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Google Analytics Powerups and Smartcuts

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Google Analytics Powerups and Smartcuts

  1. 1. Google Analytics: Powerups and Smartcuts @OptimiseOrDie @CharlesMeaden
  2. 2. Fix or Do These Things and Get Much Smarter @OptimiseOrDie @CharlesMeaden
  3. 3. © Optimal Visit 2d018© Optimise Or Die & Digital Nation Ltd. INTRODUCTION GET IN TOUCH!1. Charles Meaden @CharlesMeaden bit.ly/2HeHAt6 Craig Sullivan @OptimiseOrDie linkd.in/pvrg14
  4. 4. WHY US THEN? • 40 years working with Analytics • Nearly 500 Analytics setups • Most of them totally broken • Mistakes are good! • Failure is a part of analytics work • Our pain is your gain @OptimiseOrDie @CharlesMeaden
  5. 5. ABOUT THIS TALK: • Solid, hard won advice • Actionable insights • Google Analytics tips • Models, Templates, Reports • Articles & further reading @OptimiseOrDie @CharlesMeaden
  6. 6. CASES ARE REAL: • We care about handling client data • We can’t always show real data • We will show you models or concepts @OptimiseOrDie @CharlesMeaden
  7. 7. Powerups & Smartcuts 1. Inheritance Tax 2. Site Audits 3. Walkthroughs 4. Early Warning Hacks 5. Data Skew 6. Data Pollution 7. Data Enrichment 8. Data Models 9. Data Automation 10. Data Ownership 11. Training & Investment
  8. 8. (1 - INHERITANCE TAX
  9. 9. 10 When Taking Over An Account Get the History!
  10. 10. @OptimiseOrDie Analytics History  You might be lucky – the analytics configuration might have notes!  Always check the notes, talk to the team and discover the history  Have tags been changed in the last 2 years?  Has anyone updated the analytics?  Who made the changes?  What were the changes?  Are there any plans to make more changes?  Do any of these changes impact time periods used for analysis?  Have you talked to the analytics owner and developers?  Who owns the delivery and prioritisation of these changes?
  11. 11. 2 – ANALYTICS AUDITING
  12. 12. “Out of the entire lifecycle of analytics measurement, there is only one place guaranteed to pollute everywhere else and that’s the data collection layer.” Simo Ahava
  13. 13. “Bullshit data flows like raw sewage up and through every layer of an organisation, poisoning everyone with bad decision making.” @OptimiseOrDie
  14. 14. @OptimiseOrDie Bulls**t flows upwards! Pastel Coloured Total Bullshit Google Studio Dashboard BS metrics BS Collection BS metrics BS Collection BS metrics BS Collection BS metrics BS Collection BS reports BS Reports
  15. 15. 16 What’s the problem? Data Collection is Broken for Most Companies Thanks to @Simoahava
  16. 16. 480 client configurations 95% had high priority issues 100% had medium priority 3/480 had no tracking issues <1% had solid analytics Analysis of Site Audits @OptimiseOrDie
  17. 17. @OptimiseOrDie Even FREE tools are not FREE of effort: • FREE simply means that you get a basic system • It does not mean that it RUNS for free • A car needs correct setup, oil, fuel and maintenance • It doesn’t run on air and neither does analytics • Investment in analytics is #1 weakness in my clients • How can you race with others, if your dash is broken? • How can measure self performance if it’s flawed? • How can your team do their jobs, if they can’t measure too?
  18. 18. @OptimiseOrDie Why is Google Analytics free?Wiring Analytics to Idiosyncratic Business Signals:
  19. 19. @OptimiseOrDie Analytics Audit Resources @OptimiseOrDie THE GOOGLE ANALYTICS AUDIT CHECKLIST FROM DISTILLED: Genuinely good and comprehensive list, resources, source articles, checklist: https://www.distilled.net/resources/google-analytics-audit-checklist/ https://docs.google.com/spreadsheets/d/1GnwB-jYnNJu18NwuZJzgarZAotXQ0kxXbZAIhI4H0IE/edit#gid=0 ANNIELYTICS CHECKLIST ($295) https://www.annielytics.com/resources/annielytics-site-audit-checklist/ GOOGLE ANALYTICS HEALTH CHECK FROM CONVERSIONXL: Some excellent stuff not included in any other articles - a good roundup, sources, expert checklists: https://conversionxl.com/google-analytics-health-check HOW TO SELF AUDIT YOUR GOOGLE ANALYTICS A roundup of some useful things to audit but not a comprehensive checklist: https://boazsasson.com/tracking-reporting/how-to-self-audit-your-google-analytics/ 10 POINT CHECKLIST FOR A PERFECT GA SETUP: Some good information mixed with some less helpful stuff: http://supermetrics.com/blog/10-things-to-check-in-google-analytics-account/ GA CHECKLIST ON GOOGLE SHEETS: https://docs.google.com/spreadsheets/d/1pU9MpjjzxI-LLu45gPyGiHEpr_v-2rVpYuyNlPTXZ-I/edit#gid=0 GOOGLE ANALYTICS HEALTH CHECK: Solid checklist and additional articles - although probably needs expanding to include the best of the rest here: http://online-metrics.com/wp-content/uploads/2016/10/Google-Analytics-Health-Check.pdf TWO BASIC CHECKLISTS: https://www.dropbox.com/s/1f4w1vhpmzu938x/GoogleAnalyticsChecklist.pdf?dl=0 http://media.perpettersson.me/2017/02/GoogleAnalyticsImplementationChecklist.pdf
  20. 20. @OptimiseOrDie Automating Audits at scale: • Event Taxonomies • Page Fragmentation (parameters) • PII compliance • Campaign Tracking • Channel Configuration • Custom Dimensions • Page Crawling (tag checks) • Abnormal bounce rates • Goal & Filter checks (Management API) • Bulk configuration updates
  21. 21. @OptimiseOrDie Audit Summary • Everyone has problems now AND you’ll surely add more later • Audit regularly to avoid the flow of BS • Screw up Collection – there’s no Free Time Machine • Auditing requires more than just tech knowledge • + Lenses of User Experience, Business Goals, Platform & Tech Capability • Auditing is the easy bit – it’s what you do after that counts
  22. 22. @OptimiseOrDie TIP – Push through the PAIN of Post Audit: • We have 161 standard slides for our audits that we customise • Scored by Impact, Ease of fix, Business outcomes • We show clients how each thing shafts their data • CRITICAL, HIGH, MEDIUM & LOW classifications • Then the REAL work starts • Takes MONTHS or YEARS to fix everything
  23. 23. @OptimiseOrDie TIP – Push through the PAIN of Post Audit: • So what stuff do we get done first, that helps the company most? • Prioritisation for analytics stories! • Get resource & planning mobilised, signed in blood • Build a relationship with tech/dev • Agree a release (testing) process with dev • Parcel out prioritised work in ‘bite sized pieces’ • Celebrate every small achievement • Psychology of managing the post audit period is critical!
  24. 24. 3 – SITE WALKTHROUGHS
  25. 25. “Walkthroughs are where we tear down the frontend experience and GA configuration, to understand the flow of data. The Holy Trinity for us is Customer, Collection & Configuration - what does the customer see in the browser, what tags fire when and why, how does that data flow into GA. This is all.” @OptimiseOrDie
  26. 26. @OptimiseOrDie Data Collection & Tagging Tools WASP Inspector: • Use for general purpose GA tag inspection & debugging • Find out what scripts are running in which order • Great for core GA stuff http://bit.ly/2qrYbRE bit.ly/2qrYbRE
  27. 27. @OptimiseOrDie Audit Walkthrough Tools GTM/GA Debug • Debugging datalayer and GA • Simo’s fave extension bit.ly/2KtuYzm Data Slayer: • Handy for debugging GA and event issues • Find out what stuff is firing on the page bit.ly/2pbNmPN Data Layer Inspector: • Inspect GA and GTM activity • Hack and test data layer bit.ly/2p0r5IN Event Tracking Tracker: • Dump of event data in table • Handy for debugging GA and event issues bit.ly/2pHAlRg
  28. 28. @OptimiseOrDie What do we walk on the site? Everything! Key interaction patterns:  Searching, Category and List Pages  Filters, Sort Controls  Product Page elements  Guest checkout  Key landing pages & Journeys  Registered checkout  Logged in checkout  Logged out and then logged in checkout  Basket handling  Content pages  Quick view  Basket page  Checkout steps  Failure and error states  Email handling, more, more, more....
  29. 29. @OptimiseOrDie Walkthrough: Inspection Parameters 1. What URL shows in the address bar when we do stuff? 2. What tags & data (pageviews, events, data layer) fire when we use the product? 3. Are there any timing delayed tags? Interaction tags? Scroll tags? 4. What parameters or options are firing with the tags? 5. Which GA properties are the tags sending data to? 6. Are there page templates which are similar or identical in the tagging setup? 7. Are pages consistent within one style of template? 8. Are event tags set to interactive or non-interactive? 9. What data is sent in any event tags? What’s the taxonomy? 10. What page and interaction data is actally being pushed to Google Analytics?
  30. 30. @OptimiseOrDie Here’s one I made earlier… AMAZING! I KNOW HOW THE SITE & DATA WORKS!  Category Page /category/xxxx or /cat/xxxx  Search /search?q=xxxx  Product /product/xxxx  Basket add /addtobasket  Login /loginregister  Guest flow /guestcheckout/address (then steps are the same)  Registered flow /address (first time only)  Delivery /deliveryoption  Payment /paymentmethod  Confirm /confirmorder  Payment /payment  Success /ordersuccess/xxxx
  31. 31. @OptimiseOrDie The Holy Trinity of Walkthroughs CUSTOMER Intersection of Product and Data CONFIG Filters and Configuration inside GA setup COLLECTION Tagging, Data Layer, Data Flow to GA
  32. 32. @OptimiseOrDie Tip! User Explorer • Run a walkthrough session • Add a fake parameter (?piggle=diggle) or record the GA user ID • Filter using a segment to catch it • Check it’s your session, review • Check the GA data lines up with your journey steps!
  33. 33. 4 – EARLY WARNING HACKS
  34. 34. Setup Your Own ‘Menwith Hills’
  35. 35. Spotting The Algorithmic Bot • Someone in IT deployed a bot that created random user journeys to ‘really test the system’ • Accounted for 30% of all sessions • What can you put into place to stop this?
  36. 36. 4 Ways to Set Up your Early Warnings • Use Google Analytics Custom Alerts • Automate using the API • Off the shelf tools such as Analytics Edge or Super Metrics • Dashboards in Google Data Studio
  37. 37. Early Warning Ideas • Capture Page Load time for every page using Simo Ahava’s Google Tag Manager trick • Adapt Craig’s 15 Minute Model to extract data and compare against a running average
  38. 38. 55+ Google Analytics Custom Alerts 6 Essential Google Analytics Alerts for SEO Specialists & Web Agencies Google Analytics Spreadsheet Add-on Building visual reporting in Google Sheets @OptimiseOrDie @CharlesMeaden Tips and Resources
  39. 39. 5 – DATA SKEW
  40. 40. • Where your data in Google Analytics correct, but needs to cleaned and untangled, before you perform any analysis • Time taken to clean the data means less time for analysis! • People start to lose trust in the data if you don’t fix this… @OptimiseOrDie @CharlesMeaden What is Skewed data then?
  41. 41. @OptimiseOrDie
  42. 42. • When a user hops between subdomains in their user journey such as blog.test.com and checkout.test.com • You’ve got 2 or 3 separate sessions to try and stitch together • Google Tag Manager makes it way easier than configuring GA! @OptimiseOrDie @CharlesMeaden Subdomain / Cross domain tracking not setup
  43. 43. • Will appear as the top referring site for your all conversions and destroys your campaign tracking • Often appears when finance / IT add in a new payment gateway or tool without informing you • The Referral Exclusion list allows you to also add items such as dev servers and other ‘breakers’ @OptimiseOrDie @CharlesMeaden Payment Gateways and 3rd Party Redirects
  44. 44. • Misspelling and upper and lower cases cause havoc • Same issues can cause duplicates with page names • Google Analytics filters will save hours of needless pain • Fining your agency also really focuses minds @OptimiseOrDie @CharlesMeaden Misconfigured Campaign Tracking
  45. 45. • Most clients don’t have this working right • Changes to the website and campaigns are not reflected, stuff goes in the wrong bucket • Channels and Content Groups can be customised to your organisational way of working • People looking at reports simply don’t realise that their channel or content groupings are skewed • Sit down and bucket your Source/Medium distribution with the client –put everything in the right channel (ask us how) @OptimiseOrDie @CharlesMeaden Misconfigured Channels and Content Groups
  46. 46. • Some are incredibly useful, others fragment page data but aren’t actually used for anything! • This regex ?|& will show you all the URL’s in the All Pages that contain a query string • Don’t remove all the query strings in one go – check stuff that is needed! • Do use the Exclude URL Query Parameters and individual filters for specific query string @OptimiseOrDie @CharlesMeaden Query Strings
  47. 47. ‘With ITP 2.1, all persistent client-side cookies, i.e. persistent cookies created through document.cookie, are capped to a seven day expiry’ – Webkit • Affects EVERYONE using iPhones, iPads (also laptop Safari) • EVERY tool you use that tries to look longer than 7 days? • All the ‘Existing Visitors’ will look like ‘New Visitors’! • It’s going to skew tools, AB testing, attribution – lots of stuff • Ask your vendors for their response! @OptimiseOrDie @CharlesMeaden ITP 2 and Safari
  48. 48. Simo Ahava ITP 2.1 and Web Analytics Use Localstorage for Client ID Persistence Maciej Zawadziński Complete guide to ITP versions 1.0-2.2 Built Visible What Intelligent Tracking Prevention (ITP) 2.1 means for digital analytics Metric Theory How to Use Google Analytics to Estimate the Impact of ITP 2.1 Digiday WTF is Apple’s ITP 2.2 update? @OptimiseOrDie @CharlesMeaden Only the Best ITP Resources for you! Cory Underwood A Safari Intelligent Tracking Prevention Risk Analysis Google’s Plan for Privacy Mike King Your Analytics Data Isn’t Real and it’s getting worse
  49. 49. • Basic Google Analytics Filters For Every Site • Regexr Regular Expression Builder • Ultimate Guide to Using Google Analytics Filters • The Definitive Guide To Campaign Tagging in Google Analytics • Google Analytics channels: Let's make them great again • The Definitive Guide to Channels in Google Analytics • Why you want to customise Google Analytics Channels @OptimiseOrDie @CharlesMeaden Data Skew – Tips & Resources
  50. 50. 6 – DATA POLLUTION
  51. 51. • Data contains extra shizzle that shouldn’t be there • Either a 3rd party is doing this (bot/spam) • Or you are doing it, (by not filtering stuff) @OptimiseOrDie @CharlesMeaden What is data pollution (vs. skew)? • Invisible unless you check • Corrupts key site metrics (e.g. CR, Bounce Rate) • “Help – our conversion rate is dropping!”
  52. 52. Our Conversion Rate is Dropping: Prospects Customer Logins Internal Logins Dev & Staging Philippines Data Pollution Example Automated @OptimiseOrDie @CharlesMeaden
  53. 53. Prospects Customers (trial & paid) Internal & Partner Dev & Staging This is how it REALLY should look: Data Pollution Example Bot, Spam, Automated @OptimiseOrDie @CharlesMeaden Philippines
  54. 54. • Not filtering internal traffic (dev, staging, testing, agencies, partners, employees, contractors) • Bots, Spam (automated) • External Site Performance Monitoring • Internal Site Monitoring • Scraping or Auditing • Misconfigured tags • Double firing tags @OptimiseOrDie @CharlesMeaden Common Data Pollution Sources:
  55. 55. @OptimiseOrDie Tip! - Top Bot Detective Resources Best Strategies for Dealing with Bot Traffic in GA How to Block Spam & Bots from GA Detecting Headerless Bot Traffic in GA 30+ Custom View Filters for GA Is bot traffic costing you affiliate fees? Some additional techniques for spam
  56. 56. @OptimiseOrDie Tip! User Explorer • Check the Session Distribution Report • Set up an advanced segment • Do you have users with lots of sessions? • Filter to sessions > 200 (tweak accordingly) • Examine the high repeat session users • Is there anything odd about this traffic? • Get useful clues from network, hostname, bounce, browser, geo-IP, screen resolution • Identify, Filter, Fix
  57. 57. 7 – DATA ENRICHMENT
  58. 58. 59 Plug and Play Analytics? Data quality isn’t acquired – it’s earned! Thanks to @Simoahava
  59. 59. • You will always need to tune Google Analytics to fit how your business, product or service actually works • Customising, tweaking and enhancing the vanilla Google Analytics configuration = enriched data • What can you do to capture more of the important interactions and events as part of the user journey @OptimiseOrDie @CharlesMeaden Google Analytics – One Size Fits All
  60. 60. 1. Visit Query Explorer and authenticate your Google Analytics view 2. Get the total for your busiest month • Subtract that from 10,000,000 • Divide the figure by the number of sessions for that month 3. That’s how many additional events you can fire into Google Analytics per session @OptimiseOrDie @CharlesMeaden Ten Million Hits A Month To Use
  61. 61. @OptimiseOrDie @CharlesMeaden Analytics Data Enrichment
  62. 62. • Capture the important information shown to a user on a page • The Datalayer and Google Tag Manager make it far easier to capture information about a page and push it into Google Analytics • You’ll still need developers to generate the Datalayer • The data can then be stored in a custom dimension or in an event @OptimiseOrDie @CharlesMeaden Capturing Content About A Page
  63. 63. @OptimiseOrDie
  64. 64. • Capturing how the user interacts with individual elements on the page is incredibly useful for understanding user behaviour • Organisations such as M&M Direct are capturing every click to build ‘Propensity to Purchase’ models • Really important to build an event taxonomy that describes how people interact with your site @OptimiseOrDie @CharlesMeaden Capturing Interactions on A Page
  65. 65. @OptimiseOrDie
  66. 66. ACTION (VERB) Clicks, Applies, Adds, Removes, Selects, Collapses, Expands, Views CATEGORY (CONTEXT) Navigation, Footer, Filters, Button, Promotion, Product, Basket, Search LABEL (OBJECT) Contact Us, Product ID, Sizefilter, List ID, www.crud.com, GBP @OptimiseOrDie @CharlesMeaden The Grammar of Event Tracking
  67. 67. Clicks Navigation About Us Clicks Button Read More Views Product 11234 Adds Basket 11234 Views Product 82641 Scrolls Content 50% Clicks Promotion May001 Clicks Currency GBP @OptimiseOrDie @CharlesMeaden The Grammar of Event Tracking Views List 11345 Applies Filter Size|12|black Clicks Footer Terms and Conditions Views Basket [contents] Clicks IncreaseQty 11234 Clicks Button Checkout Now Reaches Checkoutstep 1 Clicks Button Find Address Action/Verb Category/Context Label/Object
  68. 68. Tip! – 500 characters lets you stuff values with separators @CarmenMardiros Stuff Attribute Data into Label
  69. 69. Building an Event Grammar – Alex Dean The Lego Data Layer – Carmen Mardiros Event Tracking and 10 Questions to Answer First – Paul Koks Event Tracking in Google Analytics – Himanshu Sharma 13 Useful Custom Dimensions For Google Analytics – Simo Ahava 50+ Custom Dimensions in Google Analytics – Martijn Scheijbeler Tracking Multiple Categories for Content Pages – Allaedin Ezzedin @OptimiseOrDie @CharlesMeaden Tips and Resources
  70. 70. 8 – DATA MODELS
  71. 71. @OptimiseOrDie s zn+1 = zn 2 + c Every Client has Gearing:
  72. 72. @OptimiseOrDie Favourite Models of the Masters A. 15 minute Device Model B. Bounce Layer Analysis C. Horizontal Funnel D. Segmented Funnel E. Page Group Yield F. Intent Model G. Landing & Next Page Paths H. Top of Funnel Drivers I. Flow Report Hacking J. Multi Goal Groups K. Temporal or Lifecycle L. Ecommerce Grid M. Dimensional Funnel
  73. 73. @OptimiseOrDie 30 minutes to save £80M+ in conversion: bit.ly/DeviceModel15
  74. 74. Page Yield Group % traffic User CR # Sales % revenue List / Grid 44.33% 0.24% 7547 27.6% Product Page 15.19% 0.12% 1293 4.7% Homepage 13.49% 0.82% 7848 28.7% Brand 9.75% 1.28% 8851 32.3% Category 4.51% 0.31% 991 3.6% Blog 4.00% 0.21% 596 2.2% • Why does product page conversion suck so much? • Touch devices (Mobile & Tablet) impacted • Now 7x Conversion – added 30% to revenue • 40% of traffic to these pages was PPC, D’oh! Landing Page Group Model:
  75. 75. @OptimiseOrDie All traffic HearingSight StoreOther Step 1 Step 2 Step 3 Goal Page PageHearing Intent – Landing Page Groups
  76. 76. @OptimiseOrDie All traffic HearingSight StoreOther Contact form Interact Submit Goal Store Intent Modelling – Stores: Phone Answers Goal Visit Promo viewed / printed Store visit
  77. 77. • Funnel head gets 94% from ONLY 3 pages • There are 3 types of PPC template being used • So 6 pages account for 94% • Simples! - to increase funnel flow, link more funnel head drivers or increase CR of other pages to the funnel head! • Increase head drivers • Experiment with templates Funnel Head Drivers:
  78. 78. Funnel success Funnel Step 2 Funnel Step 1 Sales Ecommerce Behaviour @OptimiseOrDie Traffic Automated funnels for: • New & Returning • Analytics Channels • Country • Customer Type • Mobile, Tablet, Desktop • iPhone Model • Windows OS • Mac OS • Browser & Version • In app or Native Browser • Screen Resolution • Landing page(s) • Content page(s) viewed • Demographics • Days to conversion • Path Length Dimension Grid Pull
  79. 79. @OptimiseOrDie Why are Segmented Grids useful? • Segments on speed! • Quick to scan • Shows up oddities in: • Landing & Bounce • Site Depth Engagement • Funnel Losses • UX Issues • Bugs & Broken stuff • This one grid cube on the left started 1 hour of work that fixed an 800K loss per month! Try app.profitgrid.io
  80. 80. @OptimiseOrDie Tip! Sketch with paper first:
  81. 81. 9 – DATA AUTOMATION
  82. 82. • If you need to run a report more than once • If it involves multiple steps and clicks • If it takes longer than 2 minutes • AUTOMATE IT • You’ll get to the data quicker • More time left over to actually do thinking and analysis! • Write once, use multiple times @OptimiseOrDie @CharlesMeaden When and Why Should You Automate
  83. 83. @OptimiseOrDie
  84. 84. • 15 3 minute Device Model • Bounce Layer Analysis • Site Speed DOM Timings • Most navigated to pages • Locating personally identifiable information (PII) • Exporting and finding query strings • Grouping device screen heights • Classifying search terms from internal search • Building user based funnels • Building categories from URLs using regex patterns @OptimiseOrDie @CharlesMeaden Charles and Craig Most Frequently Used
  85. 85. @OptimiseOrDie Automated Ecommerce Models A. Customer Segmentation B. New vs. Existing customer C. Basket analysis (various) D. Returns analysis E. Site Search analysis F. Boston Grid Quadrant G. Profit Analysis H. Yield Analysis I. Product Interaction Layer analysis J. Out of stock analysis K. First purchase / anchors L. Discount impact model M. Cart abandonment analysis N. Live chat or textual analysis O. Merchandising reporting (various)
  86. 86. • Excel plugins such as Analytics Edge or Supermetrics for Excel allow you to access the Google Analytics API directly with no need to program the queries • The Google Analytics Spreadsheet Add-on takea data directly into Google Sheets • Analytics 360 users can export directly to Big Query • Data Studio reports will automatically update from Google Analytics • Email reports from Google Analytics @OptimiseOrDie @CharlesMeaden How do I automate stuff?
  87. 87. @OptimiseOrDie Automating Models and Data Integration: Dimensions, Metrics, Query Explorer: Very useful for forming queries and getting to know the API: https://developers.google.com/analytics/devguides/reporting/core/dimsmets https://ga-dev-tools.appspot.com/query-explorer/ Guide to getting started with the API: https://www.optimizesmart.com/how-to-use-google-analytics-api-without-any-coding/ Free Google Sheets Addon: Google Sheets Addon: https://developers.google.com/analytics/solutions/google-analytics-spreadsheet-add-on
  88. 88. @OptimiseOrDie Automating Models and Data Integration: Automating Google Sheets: https://medium.com/@jev/how-to-import-data-from-google-analytics-into-google-sheets-with- google-apps-script-5174a10b24d8 ProfitGrid: Simple tool to pull a multi-dimensional grid from any GA setup: http://app.profitgrid.io Analytics Edge: Very flexible excel tool for pulling API data. Free version available. Bristling with options: http://www.analyticsedge.com/simply-free/ Supermetrics: Free GA plugin for Excel and Google Sheets. Multiple data sources available: https://supermetrics.com/product/supermetrics-data-grabber/ https://supermetrics.com/product/supermetrics-for-google-drive/
  89. 89. @OptimiseOrDie Automating Models and Data Integration: PowerBI: Allows you to pull GA data directly - was PowerPivot. If you want a multi-dimensional API pulled horizontal funnel you can segment on-the-fly, this is what you need. A very powerful way of viewing and pivoting cubes of GA data: https://powerpivotpro.com/get-the-software/ Next Analytics: Free and paid options available: https://www.nextanalytics.com/excel-google-analytics/ Analytics Canvas Integration, extracts, multiple accounts, automation and scripting. Paid only. http://analyticscanvas.com/google-analytics/ Scitylana: Integration, Hit level datastream, Extracts. Free option available. https://www.scitylana.com/
  90. 90. @OptimiseOrDie Automating Models and Data Integration: Integrating GA with R: http://code.markedmondson.me/googleAnalyticsR/ http://cran.r-project.org/web/packages/RGoogleAnalytics/ https://github.com/skardhamar/rga http://cran.r-project.org/web/packages/RGA/index.html R for Analysts: http://www.eanalytica.com/r-for-web-analysts/ Simo Ahava Recommends: "I wrote these two a while ago. First is for validating a GA account setup, with focus on Custom Dims too, and the second is for mass updating Custom Dimensions" https://chrome.google.com/webstore/detail/google-analytics- validato/nmjiiaaejkhpegmcpfaehmbijgoilimo?utm_source=permalink https://chrome.google.com/webstore/detail/google-analytics-custom- d/ogcaloflfbimfnpkkfpfddocaegdmgkk?utm_source=permalink
  91. 91. 10 DATA OWNERSHIP IS WEAK
  92. 92. Do these sound familiar?
  93. 93. Monthly reports which lack relevance, are rife with generic suggestions unsupported by research within the context of your business and simply regurgitate last month’s points, failing to show any new actionable data. Thanks to @Simoahava
  94. 94. Ugly and ineffective hacks to get tracking working at the last minute. A lack of coordination or standards for how business critical tracking should be delivered. No data layer or cross silo approach. Thanks to @Simoahava
  95. 95. Analytics changes are given low priority and deployed infrequently Fix Funnel Tracking Thanks to @Simoahava Deploy new funnel
  96. 96. Analytics tracking is often ‘added later’ or seen as a ‘Bolt On’ to existing project work because ownership is unevenly distributed!
  97. 97. Thanks to @Simoahava
  98. 98. How to Integrate Analytics & Agile Agile Analytics: www.youtube.com/watch?v=yIJp9s46CF8 Meaningful Data: www.youtube.com/watch?v=rMrB0bKdOtc
  99. 99.  Data Ownership  Weak ownership kills data outcomes  If your data is not there, late or crap, this is why  Watch the Simo talks on Agile Integration  It isn’t ‘Done’ unless Data’s there @OptimiseOrDie @CharlesMeaden
  100. 100. 11 TRAINING + INVESTMENT
  101. 101. “This is a huge weakness for many of my clients. Few companies validate if the analytics tools and skills people are given, actually allow them to do their jobs quickly and proficiently.” Craig Sullivan
  102. 102. @OptimiseOrDie Train Your Team so they…. • Can be better at their job, through data • Know how everything works in analytics • Get data out with less work • Achieve self servicing for data needs • Automate repetitive tasks • Get more proficient at finding value • Become happier and less bored! A Ferrari mechanic without engine training?
  103. 103. @OptimiseOrDie Invest in Analytics Even if tools are free, you should: • Get an Independent Audit • Invest in a proper release architecture (QA/DEV/STAGING) • Make tracking part of every project • Don’t just tread water – improve tracking • Put >5% of dev & analytics budget on ENHANCING • Things like -> Data Collection, Team Training, Fixing Stuff, Automation, Enrichment, Tracking Tools • It’s like writing a love note to yourself…
  104. 104. @OptimiseOrDie Write a Love Note to your Future Self: Hey Craig, All we are is dust in the wind dude. You’re like my future self, so I had to tell you. I thought it would be most excellent to give you clean data, so I fixed it, like all the things. You’ve got like at least 3 months of clean data man and like all the reports and stuff totally makes sense now! Whoa! Love you, Dude! Craig from the Past, Dude
  105. 105. @OptimiseOrDie Invest in Tech & Dev Don’t forget investing in the relationship with tech: • Build a direct relationship with dev & tech teams • Educate them on the outcomes and positives you seek • Educate yourself on how dev, platform & release cycle works • HELP THEM to deliver analytics reliably without extra work • Help to SOLVE PROBLEMS, s**t will get done Examples: • Give code changes directly to dev (not via marketing) • 5 minute video explanation of the data layer • Integrate the dev staging environment with the GA staging view
  106. 106. SUMMARY
  107. 107. 480 client configurations 95% had high priority issues 100% had medium priority 3/480 had no tracking issues <1% had solid analytics The Dark Side @OptimiseOrDie
  108. 108. @OptimiseOrDie @CharlesMeaden The Sunny Uplands:
  109. 109. @OptimiseOrDie Collection Skew Pollution Enrichment Modelling & Noodling Automation Ownership Invest & Train OUR PATH TO ANALYTICS SUCCESS:
  110. 110. THANK YOU! • WRITE THAT LOVE NOTE! • WANT AN AUDIT? • SKILLS TRANSFER? CHARLES bit.ly/2HeHAt6 CRAIG linkd.in/pvrg14Optimising the Optimisation @OptimiseOrDie @CharlesMeaden SLIDES bit.ly/PowSmc

Editor's Notes

  • This is what we’ll cover today in the talk – what the big problem is that I’m trying to solve and some basic groundwork you should do before you start. I also show you how to pull the data for your company with a 15 minute technique and how to use this to test the right browsers and devices on your website or product.

    I’ll wrap up with showing you some examples and how to completely automate everything we’ve covered today, so nobody whines later on ;-)
  • We spotted this during a site audit six months after it had been put in
  • The key here is have
  • The tips and resources section contains a list of
  • Not everyone will necessary know that the data is skewed or what steps need to be taken to clean the data

  • Your data may look like this piece of data – shattered into tens, hundreds or thousands of pieces of data
  • Added this to make the point that it’s over looked by devs and others who assume that this just work
  • Another good thing to setup an early warning system for
  • Not everyone will necessary know that the data is skewed or what steps need to be taken to clean the data

  • Query strings in the URL’s not pretty, but it worked as they had a process to extract then

    The analytics team hadn’t been involved in the site rebuild
  • Make the point that there are ten million hits and this a quick and easy way to find out what you have

    Also a really good reminder that you may be capturing events that you don’t need
  • Think about what data you need to capture both your short term and long term goals
  • This slide to highlight all the things you can capture on the page – animation sequence set to add and remove then
  • This slide to highlight all the things you can capture on the page – animation sequence set to add and remove itwm
  • Quick click through slide to illustrate how many clicks it takes

  • Mentioning audits as changes can creep in

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