Guides

Every guide, grouped by topic. Measurement guides show how a real product answers a question; best-practice guides give a rule that holds on any stack.

Acquisition and traffic quality 7

Guide How this LookML project separates new and returning visitors Are visitors coming back? How a real product splits new and returning visitors, why its visitor share counts sessions, and what cookies hide. RetentionAcquisition Guide Using user agents to flag non-browser ad impressions How a real ad-tech model flags impressions from clients that are not ordinary browsers, which publishers send them, and where its user-agent rule misleads. Acquisition Guide How this LookML project measures acquisition quality Which channels bring visitors who engage? How a real product compares bounce rate and events per session by channel and landing page, with the SQL. Acquisition Guide Using IP clusters to investigate suspicious ad traffic How a real ad-tech model groups IPs by how widely they spread across geos, publishers and user agents, and why its cluster labels never reach the traffic. Acquisition Guide Filters that quietly change what a metric means Why two reports disagree on one metric: hidden default filters, tile filters and unwired dashboard filters, with a checklist and real examples. Best practicesAcquisitionRetention Guide Calculating CTR from separate impression and click tables When clicks and impressions live in separate tables, a rate needs one population and one grain. How to check, with real tables that share neither. Best practicesAcquisition Guide Why parsing ids out of strings at query time is risky An id parsed from a string at query time turns malformed values into fake ids. A real publisher id parsed from a subid, and SQL that returns NULL instead. Best practicesAcquisition

Revenue 5

Guide Avoiding revenue fanout when joining orders to order items Where order revenue lives, why joining orders to items can double-count it, and how a real ecommerce model sums totals, items and average order value. Revenue Guide Modeling upgrades, downgrades and renewals as daily movements How a real subscription product stacks leads, upgrades, downgrades and renewals per day, how it defines active, and the fanout hidden in its downgrades. RetentionRevenue Guide Checking whether a few publishers earn most of the revenue How a real ad-tech model ranks publishers by bid revenue, why a ranking is not a concentration measure, and what its parsed publisher id hides. Revenue Guide Preventing join fanout by declaring every relationship Why sums and counts grow after a join, how to check any model for fanout, and the SQL and LookML that keep totals honest, from real join mistakes. Best practicesRevenue Guide Checking the primary key before you trust a count A count is only as clear as the key behind it. How to state and test a table's grain, with real tables whose keys repeat, merge rows or are missing. Best practicesRevenueRetention

Retention and engagement 5

Guide How this LookML project separates new and returning visitors Are visitors coming back? How a real product splits new and returning visitors, why its visitor share counts sessions, and what cookies hide. RetentionAcquisition Guide Modeling upgrades, downgrades and renewals as daily movements How a real subscription product stacks leads, upgrades, downgrades and renewals per day, how it defines active, and the fanout hidden in its downgrades. RetentionRevenue Guide Measuring reply rates on proposals and messages How a real social product counts responses to proposals and messages, why its response counts are averages, and how to define a reply rate that adds up. Retention Guide Filters that quietly change what a metric means Why two reports disagree on one metric: hidden default filters, tile filters and unwired dashboard filters, with a checklist and real examples. Best practicesAcquisitionRetention Guide Checking the primary key before you trust a count A count is only as clear as the key behind it. How to state and test a table's grain, with real tables whose keys repeat, merge rows or are missing. Best practicesRevenueRetention

Metric best practices 6

Guide Preventing join fanout by declaring every relationship Why sums and counts grow after a join, how to check any model for fanout, and the SQL and LookML that keep totals honest, from real join mistakes. Best practicesRevenue Guide Filters that quietly change what a metric means Why two reports disagree on one metric: hidden default filters, tile filters and unwired dashboard filters, with a checklist and real examples. Best practicesAcquisitionRetention Guide Calculating CTR from separate impression and click tables When clicks and impressions live in separate tables, a rate needs one population and one grain. How to check, with real tables that share neither. Best practicesAcquisition Guide Checking the primary key before you trust a count A count is only as clear as the key behind it. How to state and test a table's grain, with real tables whose keys repeat, merge rows or are missing. Best practicesRevenueRetention Guide Why parsing ids out of strings at query time is risky An id parsed from a string at query time turns malformed values into fake ids. A real publisher id parsed from a subid, and SQL that returns NULL instead. Best practicesAcquisition Guide Catching missing tables and stale references before a dashboard breaks Models can name tables, fields and explores that do not exist, and nothing fails until a chart runs. Real examples, and how to check yours before release. Best practices