Lesson 1Monetary variables and value-based signals: order value, average order value, lifetime value, margin bucketsThis part explains monetary variables and value signals. You'll see 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 part details first- and third-party behaviour signals. You'll learn tracking product views, cart events, searches, time on page, and boosting them 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 part covers temporal and recency variables showing recent user interactions. You'll learn computing last visit, last purchase, days since actions, and using recency for segments and prediction 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 part details technical and contextual variables describing user environment. You'll learn how device, OS, browser, connection, location, 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 part looks at email and automation data. You'll learn how opens, clicks, bounces, unsubscribes are kept, how journeys are mapped, 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 part explores ad platform data from Google Ads, Meta Ads and more. You'll learn fields for campaigns, creatives, bids, audiences, conversions, and exporting/joining 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 part explores audience and interest data from analytics, ad platforms, APIs. You'll learn 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 part covers privacy and ID variables linking events to people. You'll learn user IDs, cookies, hashed emails, mobile ad IDs, consent flags, and designing 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 part covers engagement scores and cohort indicators summarising user behaviour. You'll learn designing scoring models, frequency buckets, churn risk tracking, 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 part details CRM and transaction data. You'll learn how profiles, orders, returns, lifetime value are structured, connecting 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 part focuses on web analytics, especially Google Analytics and GTM. You'll learn key metrics, event structures, traffic sources, designing tracking 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
