Lesson 1Monetary variables and value-based signals: order value, average order value, lifetime value, margin bucketsThis part explains money details and value signs. You learn to calculate order value, average order value, profit groups, and sales-based groups to guide bids 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 own and outside behavior signs. You learn tracking product looks, cart actions, searches, time on page, and adding outside 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 explains time and freshness details showing recent user actions. You learn last visit, last buy, days since actions, and using freshness for grouping 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 tech and context details about user setup. You learn how device, system, browser, connection, place, and local time affect tracking, crediting, and campaign fixes.
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 auto-marketing data. You learn how opens, clicks, fails, and cancels are kept, how paths are made, and using engagement groups 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 checks ad platform data from Google Ads, Meta Ads and more. You learn fields for campaigns, ads, bids, groups, and buys, and how to pull and join with own 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 checks group and interest data from analytics, ad platforms, APIs. You learn how guessed interests, like-groups, custom groups, lookalikes are made and used 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 details linking actions to people. You learn user IDs, cookies, hashed emails, mobile ad IDs, consent marks, and planning right ID ways.
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 group signs summing user actions. You learn scoring models, frequency groups, churn danger, and groups for life cycle and keeping 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 buy system data. You learn how profiles, orders, returns, lifetime value are set, and linking to marketing platforms for targeting and checking.
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 data, like Google Analytics and GTM. You learn key measures, event setups, traffic source fields, and planning tracking for marketing and crediting.
Core pageview, session and user metricsEvent design, parameters and namingTraffic source and campaign UTM fieldsBehavior flows, funnels and pathing dataCustom dimensions and enhanced ecommerce
