Attribution Modelling in Google Analytics and Beyond
- Length: 608 pages
- Edition: 2
- Language: English
- Publication Date: 2021-09-25
- ISBN-10: B09H5YMDYS
- ISBN-13: 9798477650996
- Sales Rank: #0 (See Top 100 Books)
“Attribution Modelling is the first wonder of the Marketing World. He who understands it, earns it; he who doesn’t, pays it.”
For many people, Attribution Modelling is still a mumbo jumbo. They may have heard about it somewhere. And they may have a vague idea of what it is but they don’t really know how to use and benefit from it.
And that is because attribution modelling is full of jargon.
We have got ‘last click conversions’, we have got ‘first click conversions’, ‘data-driven conversions’.
We have got ‘click-through conversions’, we have got ‘view-through conversions’.
Then we have got dozens of different attribution windows, conversion windows, attribution models.
And then under each attribution window, conversion window and attribution model, we can have a range of different conversion volume and conversion values.
Then we have got different types of cost per acquisitions (CPA) like Last Interaction CPA, Last non-direct click CPA, Linear CPA, Time Decay CPA…. and the list goes on and on.
And the biggest headache of all is to decide which attribution window, conversion window and/or attribution model to use for optimizing marketing campaigns and interpreting data.
All of this has made web analytics and optimization incredibly hard and complex.
However, you need to learn all of this attribution modelling jargon. And not just learn it but truly understand it, if you want to remain relevant in the current marketplace and in demand.
Attribution modelling is the process of understanding and assigning conversion credit to marketing channels.
The primary objective of attribution modelling is to understand the buying behaviour of your website visitors and to determine the most effective marketing channels for investment at a particular point in time.
A lot has been said about attribution modelling over the years. However, talking about attribution is the easy bit. Implementing it is the real challenge.
This book has been written to help you implement attribution modelling in your organisation.
This expert guide will help your organisation think about marketing holistically. It will teach you to leverage the knowledge of attribution modelling while allocating your marketing budget and helping you understand your users’ buying behaviour.
In this book, there is a strong focus on using Google Analytics and other Google tools and technologies, such as Google Ads.
Any person who wants to improve the online performance of their business and marketing campaigns should read this book. Online marketers, web analysts, and data scientists will benefit the most from this book.
I have explained various attribution models mainly in the context of Google Analytics. However, a large portion of this book does not deal with Google Analytics at all.
So even if you have never used Google Analytics before, you can still benefit from this book.
Title Copyright About the Author Introduction What is this book about? What is not included in this book? What do you need to know in advance to benefit from this book? Who should read this book? Table of Contents Chapter-1: Introduction to attribution modelling What is attribution modelling? What is the primary objective of attribution modelling? What are attribution issues? Who are the ideal candidates for attribution modelling? What is the difference between attribution modelling and marketing mix modelling? Different categories of attribution What is multi-channel attribution? What is multi-device attribution? What is online-offline attribution? What is hybrid attribution? Real-world attribution is hybrid attribution How to fix hybrid attribution issues Introduction to nonline marketing What are attribution models? Different types of attribution models in Google Analytics Eight different types of default attribution models What is the advantage of using attribution models? How does attribution work? What are direct and assisted marketing channels? The role of assisted marketing channels in a conversion path Chapter-2: Why Attribution Modelling is the Key to Online Business Success Chapter-3: Setting Realistic Expectations from Attribution Why should you worry about not understanding attribution modelling? Why should you worry about not explaining attribution modelling to your client/boss? Attribution modelling is not a panacea Attribution modelling is not a one-time activity Attribution modelling is not meant just for big companies with big budgets Focusing on a single marketing channel is not attribution There is a no good, bad, best or flawed attribution model Data integration is the key to fixing attribution issues Attribution is much more than Google Analytics Perfect attribution does not exist You do not need perfect data to do attribution modelling Attribution modelling can affect employees’ salaries and bonuses Attribution modelling can create resistance and conflicts within your organisation Involve only the right people for discussing attribution modelling results Conversion paths almost always contain missing touchpoints Attribution modelling is based on only 'known' touchpoints Attribution is recorded and reported only for online touchpoints Attribution is not always recorded and reported for all digital marketing channels Attribution is not always recorded and reported across devices and browsers Google Ads conversion paths do not usually include impression interactions Filtered views can omit certain touchpoints in conversion paths Data sampling issues can skew the conversion path data Not all touchpoints are equally valuable Chapter-4: The Dumbification of Analytics Tools and its Consequences Analytics tools and capabilities are being dumbified Attribution modelling capabilities are pretty much non-existent in GA4 Every couple of months or so, we lose some tracking tool or capability because of some new privacy update Conversion attribution is going to get worse Privacy profiteering and the fierce competition to capture market share Collecting accurate data will become progressively more expensive Chapter-5: Work Culture and Attribution Modelling A work culture that is not data-driven Lack of business agility A work culture that does not encourage innovation Presence of organisational silos and other operational inefficiencies Non-alignment of goals and KPIs across an organisation Lack of authority Lack of expertise Lack of tools, technology, and processes Data collection issues Data integration issues Chapter-6: Misinterpretation of Analytics Data and Reports Top reasons for the misinterpretation of analytics data and reports Trying to figure out everything on your own Not being in the loop Not maintaining a database of important changes Lack of context Not understanding the intent Not understanding statistical significance Not understanding the maths and stats Attribution bias Simpson’s paradox Causal reductionism (causal oversimplification) Dunning Kruger effect Streetlight effect Confirmation bias Selection bias Observational bias Cumulative error Relying on anecdotal evidence Not understanding the Pareto principle (80/20 rule) Woozle effect Correlation causation fallacy Chapter-7: Server-Side Tracking - The Future of Analytics What is client-side tracking? What is server-side tracking? Why should you switch to server-side tracking? How to set up server-side tracking How much does server-side tracking cost? Server-side tracking and GDPR Chapter-8: Shopping Carts and Attribution The ability to provide powerful ecommerce analytics The ability to integrate with accounting software The ability to integrate with POS (point of sales) systems The ability to integrate with Google Analytics and Google Tag Manager The ability to integrate with CRM solutions The ability to integrate with a phone call tracking solution Chapter-9: Customer Data Platforms Introduction to ETL The three ETL functions Extract functions can become progressively more difficult to execute and maintain Transform functions can become progressively more difficult to execute and maintain Load functions can become progressively more difficult to execute and maintain Your TMS configurations could collapse under their own weight What is a customer data platform? Introduction to Segment The downsides of using customer data platforms Chapter-10: Before You Start Attribution Develop that great understanding Create a wide separation between marketing activities Move beyond clickstream data Use the web analytics toolbox Use advanced in-page analytics tools Collect customers feedback data 24/7 Document negative online reviews about your business Use at least one Google Analytics alternative About Matomo Analytics About Oribi Analytics Switch to server-side tracking Make sure that you fix the most common data collection issues Understand the role of a shopping cart in fixing attribution issues Use Google BigQuery Move beyond traditional tag management solutions Use Zapier Chapter-11: Google Analytics Hits and Sessions What is a hit in Google Analytics? How does Google Analytics define sessions? When does a Google Analytics session start and end? How can a Google Analytics session last longer than 30 minutes? How do you change session timeout settings? How do you decide the length of a Google Analytics session for your website? Chapter-12: Client ID and User ID Introduction to client ID The key attributes of client ID How Google Analytics calculates new and returning users How Google Analytics calculates total users Introduction to user ID How to set up user IDs Key differences between client ID and user ID Chapter-13: Acquisition Channels Source (traffic source) Medium (traffic medium) System-defined medium User-defined medium The Source/Medium report Campaign (marketing campaign) Custom campaign Channel (marketing channel) Default marketing channels Custom marketing channels Organic search marketing channel (organic search traffic) Paid search marketing channel (paid search traffic) Display marketing channel (display traffic) Direct traffic channel (direct traffic) Referral channel (referral traffic) Social marketing channel (social media traffic) Email marketing channel (email traffic) (other) marketing channel (other advertising traffic) Channel labels Default channel labels Custom channel labels Chapter-14: Default Channel Grouping What is channel grouping? Types of channel grouping What is default channel grouping? Understanding default channel grouping rules Editing the default channel grouping How to redefine a default marketing channel Redefining the direct traffic marketing channel How to add a new marketing channel to the default channel grouping Avoid adding new marketing channels to the default channel grouping How to remove a marketing channel from the default channel grouping Chapter-15: Custom Channel Grouping What is custom channel grouping? Understanding custom channel grouping rules You can create custom channel groupings at view level and user level How to create a new custom channel grouping at view level How to create a new custom channel grouping at user level How to edit a custom channel grouping Promoting a custom channel grouping Advantages of using custom channel grouping Chapter-16: MCF Channel Grouping What is MCF channel grouping? Where to find MCF channel groupings in Google Analytics Types of MCF channel groupings Default MCF channel grouping Custom MCF channel grouping Using a template to create a new custom MCF channel grouping Creating a brand new custom MCF channel grouping from scratch via MCF report Chapter-17: Deep Dive into Direct Traffic What is direct traffic? 'Type-in' traffic Traffic from bookmarks Traffic from mobile apps Traffic from non-web documents Traffic from desktop email clients Traffic from instant messenger (IM) or online chat rooms Traffic from incorrectly tagged marketing campaigns Traffic from web browsers that do not send referrer data Traffic from redirected URLs that do not send referrer data Traffic from IOS 'open in...' Traffic from a link that uses the 'rel=noreferrer' attribute Traffic from a firewall that does not send referrer data Fake direct traffic from spambots HTTPS to HTTP redirect Direct traffic is actually a demand What is the difference between direct traffic and referral traffic? How does Google Analytics report on direct traffic? How Google Analytics attributes conversions to direct traffic Causes of a sudden spike in direct traffic in Google Analytics Chapter-18: Methods to Capture as Much Referrer Data as Possible Tag the URLs of all marketing campaigns Tag each marketing campaign correctly Use a direct payment gateway Make sure all pages of your website contain valid Google Analytics tracking code that fires on page load Keep browser referral issues, privacy settings, and add-ons in mind Migrate your website to HTTPS Block internal traffic Segment your direct traffic into two categories Look for correlations between your direct visits and marketing campaigns Use phone call tracking solutions Avoid using headless solutions Devise new ways to capture referrer data Chapter-19: Google Analytics Campaign Attribution The last non-direct traffic source does not exist The last non-direct traffic source exists The last non-direct traffic source changed for the user within six months The last non-direct traffic source does not change for the user for six months Each direct returning visit refreshes the timeout of the last non-direct traffic source Campaign timeout setting in Google Analytics How to change the campaign timeout setting How to decide the length of campaign timeout for your website Why you should not set a campaign timeout longer than three months Chapter-20: The Referral Exclusion List How does referral traffic affect the GA session count? What is a referral exclusion list? How to add a domain to the referral exclusion list Important points to remember about adding domains to the referral exclusion list The impact of the referral exclusion list on cross-subdomain traffic The impact of the referral exclusion list on cross-domain traffic Impact of the referral exclusion list on third-party domains Impact of the referral exclusion list on payment gateways Why do you sometimes see traffic from excluded domains? Chapter-21: Cross-Device Tracking By default, Google Analytics is not able to track users’ activities across devices Methods to set up cross-device tracking Setting up cross-device tracking via Google Signals Setting up cross-device tracking via user ID Setting up cross-device tracking via measurement protocol Using the Google Analytics 4 property to track cross-device conversions Cross-device tracking and user privacy Chapter-22: Google Signals Cross-Device Reports Google Signals cross-device reports in Google Analytics Device Overlap report Device Paths report Channels report Acquisition Device report Users are deduplicated across devices Important points about Google Signals cross-device reports Chapter-23: User ID Cross-Device Reports User ID cross-device reports in Google Analytics User ID Device Overlap report User ID Device Paths report User ID Acquisition Device report User ID Coverage report Key differences between user ID and Google Signals cross-device reports Chapter-24: Cross-Domain Tracking Cross-domain tracking in Google Analytics Cross-domain tracking set up can get very technical Chapter-25: Introduction to Roll-up Tracking What is roll-up tracking? What is the difference between cross-domain tracking and roll-up tracking? What is the difference between cross-device tracking and roll-up tracking? When should you set up roll-up tracking? Methods to set up roll-up tracking Chapter-26: Roll-Up Tracking Via Google Analytics Standard Structure of a Google Analytics account Roll-up accounts and roll-up properties Roll-up views and roll-up reports Planning the roll-up property setup Introduction to standard and premium roll-up tracking Introduction to source domains Standard roll-up views and properties How to implement standard roll-up tracking Drawbacks of standard roll-up tracking Chapter-27: Roll-Up Tracking Via Google Analytics 360 Managing roll-up properties Advantages of premium roll-up tracking Drawbacks of premium roll-up tracking Users and session handling in premium roll-up reporting Dimension mapping Metric mapping Cross-domain and cross-device tracking on top of roll-up tracking Chapter-28: Roll-Up Tracking via BigQuery, Google Sheets and GA4 Roll-up tracking via Google BigQuery Roll-up tracking via Google Sheets Roll-up tracking via Google Analytics 4 (GA4) Chapter-29: Google Analytics 4 (GA4) What is Google Analytics 4? Introduction to GA4 properties Introduction to GA4 reporting views Introduction to data streams The ‘event and parameter’ measurement model Advantages of using a GA4 property Drawbacks of using Google Analytics 4 Chapter-30: Online-Offline Conversion Tracking Online and offline conversions and campaigns What is online-offline conversion tracking? Online to offline attribution issues and how to fix them Offline to online attribution issues and how to fix them Chapter-31: In-Store Data Tracking Introduction to in-store data tracking Tracking in-store data via a POS system How to send offline sales data from POS software to a Google Analytics property How to integrate shopping cart data with accounting software Tracking in-store data through coupons Tracking in-store data via loyalty programs Online loyalty programs Offline loyalty programs Chapter-32: Store Visit Conversion Tracking How Google defines a store What are store visits in the context of Google Analytics? Google Analytics store visits reports Important points about Google Analytics store visit conversion tracking Shop visit conversion tracking in Google Ads Important points about Google Ads shop visit conversion tracking Eligibility criteria for store visit conversion reporting The major drawback of store visit conversion tracking in Google Analytics and Google Ads Store visit conversion tracking in Facebook Chapter-33: Phone Call Tracking A phone call is a marketing channel A phone call is a touchpoint Phone call experience optimisation Every phone call is live customer feedback Introduction to phone call tracking Phone call tracking solutions from Google Commercial phone call tracking solutions How to choose a commercial phone call tracking solution In-house phone call tracking solutions Jargon used in phone call tracking How does phone call tracking work? Tracking phone leads from billboard ads Tracking phone leads from print ads Tracking phone leads from transit media ads Tracking phone leads from radio and TV ads Phone call tracking and privacy regulations Chapter-34: TV Attribution Introduction to TV attribution solutions Benefits of using a TV attribution solution Other ways to measure the impact of TV ads Using coupons to track online sales generated from TV ads Using vanity URLs for tracking online traffic and sales from TV ads Manually correlating online customers’ activities with TV ad airings Chapter-35: Conversions in Multi-Channel Funnels Introduction to conversions What are ecommerce conversions and goal conversions? What are macro and micro conversions? What is conversion volume? What is conversion value? Introduction to multi-channel funnel reports Types of multi-channel funnel reports Data discrepancies between MCF and non-MCF reports What are conversions in GA multi-channel funnels? Understanding path length Long and short conversion paths, and what do they mean for your brand? What is a lookback window? Default lookback window Custom lookback window Important points about lookback windows Conversion values in multi-channel funnel reports Chapter-36: Deep Dive into Interactions (Touchpoints) Introduction to interactions (touchpoints) Different types of interactions in Google Analytics Interactions based on position Interactions based on an online user’s type of activity Interactions based on campaign or traffic source type Interactions based on online/offline activities How Google Analytics displays touchpoints on a conversion path Important points about interactions and conversion paths Types of interaction analysis Chapter-37: Assisting Interactions Analysis What is assisting interactions analysis? What are assisted conversions? What is assisted conversion value? What are last click or direct conversions? What is last click or direct conversions value? Assisted/last click or direct conversions Chapter-38: First Interaction Analysis What is first interaction analysis? What are first click conversions? First click conversion value The ratio of first and direct conversions Chapter-39: Attribution Model and Window Specific Conversions Types of conversions based on the attribution model being used How to find attribution model specific conversions in Google Analytics Types of conversion values based on the attribution model being used How to find attribution model specific conversions values in Google Analytics Types of conversions based on the attribution window being used Types of conversion values based on the attribution window being used Chapter-40: Attribution Model and Window Specific CPA Types of CPAs based on the attribution model being used Prerequisites for calculating CPA in Google Analytics How Google Analytics calculates attribution model specific CPAs How to find attribution model specific CPAs in Google Analytics Types of CPAs based on the attribution window being used Chapter-41: Attribution Model and Window Specific ROAS Types of ROAS based on the attribution model being used Prerequisites for calculating ROAS in Google Analytics How Google Analytics calculates attribution model specific ROAS How to find attribution model specific ROAS in Google Analytics The Cost Analysis report The ROI Analysis report The Model Comparison Tool report Types of ROAS based on the attribution window being used Chapter-42: View-Through Conversions What are view-through conversions? Why are view-through conversions important? When are view-through conversions recorded and reported? Important points about view-through conversions What is GDN impression reporting? How to use GDN impression reporting Benefits of GDN impression reporting Chapter-43: Acquisition and Google Ads Conversion Paths What is an acquisition conversion path? Campaign (or source/medium) path Campaign path Default channel grouping path Keyword (or source/medium) path Keyword path Landing page URL path MCF channel grouping path Medium path Source path Source/medium path Google Ads conversion paths How to access different conversion paths Chapter-44: Conversion Segments What are conversion segments? How to use a conversion segment What are default conversion segments? All conversions Time lag > 1 day Path lag > 1 Any interaction is referral First interaction is paid advertising Last interaction is paid advertising First interaction is direct Last interaction is direct First interaction is organic search Last interaction is organic search Comparing conversion segments to each other What are user-defined conversion segments? How to create a new conversion segment Chapter-45: Classification of Attribution Models Rule-based attribution models Algorithmic attribution models Single-touch attribution models Multi-touch attribution models Vendor-specific attribution models Default attribution models Custom attribution models How to access attribution models in Google Analytics Chapter-46: Last-Interaction Attribution Model Chapter-47: First-Interaction Attribution Model Chapter-48: Linear Attribution Model Chapter-49: Position-Based Attribution Model Chapter-50: Last Non-Direct Click Attribution Model Chapter-51: Last Google Ads Click Attribution Model Chapter-52: Time-Decay Attribution Model Chapter-53: MCF Data-Driven Attribution Model What is the MCF data-driven attribution model? How does the DDA model assign conversion credit to touchpoints? Important points about the DDA model Advantages of using the DDA model Introduction to lift analysis General criteria for carrying out data-driven attribution The minimum conversion threshold for setting up the MCF DDA model The minimum conversion threshold to continue using the MCF DDA model The minimum conversion threshold for setting up the DDA model for each conversion type MCF DDA model eligibility criteria checklist Tasks to complete before you enable the MCF data-driven model How to enable the MCF DDA model in Google Analytics Chapter-54: Model Explorer What is the Model Explorer? Eligibility criteria for using the Model Explorer How to access the Model Explorer report How to read the Model Explorer report What is weighted average conversion credit? What exactly is weight? Colour coding used in the Model Explorer report How to determine the overall weight of marketing channels under data-driven attribution Downloading the MCF DDA model Chapter-55: Model Comparison Tool What is the Model Comparison Tool? Eligibility criteria for using the Model Comparison Tool How to access the Model Comparison Tool Conversions and CPA Conversion value and ROAS Conversions and value Percentage change Comparison and reference attribution models Case study - How organic search can be valued from a different perspective Case study - How organic search can be valued from a different perspective via the DDA model Chapter-56: Custom Attribution Models What is a custom attribution model, and why do you need one? Requirements for creating a custom attribution model How to create a custom attribution model Quick recap of conversion credit and weighting What are conversion credit weighting rules? Default conversion credit weighting rules Important points about the default credit rules Custom conversion credit weighting rules How to create a custom credit rule Overlapping conversion credit weighting rules Adjusting credit for impressions Adjusting credit based on user engagement Sharing a custom attribution model Chapter-57: Attribution BETA Introduction to attribution projects Prerequisites for creating an attribution project How to get the best results from your attribution project Conversions in attribution projects Lookback windows in attribution projects Creating a new attribution project Before you start analysing reports in your attribution project Attribution project reports and settings Conversion Paths report Conversion Lag Report Conversion Path Length report Model Comparison report Google Ads Performance report Major differences between attribution project reports and multi-channel funnel reports Chapter-58: GA4 Attribution Introduction to GA4 attribution Introduction to GA4 attribution models Types of GA4 attribution models Cross-channel last-click attribution model Cross-channel first-click attribution model Cross-channel linear attribution model Cross-channel position-based attribution model Time-decay attribution model in GA4 Ads-preferred rules-based attribution model GA4 reporting attribution model Lookback window in GA4 Advertising Snapshot in GA4 Model Comparison report in GA4 Conversion Paths report in GA4
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