Lesson 1Monetary variables and value-based signals: order value, average order value, lifetime value, margin bucketsThis section explains monetary variables and value-based signals. You'll learn how to calculate order value, average order value, margin buckets, and revenue-based segments to guide bidding and customer strategies effectively.
Gross order value and net revenueAverage order value and basket metricsCustomer lifetime value model choicesMargin buckets and profitability tiersValue-based bidding and ROAS targetsLesson 2First- and third-party behavioral signals: product views, category visits, cart events, search queries, time on pageThis section details first- and third-party behavioural signals. You'll learn how to track product views, cart events, searches, and time on page, and enrich them with third-party intent and contextual data.
Product and category view event designCart additions, removals and checkout stepsOn-site search queries and filters usedTime on page, scroll depth and engagementThird-party intent and contextual signalsLesson 3Temporal and recency variables: last visit, last purchase, days since last open/click, session recencyThis section explains temporal and recency variables that capture recent user interactions. You'll learn to compute last visit, last purchase, days since actions, and use recency for segmentation and predictive models.
Timestamps and event time normalizationLast visit and last session calculationsLast purchase and order recency metricsDays since last open, click or loginRecency-based segmentation and RFM useLesson 4Technical and contextual variables: device type, OS, browser, screen size, connection type, geo (city/region), local timeThis section details technical and contextual variables describing the user’s environment. You'll learn how device, OS, browser, connection, location, and local time impact tracking quality, attribution, and campaign optimisation.
Device type and form factor taxonomiesOperating system and version detectionBrowser, user agent and feature supportScreen size, resolution and viewport groupsConnection type, IP-based geo and local timeLesson 5Email and marketing automation data: open rate, click-through, send history, engagement segments, unsubscribe eventsThis section examines email and marketing automation data. You'll learn how opens, clicks, bounces, and unsubscribes are stored, how journeys are modelled, and use engagement segments for targeting and testing.
Send, open, click and bounce eventsUnsubscribe, spam and preference dataJourney and workflow state trackingEngagement segments and lead stagesDeliverability and reputation indicatorsLesson 6Ad platform data: available fields in Google Ads and Meta Ads (keywords, creative, placements, bid, impressions, clicks, conversions)This section explores ad platform data from Google Ads, Meta Ads and others. You'll learn fields for campaigns, creatives, bids, audiences, conversions, and how to export and join with first-party data.
Campaign, ad set and ad level fieldsKeywords, audiences and placements dataCreative variants, formats and metadataBids, budgets and pacing indicatorsImpressions, clicks and conversion logsLesson 7Audience and interest data: inferred interests, affinity categories, custom audiences, lookalikes and API-derived signalsThis section explores audience and interest data from analytics, ad platforms, and APIs. You'll learn how inferred interests, affinity groups, custom audiences, and lookalikes are built and activated in campaigns.
Inferred interests from on-site behaviorAffinity and in-market category taxonomiesBuilding and refreshing custom audiencesLookalike modeling inputs and controlsAPI-derived intent and contextual signalsLesson 8Privacy and identifier variables: user IDs, cookie IDs, hashed emails, mobile ad IDs, consent flagsThis section covers privacy and identifier variables linking events to people. You'll learn about user IDs, cookies, hashed emails, mobile ad IDs, consent flags, and designing compliant identity strategies.
First-party user IDs and login identifiersCookie IDs and browser storage limitsHashed emails and identity resolutionMobile ad IDs and app tracking signalsConsent flags, TCF strings and policiesLesson 9Engagement scoring and cohort indicators: email engagement score, site engagement score, churn risk, frequency bucketsThis section covers engagement scores and cohort indicators summarising user behaviour. You'll learn to design scoring models, define frequency buckets, track churn risk, and build cohorts for lifecycle analysis.
Designing email engagement scoring modelsSite engagement scores from web behaviorFrequency buckets and intensity tiersChurn risk flags and propensity scoresCohort definitions and tracking windowsLesson 10CRM and transaction systems: user profiles, purchase history, lifetime value, order frequency, returnsThis section details CRM and transaction system data. You'll learn how profiles, orders, returns, and lifetime value are structured, and connect them to marketing platforms for targeting and measurement.
Customer master records and keysOrder, line item and invoice structuresReturns, cancellations and refunds dataLifetime value and tenure calculationsSyncing CRM data to marketing toolsLesson 11Web analytics data: Google Analytics/GTM variables (pageviews, events, sessions, traffic source, device, behavior flows)This section focuses on web analytics data, especially Google Analytics and GTM. You'll learn key metrics, event structures, traffic source fields, and design tracking plans supporting marketing and attribution.
Core pageview, session and user metricsEvent design, parameters and namingTraffic source and campaign UTM fieldsBehavior flows, funnels and pathing dataCustom dimensions and enhanced ecommerce
