This document provides tips and ideas for using advanced analytics to better manage content. It discusses using social media analytics to monitor engagement, Google Analytics to review content over time, and advanced dashboards and R programming for more granular analysis. The document outlines specific metrics and dimensions to examine in various analytics tools to discover useful content and relationships among traffic sources.

1. Advanced Analytics for Content
Marketers
Tips and Ideas To Manage Content Better With Measurement
Pierre DeBois
Founder and Chief Analytics Officer, Zimana
@ZimanaAnalytics
@zimanaanalytics • #CMWorld

2. AGENDA
① Social Media Analytics – Monitoring Activity
② Google Analytics – Reporting Ideas to Discover Content
Usefulness
③ Advanced Tools – Overview of Purpose
• Advanced Dashboards (Supermetrics)
• R programming (Stats / Regression)
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3. 1 Social Media Analytics
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4. There are analytics dashboards for every platform
Use These to note activity on the platform
What to Look For
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5. Example: Twitter Analytics &
Hootsuite
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6. Example: Twitter Analytics
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7. Increases in followers (if starting out)
Posts , Pins, or Tweets That Received Impressions
(establishing usage)
Gauge Personas to Know How to Best Adjust Messages
Basics That Your Social Media Should Give You
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8. 2 Google Analytics
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9. See how traffic sources contribute to your
main platform.
Note what visitors are examining regularly for
additional content ideas
What to Look For
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10. Connect Search Console / AdWords (optional)
UserID – segment audience by cross device or registration
(developer)
Ecommerce (optional: retail)
Alerts / Goals
Some Assembly Require (What To Note)
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11. Set Goals
① Helps to Compare If A
Change in A Dimensions
Is Worthwhile
② Can be set by:
• Pages reached
• Time in Session
• Economic
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12. Set Alerts
① Navigate to account
admin
② Set a traffic alert
③ Start with a
percentage increase
rather than set amount
for scale
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13. Annotate Events On Key Reports
• Annotate Important Events ( or Keep a log )
• Traffic changes associated with offline marketing
events may be easier to highlight
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14. Look At Content
① Navigate to Site
Content
② Look at Average Time
③ Page Value (goals)
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15. Evergreen Content
① Examine Content & Landing Pages
② Use 30 – 60 – 90 days or Events Annotated to the
timeline
③ Note content that seems to rank consistently – can it
be promoted or extend?
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16. Evergreen Products
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17. Affinity Reports
① Consider Topics That
Appear - Are They Inline
With Site Purpose?
② Examine at 30 – 60 – 90
Days & Annotation
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18. Site Search
① Navigate to Site Content
② Reveals What Topics People Are Searching For
③ Can use 30-60-90 days / annotation to note different
patterns
④ Can Note Where People Are Dropping Off After A
Search
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19. Site Search
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20. Behavior & User Flow
• Are Visitors Navigating
to Other Content
Regularly?
• Drop Offs may be a
good point for popup
reminder message
• More typical for
products
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21. UserID
• Cross device or registered users
• Default for cross devics
• ga('set', 'userId', {{USER_ID}}); //
Set the user ID using signed-in
user_id.
• Creates a filtered view
• Developer sets code for specific
needs (registration)
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22. Social Media Reports
Can help to rank
where your activity
is leading to
conversions
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23. Most Analytics tools are
meant to provide trends.
Use What You Know About
Your Entire Marketing
Schedule to Identify
Patterns.
Think trends
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24. 3 Advanced Tools
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25. Supermetrics Data Grabber
① Import from GA,
AdWords, Facebook,
BingAds, Twitter,
YouTube
② Allows viewing &
graphing Dimensions
and Metrics in other
combination
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26. Data Entry for Basic Validation. Data validation ensures that the
entered data conform to user-specified requirements (e.g., must be
integer between 0-5), and can reduce data entry errors. Basic
Calculations (e.g., descriptive statistics, basic sort, filter, pivot
table).
Viewing/Scrolling Data at a Glance. Excel can be handy for a quick
visual overview of your data or planning for advanced models.
Data Presentation and Summarization in a simple table or graph
What to Look For With Excel
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27. Other Dashboards
① Neo4j
② Tableau
③ DataHero
④ Google Data Studio
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28. 4 R programming
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29. Why R?
① Applies statistical
analysts
② Can blend datasets for
regression, time series
③ Results are shareable
④ Libraries for
integration
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30. Example
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31. R Studio / GUI
① Download
rtsudio.com/produc
ts/rstudio/download
② Other GUI – Visitor
Studio, Eclipse,
Rattle
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32. TwitteR -
RGA – Google Analytics
Most libraries designed to import data or for provided
statistical model
Libraries for R
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33. Many of the advanced
analytics tools are oriented
towards developer
languages (You’ll discover a
LOT of Python and R
solutions). To get the most
from the tool, focus more on
conditions in which data is
generated and how
information is represented as
data. There are an endless
number of resources for
importing from a database.
Don’t get too bogged down
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34. CRAN http://cran.r-project.org/.
MRAN (Microsoft’s version on
CRAN): https://mran.microsoft.com/packages/.
GitHub via install-github function from the devtools package,
devtools::install_github("githubaccountname/packagename").
First install the devtools install.packages("devtools")
Where To Review and Obtain R Packages
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35. Use Social Media Analytics For
Monitoring Engagement
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36. Use Google Analytics To
Review Content Over Time
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37. Use Advanced Dashboards For
More Granular Analysis
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38. Use R For Discovering
Relationship Among Sources
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39. Thank You
pdebois @ zimana.com
zimana.com
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