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[ Target ]
Definitely
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Definitely
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![The biggest challenge?
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Ten Powerful Tips To Get More From Your Analytics
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The document outlines ten essential tips for optimizing analytics efforts, including the importance of prioritizing key performance indicators (KPIs), understanding basic metrics, and leveraging testing strategies. It addresses common challenges in the analytics field, such as the skills gap and underinvestment despite demand for measurable results. Additionally, the document emphasizes the significance of effective data integration, appropriate attribution modeling, and utilizing the right tools to derive actionable insights from analytics.
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Ten Powerful Tips To Get More From Your Analytics
- 1. 10 Powerful Tips to get more from your analytics 10 Powerful Tips to get more from your analytics Senior Partner, Web Analytics Demystified michele@webanalyticsdemystified.com @michelejkiss Michele Kiss
- 2. Agenda How to prioritizeyour analytics efforts Making the most of fundamental features Leveraging User and A/B/MV Testing Automation and data integration Attribution Alternative analytics solutions Working with your ‘human’ resources
- 3. Challenges Vast shortages ofanalytics professionals 50-60% gap between supply & demand
- 4. Despite evidence ofthe success analytics can bring, companies under-invest
- 5. (Yet demand ‘measurableresults’ from marketers)
- 6. The result? Digital MarketingManager Requirements: • 30 years social media experience; • Expert Javascript developer; • Advanced degree in Mathematics and Statistics; • Fluent in R and SAS and able to build complex regression models over a cup of tea; • Single-handedly able to build and manage an Enterprise Data Warehouse; • Ability to manage seventeen different social networks, including that new one that doesn’t make any sense for our business but ‘my kids use it so we need to be there.’
- 7. m a rk e t e r s a r e d r o w n i n g i n d a t a
- 8.
- 9. So how canI get more from my data?
- 10. 1. Start byFocusing
- 11. Don’t overwhelm yourselfby trying to measure everything
- 12.
- 13. Define your KPIs Thisis not short for 1,000… Key Performance Indicators Define your KPIs
- 14. If everything is critical, then nothing is
- 15. We struggle todo this with data. But, marketers prioritize all the time When you cut budget from one area When you exclude a tactic (or channel) from your plans
- 16. Defining KPIs isnot this…
- 17. Analytics is notabout “building a report of all our web metrics” It’s about Selecting and focusing on the data necessary to measure success
- 18. A better wayto think of ‘KPIs’ What do I want to achieve? How will I know if I’ve done that? These are your KPIs!
- 19. For each channelyou invest in (time or money) What one thing do you want people to do? In other words… Why do you even bother?
- 20. Use this to focus on the essential data
- 21. Examples… Goal: Build brandaudience Sample KPIs: • XX% Growth in Linked In followers • XX,XXX Views of Website • XX% Conversion to Lead (to ensure you’re not building a low performing audience!)
- 22. Examples… Goal: Engage LoyalCustomers Sample KPIs: • XX% Share rate of content • XX,XXX Referrals • XX% Forum participation rate
- 23. Examples… Goal: Build awarenessfor a new product Sample KPIs: • XX,XXX Impressions delivered to target audience • XX% Product awareness lift • XX,XXX Views of product content (e.g. informational landing page)
- 24. Examples… Goal: Encourage producttrial Sample KPIs: • XX% Conversion to trial • XX% Conversion from trial to paid customer • XX,XXX Views of pricing page
- 26. A KPI isnot a KPI without a target.
- 28.
- 29. Bracketing is handy,too. 1 lead [ 1,000,000 leads ] [ Target ] Definitely Bad Definitely Good
- 30. A KPI isnot a KPI without a target.
- 31. If you can’tarrive at an educated estimate before you start You won’t magically “know what success looks like” when you finish!
- 32. 2. Nail theBasics
- 33. Understand the terms VisitorOne individual coming to your site Individual device Visit One time-based encounter an individual has with your site Time-out depends on your settings Page View Number of times a page loaded What if you don’t have a page refresh? and the limitations!
- 35. Why Time Spent1is a Terrible2 Metric 1 So is Bounce Rate 2 Okay, ‘terrible’ is a little extreme, but you can do much better
- 36. Time Spent Fundamental issue: ‘Time Spent’ is not inherently good or bad.
- 37. Time spent withcontent CustomerSatisfaction/Likelihoodto Convert/SomeotherawesomethingPresumed Correlation
- 38. But… Users also spend(more) time when: They can’t find what they are looking for (And are highly motivated to persevere)
- 39. Time Spent Practical issue: Page A 00:01:00 Page B 00:01:45 Time Stamp of Page B minus Time Stamp of Page A
- 40. Time Spent Practical issue: Page A EXIT There is no Page B time stamp! These people are excluded from your time average
- 41.
- 42. Bounce Rate Definition: “User landedand didn’t take another action”
- 43. Bounce Rate Definition: “User landedand didn’t take another tracked action”
- 45. It’s not thattime and bounce rate are ‘bad’ We can just do better
- 46. What’s better? Go backto this…
- 47. What one thing do you want people to do?
- 48. Better than BounceRate Early stage: • % View more information • % View pricing • % Download a brochure
- 49. Better than BounceRate Conversion: • % Navigate to the form • % Submit the form • % Sign up for emails
- 50. Better than BounceRate Content Consumption: • % Click related content • % Share the article
- 52. 3. Take CreditWhere Credit is Due
- 53.
- 54. Will automatically detectsome information about incoming traffic
- 55. Traffic from search Trafficreferred by other websites
- 56. This is informationis very rudimentary!
- 57. Limitations • Auto-detection can’ttell paid and organic search apart • Nor brand vs organic vs shared social • Email typically counts as “Direct to Site” • Everything that’s not a search engine is a “referring website”
- 58. But Google Analytics gives you a way to customize! You can literally tell GA where traffic came from and how to treat it
- 59. Involves appending query stringparameters http://www.mywebsite.com ?utm_campaign=presidents-day-sale &utm_medium=display &utm_source=catalina Don’t be scared… it’s easy
- 60. Use for • Displayads • Search ads • Emails • Social posts … Basically any link that we can control
- 61. (Where the destinationis a owned property, tracked with Google Analytics) • Brand website • Mobile site • Tumblr blog
- 62. Whatever you namethe utm_ variables shows up in your reports!
- 63. Source Site, propertyor partner e.g. Google, Facebook, Pinterest, GDN Medium Channel (Grouping of Sources) e.g. Social, CPC Campaign Overarching marketing initiative Content Optional, for additional information E.g. “Email Header / Footer” or “Headline 2” Or Author… Term Optional, for paid search only Variables to choose
- 64. Level of detail Youcan be as detailed or specific as makes sense
- 65.
- 66. Types of LinkedIn Posts linked-in-blogpost linked-in-post linked-in-page
- 67. The Most ImportantThing is consistency Display not Display or Display Ads or Banner Ads
- 68. You can usethis everywhere… How many people click through my email signature? http://michele.webanalyticsdemystified.com/ ?utm_source=emailsignature &utm_medium=email &utm_campaign=mkemailsignature &utm_content=michele
- 69. HOW do Ido this? Two options: 1. Google Analytics URL Builder
- 70. HOW do Ido this? Two options: 2. Create your own! Use drop-downs to select pre-populated sources and mediums Allow write-in campaign names (since those change more often)
- 71. A caution Because the most important thing is consistency A shared spreadsheet with (consistent) drop-down selections is ideal to enforce it…
- 72. Lack of consistency… Leadsto this:
- 73.
- 74. You are not youruser
- 75.
- 76. User Testing Remote UserTestingFormal User Testing Observation Focus Groups Eye tracking Task completion Card sorting
- 77. A/B/n Testing Testing 2(+)versions against a control • Can test whole pages • An entire experience / flow • Or single changed element (e.g. button)
- 78. Multivariate Testing Test multipleelements at one time • Relies on testing software to tease out impact of each element change and propose best combination
- 79. User Testing “Why” Small samplesize Quantitative data Qualitative feedback Test partial concepts “How much” Large sample size Quantitative data Real customer results Tests parts or whole A/B/MV Testing
- 80. User and A/BTesting… Not either/or
- 81.
- 82. Quick User TestingOptions
- 83. Types of A/BTests: Full Page
- 84. Types of A/BTests: Button
- 85. Simple ! Complex Startsimple! • A/B tests are far simpler • Multivariate tests more complex
- 86. Content Experiments Part ofGoogle Analytics
- 88.
- 89. Testing is notjust throwing ideas out Good testing starts from a hypothesis
- 90. “I believe thatchanging the call to action will lead more users to click-through to sign up.” “I believe that a shorter sign up form will increase conversion through the form.” “I believe that linking to support articles will reduce call center volume.”
- 91. Boring (but reallyimportant) Stats Lesson
- 92.
- 93. Significance & Confidence Confidence “95%confidence” If we repeated this test 100 times, we would see similar results 95 times Results are ‘Significant’ Based on statistical significance (meeting a 95%+ criteria), not the ‘importance’ of the test results
- 94. The biggest challenge? Process [Hint:It’s not normally the technology…]
- 95. Test ideas Evaluate Test design Setup,QA & Launch Analyze results Follow up tests Testing roadmap
- 96.
- 97. 3 Biggest Mistakesin Testing ‘Calling’ a test too early Results may fluctuate early on and you may ‘call’ a false winner
- 98. 3 Biggest Mistakesin Testing Isolating testing from launches If it launches, it should be tested first!
- 99. 3 Biggest Mistakesin Testing Not leveraging & integrating analytics Analytics can: • Ensure your test ideas will materially move the needle for the business! • Provide data-driven test ideas
- 100. 5. Automate (ToSave Time)
- 102.
- 103.
- 104.
- 105.
- 107. Any one dataset alone is incomplete
- 108.
- 109.
- 110. Disconnected Data Data combination “Person” level data integration Dashboardsolutions APIs and Plugins Excel and Tableau Direct Connections
- 112.
- 113.
- 114.
- 115. Side-by-side data • Excel • Tableau • Via APIs / plugins: – Supermetrics – Next Analytics – Shufflepoint – Analysis Engine – Analytics Canvas
- 116. 7. Go Beyond“Last Click”
- 117.
- 118.
- 119. Evolution Last Click & Siloed RuleBased Data Driven
- 120. Understand current attribution “Butwe’re not doing attribution!”
- 121. Google Analytics Last-touch bydefault (With one exception)
- 122.
- 123. Siloed systems Siloed datais, essentially, duplicated attribution
- 124. Last Click & Siloed RuleBased Data Driven
- 125. Attribution Models Applying rulesto decide what credit is assigned Display Paid Search Organic Search Conversion Introducer CloserIntermediate
- 126. Example Models ConversionIntroducer CloserIntermediate 100%(First Touch) 100% (Last Touch) 33% 33% 33% (Equal Weighted) 20% 30% 50% (Custom) 50% 50% (Custom)
- 127. Last Click & Siloed RuleBased Data Driven
- 128. Data Driven Attribution Usesdata to decide how success should be attributed
- 129. Last Click & Siloed RuleBased Data Driven Significant Cost Factors
- 130.
- 131.
- 132.
- 133. 8. Use TheRight Tool For The Job
- 134. Don’t expect onetool to answer every question
- 135. What are peopledoing? Web Analytics Question Which performs better? Why do our users do/don’t do “X”? Social Analytics Surveys A/B/MV Testing User Testing Session Replay Voice of Customer
- 136. This doesn’t mean you have to go out and buy a ton of new tools. Just use the ones you have in the right way.
- 137. 9. Make Senseof the Numbers
- 138.
- 139.
- 140. 10. Use YourResources
- 141.
- 142.
- 144. Don’t let yourdefendant be your jury
- 145.
- 146. Set clear accountabilities Involvean ‘independent arbitrator’
- 147. Don’t stop atvanity metrics
- 148. Keep them fullyinformed! An in-depth analysis of your paid search efforts is not helpful if the agency is unaware of major television spend!
- 149. Multiple Agencies Brand Search Social Website Media need tobe in contact with a good working relationship
- 151. Magical insights –just add data!
- 152. If what youget from your analytics team is not helping you, you’re doing something wrong (too)
- 153. Good analysts want to contribute value (They don’t want to produce Excel spreadsheets that everyone ignores)
- 154. Keep them fullyinformed! Applies here too!
- 155. c o nte x t
- 156. How to providecontext Be clear about goals Keep updated about actions
- 157.
- 158. Don’t ask fordata Pose business questions
- 159. “I want areport of visitors by city.” “I am trying to decide the best area to hold an event.” “I want a report of visitors by city.” “I am trying to decide the best area to hold an event.”
- 160. “I need thebounce rate for every page on the site.” “I am checking out landing page optimization tools and looking for a good ‘beta’ page to test.” “I need the bounce rate for every page on the site.” “I am checking out landing page optimization tools and looking for a good ‘beta’ page to test.”
- 161.
- 162. Audit what you’reasking for
- 163. Request (and attend)regular trainings
- 164. Remember Your analysts andpartners want to help you! Talk to them about how they can best support you (and how you can help them to do so!)
- 165. Senior Partner, WebAnalytics Demystified michele@webanalyticsdemystified.com @michelejkiss Michele Kiss Questions?