an early indicator of campaign relevance and audience targeting quality.

Cost per click measures the average price you pay each time a user clicks on your ad. It is the foundational pricing metric for pay-per-click advertising and a critical input to [Customer Acquisition Cost](/glossary/saas-metrics/customer-acquisition-cost), connecting ad spend directly to traffic volume.

Cost per acquisition measures the total cost to acquire a single converting user, whether that conversion is a purchase, sign-up, or lead. CPA is the bottom-line efficiency metric for paid marketing, connecting ad spend to actual business outcomes rather than intermediate metrics like clicks or impressions.

Cost per lead measures the average amount spent to generate a single lead. It is the primary efficiency metric for demand generation teams, connecting marketing spend to pipeline volume and serving as an early indicator of whether campaigns are attracting potential customers at a sustainable cost.

Cost per mille (CPM) measures the cost of one thousand ad impressions. It is the standard pricing and benchmarking metric for display, video, and brand awareness campaigns where the primary objective is reach rather than clicks or conversions.

Return on ad spend measures the revenue generated for every pound spent on advertising. It is the primary profitability metric for paid media, telling you whether your ad campaigns are generating more revenue than they cost and by how much.

Bounce rate measures the percentage of visitors who leave a website after viewing only one page without taking any further action. It is a key engagement metric that signals whether your content and user experience meet visitor expectations set by the referring source.

A marketing qualified lead is a prospect who has demonstrated enough engagement or fit to be considered ready for sales outreach. MQL is the handoff point between marketing and sales, making it one of the most important and most contested metrics in B2B organisations.

A sales qualified lead is a prospect that has been vetted by the sales team and confirmed as a genuine sales opportunity worth pursuing. SQL represents the point where a lead transitions from marketing-generated interest to sales-accepted pipeline.

Marketing ROI measures the return generated by marketing investments relative to their cost. It is the definitive metric for evaluating whether marketing spend is creating or destroying value, connecting every pound invested to the revenue or profit it produces.

Email open rate measures the percentage of delivered emails that are opened by recipients. It is one of the most widely tracked email marketing metrics, though recent privacy changes have made it less reliable as a standalone indicator of engagement.

Organic traffic refers to website visitors who arrive through unpaid search engine results. It is the most cost-efficient acquisition channel for most businesses, compounding over time as content matures and domain authority grows.

Conversion rate measures the percentage of visitors, users, or leads who take a desired action, such as making a purchase, signing up for a trial, or submitting a form. It is the fundamental metric for evaluating the effectiveness of any acquisition funnel, landing page, or marketing campaign.

Ad revenue is the total income a business generates from displaying advertisements to its audience. It is the primary monetisation model for media publishers, ad-supported apps, and platforms that offer free products funded by advertising.

Brand recall measures the percentage of a target audience who can name your brand unprompted when asked about a product category. It is the strongest form of brand awareness and a leading indicator of market share and purchase intent.

Branded search traffic is the volume of website visitors who arrive through search queries that include your brand name or branded terms. It serves as a real-time, quantitative proxy for brand awareness and demand generation effectiveness.

Pages viewed per session measures the average number of pages a visitor views during a single visit to your website. It is a core engagement metric that reflects content quality, site navigation effectiveness, and the depth of visitor interest.

Percentage of new users measures the proportion of total website visitors who are visiting for the first time. It reveals the balance between audience acquisition and audience retention, and signals how effectively a business is expanding its reach.

Press clippings measure the number and quality of media mentions a brand receives across newspapers, magazines, online publications, broadcasts, and podcasts. They are a core earned media metric used to evaluate the effectiveness of public relations efforts.

Social media mentions measure the volume and sentiment of public references to your brand, products, or related terms across social platforms. They serve as a real-time indicator of brand visibility, reputation, and audience engagement in the social conversation.

The viral coefficient, also known as the K-factor, measures the average number of new users that each existing user generates through referrals, invitations, or sharing. A viral coefficient above 1.0 means each user brings in more than one new user, creating exponential growth.

Website traffic growth measures the rate of increase in total website visitors over a defined period. It is the top-level indicator of whether a business is successfully expanding its digital audience and a prerequisite for scaling online revenue.

Unsubscribe rate measures the percentage of email recipients who opt out of future communications after receiving a message. It is a direct signal of audience dissatisfaction and, when tracked alongside other email metrics, reveals whether your content, frequency, or targeting is misaligned with subscriber expectations.

Form conversion rate measures the percentage of users who view a form and successfully submit it. It is a critical micro-conversion metric that directly impacts lead generation, sign-ups, and revenue, making it one of the highest-leverage optimisation targets in digital marketing.

Email click-through rate measures the percentage of email recipients who click on at least one link within an email. Unlike general CTR, which spans ads and search results, email CTR specifically captures how well your email content and calls-to-action drive recipients from the inbox to your website or landing page.

Impression share measures the percentage of eligible impressions your ads actually received. It tells you how much of the available opportunity you are capturing and, critically, how much you are missing due to budget constraints or ad rank limitations.

Quality score is a diagnostic metric in Google Ads that rates the quality and relevance of your keywords, ads, and landing pages on a scale of 1 to 10. It directly influences your ad rank and cost per click, making it one of the most important factors in paid search efficiency.

Email deliverability rate measures the percentage of sent emails that successfully reach the recipient's inbox rather than being blocked, bounced, or routed to spam. It is the foundation metric for every email marketing programme because no other email metric matters if the message never arrives.

Campaign conversion rate measures the percentage of campaign recipients or visitors who complete a desired action, such as making a purchase, submitting a form, or signing up for a trial. It is the definitive measure of whether a marketing campaign is achieving its objective, connecting audience reach to business outcomes.

List growth rate measures the pace at which an email subscriber list expands over a given period, accounting for new subscribers, unsubscribes, and bounces. It is the health indicator for the top of your email marketing funnel, revealing whether your audience-building efforts are outpacing natural list attrition.

Exit rate measures the percentage of pageviews on a given page that were the last in a session. Unlike bounce rate, which only counts single-page sessions, exit rate applies to all sessions regardless of how many pages the visitor viewed before leaving. It reveals which pages are most commonly the final stop in a user journey.

Pages per session measures the average number of pages a visitor views during a single session on your website. It is a core engagement metric that indicates how effectively your site architecture, content, and internal linking encourage visitors to explore beyond their landing page.

New user rate measures the percentage of website visitors who are visiting for the first time within a given period. It indicates how effectively your acquisition channels are reaching new audiences versus re-engaging existing ones, and it shapes how you balance growth investment against retention efforts.

Goal completion rate measures the percentage of sessions in which a visitor achieves a predefined objective, such as completing a purchase, submitting a form, downloading a resource, or reaching a specific page. It is the metric that directly connects website activity to business outcomes by quantifying how often visitors do what you want them to do.

Ad copy testing analysis is the disciplined comparison of two or more ad copy variants to learn which messaging drives better performance against a chosen metric. It replaces opinion about which headline or hook works with measured lift and statistical confidence, so creative decisions rest on evidence rather than taste.

Ad frequency is the average number of times a single person sees your ad during a given period. Analysing it tells you whether you are reaching new people or repeatedly hitting the same audience. It is the bridge between raw impressions and the unique reach those impressions actually delivered.

Attribution modelling is the method used to assign credit for a conversion across the marketing touchpoints a customer interacted with before they bought. It turns a list of clicks, opens, and visits into a defensible answer to the question of which channels actually drove revenue. Different models split that credit in different ways, so the model you choose changes which channels look effective.

Audience segmentation is the practice of dividing a customer base into distinct groups whose members share traits or behaviours that make them respond to marketing in similar ways. The aim is to stop treating one average customer and start treating each group on its own terms. Well-built segments lift response because the message, offer, and timing fit the group rather than the mean.

Audience segmentation analysis is the work of examining your defined segments to confirm that they differ in value, behaviour, and response in ways that justify treating them separately. Where segmentation creates the groups, the analysis judges whether those groups are real, distinct, and worth the effort. It turns a set of labels into evidence about where each marketing pound should go.

Average position is the mean ranking your pages hold across the search queries they appear for, weighted by how often each query is shown. It tells you, on average, how high up the results page your content sits. A lower number is better, because position one is the top of the page.

Bid strategy performance analysis is the evaluation of how each bidding approach in a paid-media account turns spend into conversions and revenue. It compares strategies such as manual CPC, target CPA, and target ROAS on cost, efficiency, and outcome metrics. The goal is to find which bidding method delivers the best return for each campaign and budget level.

Broadcast vs campaign performance is the side-by-side comparison of single one-off sends against structured multi-step campaigns, measured on the same outcomes so a team can see which approach earns its place. A broadcast goes out once to a list; a campaign unfolds as a planned sequence. Comparing them on equal footing shows where each delivers value and where one is quietly carrying the other.

Campaign attribution analysis is the practice of assigning credit for a conversion across the marketing touchpoints a customer interacted with on the way to buying. It turns a single sale into a distribution of influence across channels, campaigns, and ads so spend can be judged on the value it actually creates. The model you choose decides how that credit is shared, which is why the same conversion can look very different under different rules.

Campaign performance comparison is the practice of evaluating multiple marketing campaigns against the same normalised metrics so they can be ranked fairly. It puts campaigns of different size, channel, and goal onto one scale so the team can see which earned the most return per pound spent. It is how a marketing team decides where the next budget should go.

Campaign performance ROI is the financial return a campaign earns relative to its cost, measured across the full path from spend to closed revenue. It connects the performance metrics a campaign produces, such as clicks and leads, to the profit those metrics ultimately generate. It answers whether a campaign performed not just busily but profitably.

Campaign ROI is the net profit a marketing campaign generates expressed as a percentage of its total cost. It tells you whether the money spent on a campaign came back with a return or whether it was a loss. Campaign ROI turns marketing from a cost centre into a measurable investment.

Cross-campaign performance analysis is the practice of comparing marketing campaigns on a single, normalised return basis so spend can be moved to the campaigns that produce the most value per pound. It puts campaigns with different budgets, channels, and goals on the same scale. The aim is not to rank campaigns for their own sake, it is to decide where the next pound should go.

Customer lifetime value from ads is the total profit a business expects from a customer acquired through paid advertising, across the whole relationship. It attributes lifetime value back to the campaign or channel that won the customer, so you can judge ad spend on the revenue it produces over years rather than the conversion it produced today. Two channels with identical acquisition cost can deliver very different lifetime value, and this metric exposes the difference.

Customer lifetime value from email is the total profit a business earns from a customer over their relationship, attributed to the email programme that nurtured and retained them. It measures email not as opens and clicks but as the revenue it sustains across years. Because email mostly works on customers you already have, its lifetime value comes from keeping people active and buying again rather than acquiring them in the first place.

Customer reactivation rate is the percentage of previously churned or dormant customers who return to active, paying status within a defined period. It measures how effectively a business recovers lost revenue rather than always replacing it with new acquisition. A healthy reactivation rate lowers the effective cost of growth because winning back a known customer is usually cheaper than acquiring a stranger.

Dayparting analysis is the practice of breaking performance down by hour of the day and day of the week to find when your spend, traffic, or campaigns actually perform. It exists because a daily average flattens out the truth: the same advert can return three times as much at 8pm as it does at 3am. Dayparting turns that hidden pattern into a budgeting and scheduling decision.

Email attribution analysis is the process of assigning revenue and conversions to email campaigns based on the part each email played in a customer journey. It answers a single question: how much of the outcome would not have happened without the email. Done well, it turns email from a channel people assume works into a channel with a measured, defensible contribution to revenue.

Email deliverability analysis is the process of measuring whether sent email reaches the inbox rather than the spam folder or being blocked entirely. It separates the share that was accepted by a mailbox provider from the share that actually landed where a person would see it. Done well, it explains a fall in opens and clicks that has nothing to do with the message and everything to do with where it was filed.

Email engagement cohort analysis is the practice of grouping subscribers by when they joined and tracking how their engagement changes in the weeks and months that follow. It replaces a single blended open or click rate with a view of how each intake behaves as it ages. Done well, it shows whether engagement is genuinely improving or whether a flood of new subscribers is masking decay in the people who joined earlier.

Email engagement rate is the percentage of delivered emails that triggered a meaningful interaction, such as an open, click or reply, within a defined window. It tells you whether the people receiving your emails are actually paying attention, rather than whether the email simply landed in the inbox. A healthy engagement rate is the difference between a list that compounds in value and one that quietly decays.

An email engagement score is a single weighted number that summarises how actively an individual recipient interacts with your email, combining opens, clicks, replies and recency into one figure. Unlike a list-wide rate, the score lives at the level of one person, so it can rank, segment and route recipients by how warm they really are. It turns scattered behavioural events into a value you can act on.

Email engagement scoring is the model and process that assigns each recipient a weighted score from their email behaviour, then keeps that score current and routes recipients by tier. Where a single score is a number, scoring is the whole system that produces it, including the weights, the decay, the refresh cadence and the actions each tier triggers. It is the engine that makes engagement data operational rather than merely observed.

Email frequency optimisation is the practice of finding the number of emails per subscriber per period that maximises total engagement and revenue without driving unsubscribes, spam complaints and inbox fatigue. It treats send cadence as a variable to tune rather than a fixed habit. The goal is the highest sustainable output per subscriber over time, not the most sends this week.

Email funnel analysis is the practice of tracking how recipients move through each stage of an email campaign, from delivered to opened to clicked to converted, and measuring the drop-off at every step. It turns a single open or click number into a stage-by-stage diagnosis. The point is to find the exact stage where prospects fall away so you fix the real leak rather than guessing.

An email list health score is a composite measure that combines engagement, list hygiene and deliverability signals into a single figure that reflects how healthy and deliverable an email list is. It rolls scattered signals like open rate, bounce rate, complaints and unengaged volume into one number you can track over time. A strong score means your mail reaches the inbox and earns action. A falling score warns of trouble before deliverability collapses.

Email revenue attribution is the practice of crediting revenue to email campaigns based on the role email played in the path to purchase. It tells you how much money your email programme actually generates, not just how many people opened or clicked. The number you get depends heavily on the attribution model you choose.

Email revenue per recipient is the average revenue a single email send earns, calculated by dividing the revenue attributed to a campaign by the number of recipients who received it. It tells you what each delivered email is worth, which makes campaigns comparable regardless of list size. A higher number means each contact you reach is generating more value.

Email ROI is the return earned for every pound invested in email marketing, calculated as the profit from email divided by the cost of running the programme. It tells you whether email pays for itself and by how much, expressed as a ratio or a percentage. A higher number means each pound spent on email is working harder.

Email template performance analysis is the practice of measuring how each reusable email template performs against engagement and conversion goals, then comparing templates to find which layouts, subject lines, copy and calls to action drive the best results. It turns a folder of templates into a ranked, evidence-based library. The goal is to retire weak templates, scale winners, and understand why one template outperforms another.

Email timing optimisation analysis is the practice of measuring how send time, day of week and frequency affect email engagement, then adjusting when emails go out to maximise opens, clicks and conversions. It separates the effect of when an email arrives from the effect of what it says. The goal is to deliver each message at the moment a recipient is most likely to act, rather than at a time that suits the sending team.

Email unsubscribe rate is the percentage of recipients who opt out of a mailing list after receiving a given email, calculated as unsubscribes divided by emails delivered. It measures how much of your audience a send drives away. A low and stable unsubscribe rate signals that your content matches what people expected when they joined, while a rising rate is an early warning that frequency, relevance or targeting has slipped.

Event-triggered flow performance measures how effectively an automated message flow turns a triggering event into the outcome it was built to drive. It captures the whole journey from trigger to conversion, not just whether a message was sent. It tells you whether your automations are earning their place or quietly leaking value.

Flow conversion rate is the percentage of users who enter a defined multi-step flow and complete it. It measures how well a sequence of steps, such as a signup, checkout, or onboarding flow, carries people from the first step to the goal. It is the headline number that every step-level drop-off rolls up into.

Flow efficiency is the percentage of a work item total time that is spent on active work rather than waiting. It exposes how much of a delivery process is genuine effort and how much is queues and handoffs. Most teams discover that work spends far more time waiting than being worked on, which is exactly what flow efficiency reveals.

Impression share lost to budget is the percentage of eligible ad impressions a campaign missed because its budget was exhausted. It tells you how much demand you could have captured but did not, purely because spend ran out before the auctions did. A high figure means real, ready buyers are seeing a competitor instead of you.

Keyword performance analysis is the practice of measuring how each target search keyword contributes to ranking, traffic, and downstream conversion. It moves beyond rank alone to judge a keyword on the qualified visitors and revenue it actually delivers. Done well, it tells you which keywords to invest in and which to drop.

Landing page performance analysis is the practice of measuring how effectively a single landing page turns visitors into a desired action, usually expressed as a conversion rate. It looks at the full path from arrival to completion, including bounce, engagement and form completion. The point is to find the specific reason a page wins or loses, not just to report the headline rate.

List performance analysis is the practice of measuring how well an email or marketing list converts contacts into engagement and revenue, from delivery through to clicks and purchases. It looks across deliverability, open and click behaviour, unsubscribe rates, and revenue per contact rather than judging a single send. The aim is to understand whether a list is growing in value or quietly decaying.

List quality score is a composite measure of how clean, deliverable, and engaged an email or marketing list is, expressed as a single index. It combines validity of the addresses, engagement of the contacts, and the rate at which people opt out or complain into one number. The score answers a simple question, which is whether the list is an asset worth investing in or a liability that drags down every campaign.

Marketing attribution analysis is the method of assigning credit for a conversion across the marketing touchpoints that led to it, so each channel can be judged on the revenue it actually influenced. It answers the question every marketing budget depends on: which channels are working and which are coasting on the work of others. The choice of attribution model decides how credit is split, and that choice changes which channels look profitable.

Message deliverability rate is the percentage of sent messages that successfully reach the intended recipient, rather than being bounced, blocked or filtered out. It measures whether your messages actually arrive, not just whether you sent them. The rate applies across email, SMS and push channels, and it is the foundation every downstream metric like opens and replies depends on.

Message frequency optimisation is the practice of finding the send cadence that produces the most engagement per recipient while keeping unsubscribes and complaints low. It treats how often you message as a tunable variable rather than a fixed habit. Tracked over time, it shows the point where one more send starts costing more in fatigue than it earns in response.

Message length distribution is the spread of how long messages are across a body of communication, grouped into bands such as short, medium, and long. It shows whether messages cluster tightly around one length or scatter widely. Tracked over time, the shape of the distribution reveals shifts in how a team or audience communicates that an average alone would hide.

Message response time by priority is the average time taken to reply to messages, broken down by how urgent each message is. It separates a fast reply to a routine note from a slow reply to a critical one, which a single overall average blends together. Tracked per priority tier, it shows whether the most urgent messages are actually being handled fastest.

Message sentiment analysis is the practice of classifying the emotional tone of customer messages as positive, neutral, or negative, then aggregating those classifications into a single score you can track over time. It turns unstructured text from support tickets, chats, reviews, and social posts into a number that reflects how customers feel. Tracked well, it gives you an early read on satisfaction long before it shows up in churn or revenue.

Message volume is the total number of inbound customer messages a team receives across its channels in a given period. It counts every email, chat, ticket, and social message that needs a response. Tracked over time, it tells you how much demand is hitting your support function and whether that demand is rising faster than your ability to handle it.

Negative keyword analysis is the process of finding search terms that trigger your paid ads but do not match buyer intent, then measuring the spend wasted on them. It turns a long, messy search-terms report into a single number you can act on: the share of budget spent on traffic that will never convert. Done regularly, it protects budget, lifts conversion rate, and sharpens who actually sees your ads.

Newsletter subscriber churn is the percentage of subscribers who leave your email list in a given period through unsubscribes, hard bounces, spam complaints, and removed unengaged addresses. It is the clearest signal of whether your list is a growing asset or a leaking one. Left unmeasured, churn quietly erodes reach, hurts deliverability, and makes acquisition look more effective than it really is.

Repeat purchase rate from email is the percentage of customers acquired or last touched through email who go on to make at least one additional purchase. It isolates the contribution of the email channel to repeat buying, separating it from paid, organic, and direct demand. It tells you whether email is building loyal customers or simply driving one-off transactions.

Revenue attribution by source is the practice of assigning closed revenue to the channels, campaigns, and touchpoints that influenced each deal. It tells you which sources produce paying customers rather than just clicks or leads. Done well, it turns a flat marketing budget into a ranked list of what to fund next.

Search query performance measures how well an individual search query drives visibility, clicks, and downstream conversions. It moves the analysis below page and campaign averages to the exact words people type. A single query can carry an entire landing page, or quietly bleed budget with high spend and no conversions.

Search term analysis is the practice of examining the actual terms people type into search to find which drive conversions, which waste spend, and which intents you are missing. It separates the keywords you bid on from the real terms that triggered them. The output is a prioritised list of terms to scale, refine, or exclude.

Sequence completion rate is the percentage of people who enter a multi-step sequence and reach the final step. It measures how well a designed series, such as an outreach cadence, an onboarding flow, or an automated email journey, carries people all the way through rather than losing them partway. A high rate means the steps connect smoothly. A low rate means people drop out before the sequence does its job.

Sequence performance analysis is the practice of measuring how an automated outreach sequence converts enrolled prospects into replies and meetings, step by step. It looks at open, reply, and conversion rates at each touch so you can see which message and which timing carries the result. The point is to find the one step that helps or hurts, not just the sequence average.

Traffic source analysis is the practice of grouping website or app visitors by the channel that brought them and measuring how each channel performs on volume, quality, and conversion. It answers not just how many people arrived but which sources sent the visitors who actually convert. Done well, it shows where to invest acquisition effort and where spend is buying traffic that never turns into outcomes.

Transactional message success rate is the percentage of transactional messages, such as receipts, password resets, and order confirmations, that are successfully delivered to the recipient out of all messages sent. Unlike marketing email, these messages are triggered by a user action and are expected, so a failure is a broken experience rather than a missed promotion. A reset email that never arrives can lock a customer out entirely.

Transcript keyword trending is the rate at which a specific word or phrase appears across spoken transcripts over a given period, expressed as mentions per period or as a change versus the previous period. It turns unstructured conversation data into a measurable signal. Teams use it to spot rising themes in sales calls, support tickets, and user interviews before they show up in revenue.