SUPERWEEK Analytics Presentation
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Optimizing Google Adwords using Google Analytics
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SUPERWEEK Analytics Presentation
- 2. About @analyticsninja Loves working with fun businesses
- 3. Goal of this presentation • Discuss the integration between Google Adwords & Google Analytics • Definition of Adwords specific metrics in GA and their corresponding Adwords settings. • Analysis techniques to improve PPC performance (bulk of presentation) http://online-behavior.com/ebooks
- 4. Dimensions & Metrics Dimensions – Describe Data Metrics – Measure Data
- 5. Dimensions & Metrics Dimensions – Describe Data Metrics – Measure Data Full list of every Adwords specific dimension and metric
- 8. Custom Reports – The ABC’s Drill Down
- 9. Custom Reports – The ABC’s Micro Conversions @analyticsninja
- 13. Help Determine Relevancy using Bounce Rate
- 20. Keyword Optimization - Negatives
- 22. Keyword Positions & Bidding
- 23. Keyword Positions & Bidding Example when to boost bids
- 24. Keyword Positions & Bidding
- 25. Not Segmented by Match Type
- 27. Destination URLs not Filtered
- 28. @analyticsninja
- 29. Why engagement goals matter Lower than Avg. Ecommerce Rate Higher than Avg. User Engagement @analyticsninja
- 30. How to choose Page Depth & Time on Site Goals
- 31. Multi-touch Attribution Examples @analyticsninja
- 32. Optimizing Adwords Campaign Settings • Network – • Ad Scheduling – Google Time of Day Search Partners Day of Week Display • Language • Devices – • Location – Desktop GeoTargeting Tablets Smartphones @ analyticsninja
- 34. Auto / Managed Placements Actual domain where ad displayed @analyticsninja
- 35. @analyticsninja
- 36. UGH! I hope your conversions don’t look like this! @analyticsninja
- 37. However… @analyticsninja
- 38. Check to see if they look like this
- 39. Display Network Assists @analyticsninja
- 40. @analyticsninja
- 41. Display Network Assists @analyticsninja
- 42. Discover which domains are making the biggest impact @analyticsninja
- 43. Get Ready for Attribution Modeling it’s where the money is at @analyticsninja
- 44. Optimizing Adwords Campaign Settings • Network – • Ad Scheduling – Google Time of Day Search Partners Day of Week Display • Language • Devices – • Location – Desktop GeoTargeting Tablets Smartphones @ analyticsninja
- 45. Ad Scheduling
- 46. Ad Scheduling
- 47. Day of Week @analyticsninja
- 48. Day of Week @analyticsninja
- 49. Day of Week @analyticsninja
- 50. Add a Secondary Dimension (any) @analyticsninja
- 51. Hat Tip @analyticspros @analyticsninja
- 52. Day of Week @analyticsninja
- 53. Day of Week @analyticsninja
- 54. While we’re on the topic of time… @analyticsninja
- 55. It is easy to discover “increases” in GA @analyticsninja
- 56. It is difficult to discover “decreases” in GA @analyticsninja
- 57. Inverse Date Range Comparison @analyticsninja
- 58. Optimizing Adwords Campaign Settings • Network – • Ad Scheduling – Google Time of Day Search Partners Day of Week Display • Language • Devices – • Location – Desktop GeoTargeting Tablets Smartphones @ analyticsninja
- 59. Mobile Growth
- 60. Mobile Campaign Settings @analyticsninja
- 61. Mobile Analysis • Use the Standard Campaigns report as Mobile includes cost data there too. • Multi-Channel Funnels are somewhat less useful for Mobile Analysis because it is quite possible that converting customers return on a non-mobile device. • Pay special attention to micro-conversions coming from mobile. • Add a smartphone only advanced segment (Smartphone vs. Tablet vs. Deskop) @analyticsninja
- 62. Mobile Analysis @analyticsninja
- 63. Related to Mobile Analysis BROWSER @analyticsninja
- 64. Related to Mobile Analysis Screen Resolution @analyticsninja
- 65. Optimizing Adwords Campaign Settings • Network – • Ad Scheduling – Google Time of Day Search Partners Day of Week Display • Language • Devices – • Location – Desktop GeoTargeting Tablets Smartphones @ analyticsninja
- 66. Location Targeting Optimization @ analyticsninja
- 67. Location Targeting Optimization @ analyticsninja
- 68. Location Targeting Optimization @ analyticsninja
- 70. Remarketing with GA @ analyticsninja
- 71. Remarketing with GA Visitor Segmentation! @ analyticsninja
- 72. Remarketing with GA Product Cross-sells @ analyticsninja
- 73. Remarketing with GA Watched Promo Video
- 74. Remarketing with GA Freemium Retargeting
- 75. Contact Info Yehoshua Coren ninja@analytics-ninja.com Twitter: @analyticsninja www.analytics-ninja.com @ analyticsninja
- 76. BONUS
- 77. BONUS
- 78. BONUS
- 79. BONUS
Notas del editor
- Having worked with businesses in a lot of different industry verticals, I can confidently say that analytics is important to everyone and needs to be tailored to each business.
- In other words, dimensions are the things that describe the visit, visitor, page, or event. Dimensions are what make up the rows in GA reports; they are the things we "drill down" into when analyzing data. Most common dimension pair we use is Source / MediumLater we’ll talk about some less commonly used dimensions that can lead to powerful optimizations.
- Most potent aspect of the Google Analytics + Adwords integration is the fact that a large list of Adwords specific dimensions and metrics are automatically populated simply be configuring auto-tagging correctly.Metrics will inform us about performance. Dimensions will allow us to know what to optimize, whether by changing campaign settings or through bid management.
- Lets take a look at the most commonly used Adwords report, the campaign report. Primary dimensions are Campaign > Adgroup > KeywordSecondary dimensions include everything in the list aboveIt is important to remember / consider that the ease of data access, beauty of UI, speed of processing and interface makes it much easier to arrive at decisions using this tool (GA).
- We’re going to go back to mobile later on in the presentation.
- This framework is not my own, rather it is a reframing of AvinashKaushik’s Acquisition Behavior and Outcomes, which is more accurate, but I substitute the word conversion as it is the desired outcome, and a bit easier to remember the ABCs.Benefit of Custom Reports is that you’ll be able to see a fuller view of your data in one place. Two types – explorer or flat table. I almost always use the explorer because I can drill down into my data.In this presentation, please pay particular attention to these custom reports and use them as a blue print for building your own.
- Explain ABC’s - my own take on AvinashKaushik’s “Acquisition, Behavior, Outcomes”Including all three in your reports allows for efficient data analysis.We’re going to spend some time talking about macro conversions and micro conversions.Macro conversions for ecommerce would be view a receipt page.Micro conversions – newsletter signup, online chat, add to cart, social share, phone call, whitepaper download.Notice two of the metrics in this custom report, page depth and time on site.
- This is what the macro conversion tab looks like in the actual report.In the drill down example in the bottom left I included Matched search query. At this time, Adwords cost data is not available for search queries, so you’ll need to just focus on performance metrics.
- Optimizing by bounce rate. Bounce rate always needs to be viewed in context and for content sites a high bounce rate is not always a bad thing.However, if you’re doing PPC then a high bounce is almost always a bad thing.
- Take a look at the landing page. Oftentimes, advertisers make really poor choices about what page a person lands on. Also, keep any eye on the outcomes. Just because someone doesn’t bounce and they look at 2 or 3 pages on your site, doesn’t mean they are interested or engaged. They might just be lost.Highlighted are two problematic campaigns.
- Another use way to sort data is by ROI. There is no weighted sort for this yet.Ecommercemetrics poor, what about other metrics? In this report I noticed low bounce rate and high pages per visit.
- Ecommerce metrics poor, what about other metrics?Upper funnel indicators strong. Looking at phone calls, and chats, important conversion points especially for B2B. Moving on to optimizing keywords.
- Keywords in Adwords always have an associated matchtype. You bid on a keyword matchtype combo.
- Adding negative keywords is a tremendous way to save money.
- Although cost data isn’t available, valuable data From Google analytics is still available about the matched search queryDrill down by match type, then keyword, then to match search queryIdea is to find new negative keywords, or new keywords to bid on.
- First drill down by match type > then into the keyword and do a weighted sort.
- Action item – add negative keywords
- Of course, additional segmentation for branded vs. non-branded terms is necessary hereBut I believe if you look at this data in your own accounts you’ll see huge differences in CTRs between Top and RHS.
- Sorted by ROILooking for LOW CTR and HIGH impressionsNotice the filter – this because some campaigns had very low volume but 1 or 2 transactions kicked up their ROI.
- Here are the settings for the custom report. (describe)Strong ROI, great place to up the bid to drive more traffic.
- If these keywords are segmented by matchtype, how do we get usable data out of this report?CALLED KEYWORD POSITIONS REPORT
- Don’t forget to clean up your Request URI field later.
- You hopefully noticed in my custom reports that I measure user behavior by setting goals.“Engagement” itself is a very loose term. In GA reports it refers to visit depth and time on site. However, you should really view it as a stepping stone to Visitor Frequency. There are oftentimes “clues” that we can find based upon user behavior during there visit that can inform us as to what type of visitor they are.In this example, the Adwords display network seems like a loser. (add slide)Poor conversion rate + poor engagement or “other” metrics means that there is a very low chance that the visitor might return. Free up money from your PPC spend to focus on higher potential visitors.The above example may be an indication of a visitor early in their buying cycle.Now we have Multi Channel Funnels which provide much deeper insights into whether users return and convert. BIG addition to GA since, in general as a tool, GA is really visits based.New features coming out this year will allow for much better “user segmentation” or “visitor segmentation,” even going cross device if you have a login on your site.
- How to choose engagement goals.Use these reports!Hints or clues we get about the visit should be complimented with MCFs.
- This is how real user behavior looks.Whenoptimizing traffic sources, it is critical not to throw the baby out with the bathwater.This is not an actionable report.
- As a rule of thumb, you should have separate campaigns for display and search.
- I switched the position of the primary and secondary dimensions so that it would be easier to see the Per Visit Value.
- Action Items -> Check days to purchase using multi channel funnels. Drill down in a custom report from Day of Week into Days since last visit and then apply a Visits with Transactions advanced segment.It is possible to do pan-session analysis in GA even without Universal Analytics. This is just a taste of things to come.
- Action Items -> Check days to purchase using multi channel funnels. Drill down in a custom report from Day of Week into Days since last visit and then apply a Visits with Transactions advanced segment.
- Weekly data points (visits). Almost 1 Billion visits in this data set. This is just one site. Not scientific. Take a look at your own site.
- You campaign settings should not look like this.
- In this segmentation example, we can analyze conversion rates and abandonment rates by browser type.Safari is one of the culpritsAdd additional segments for more insights. Slice and dice until you get actionable items.
- Export your data to Excel and use conditional formatting to assist your analysis.Fixing technical issues with your site is a GREAT way to improve conversion. Use GA to find javascript errors in your shopping cart or other cross browser issues.Designers and Site Owners are often using computer systems that differ greatly from their users. I browse the internet with 2 large HD screens. Many users in this example do not.
- (describe metrics)
- Does anyone know the name of the dark green state? Hint, it is not New York or California.
- By adding the filter, I now have information about the regions with enough volume to be worth my time. Still sorted by Per Visit Value.Mash together with publically available census population information to get KPIs like revenue per capita or other such data that relates to marketshare and penetration.