Lesson 1Monetary variables and value-based signals: order value, average order value, lifetime value, margin bucketsThis section explains monetary variables and value signals, teaching how to calculate order value, average order value, margin buckets, and revenue segments to shape bidding and customer plans.
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 behaviour signals, covering tracking of product views, cart events, searches, time on page, and enhancing with third-party intent and context 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 covers time-based and recency variables tracking recent user actions, teaching calculations for last visit, last purchase, days since events, and using recency for segments and predictions.
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 explores technical and context variables describing user setup, showing how device, OS, browser, connection, location, and local time impact tracking, attribution, and campaign tweaks.
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 reviews email and automation data, covering storage of opens, clicks, bounces, unsubscribes, journey models, and using engagement segments for targeting and tests.
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 dives into ad platform data from Google Ads, Meta Ads and more, covering fields for campaigns, creatives, bids, audiences, conversions, and exporting to 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 looks at audience and interest data from analytics, ads, APIs, covering building inferred interests, affinity groups, custom audiences, lookalikes, and activating 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 handles privacy and ID variables linking events to users, covering user IDs, cookies, hashed emails, mobile ad IDs, consent flags, and compliant identity plans.
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 markers summarising behaviour, teaching scoring models, frequency buckets, churn risk tracking, and 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 data, showing structure of profiles, orders, returns, lifetime value, and linking 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, especially Google Analytics and GTM, covering key metrics, events, traffic sources, and tracking plans for 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
