Lesson 1Monetary variables and value-based signals: order value, average order value, lifetime value, margin bucketsDis section go explain monetary variables and value-based signals. You go learn how to compute order value, average order value, margin buckets, and revenue-based segments to guide bidding and customer strategies.
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 pageDis section dey detail first- and third-party behavioral signals. You go learn how to track product views, cart events, searches, and time on page, and how to enrich dem 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 recencyDis section go explain temporal and recency variables wey dey capture how recently users interact. You go learn to compute last visit, last purchase, and days since actions, and how to 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 timeDis section dey detail technical and contextual variables wey dey describe di user environment. You go learn how device, OS, browser, connection, location, and local time dey affect tracking quality, attribution, and campaign optimization.
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 eventsDis section dey examine email and marketing automation data. You go learn how opens, clicks, bounces, and unsubscribes dey stored, how journeys dey modeled, and how to 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)Dis section dey explore ad platform data from Google Ads, Meta Ads and others. You go learn about fields for campaigns, creatives, bids, audiences, and conversions, and how to export and join dem 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 signalsDis section dey explore audience and interest data from analytics, ad platforms, and APIs. You go learn how inferred interests, affinity groups, custom audiences, and lookalikes dey built and how to activate dem for 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 flagsDis section dey cover privacy and identifier variables wey dey link events to people. You go learn about user IDs, cookies, hashed emails, mobile ad IDs, and consent flags, and how to design 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 bucketsDis section dey cover engagement scores and cohort indicators wey dey summarize user behavior. You go learn how to design scoring models, define frequency buckets, track churn risk, and build cohorts for lifecycle and retention 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, returnsDis section dey detail CRM and transaction system data. You go learn how profiles, orders, returns, and lifetime value dey structured, and how to connect dese records 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)Dis section dey focus on web analytics data, especially Google Analytics and GTM. You go learn key metrics, event structures, traffic source fields, and how to design tracking plans wey support 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
