This document provides guidance on using web analytics data to further institutional goals. It recommends articulating specific, measurable goals and then determining strategies, tactics, and metrics to track progress. Case studies demonstrate how segmentation can provide different insights than aggregate data. The document also demonstrates how to customize the Google Analytics Data Grabber tool to extract data and populate a dashboard for reporting and taking action. Hands-on practice is provided to help users customize the tool for their own analytics needs.
Designing Data Visualizations to Strengthen Health SystemsAmanda Makulec
Slide deck from our hands-on workshop hosted at the 4th Global Symposium on Health Systems Research, focused on basic design tips, tricks, and best practices to improve your charts and graphs.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
Designing Data Visualizations to Strengthen Health SystemsAmanda Makulec
Slide deck from our hands-on workshop hosted at the 4th Global Symposium on Health Systems Research, focused on basic design tips, tricks, and best practices to improve your charts and graphs.
Creating a Data-Driven Organization, Crunchconf, October 2015Carl Anderson
What does it mean for an organization to be data-driven? How does an organization get there? Many organizations think that they are data-driven but the reality is that few genuinely are and that we could all do better. In this talk, I cover what it truly means to be data driven. The answer, it turns out, is not to do with the latest tools and technologies (although they can help) but having an appropriate data culture than spans the whole organization, where data is accessible broadly, embedded into operations and processes, and enables effective decision making. In this presentation, I dissect what an effective data-driven culture entails, covering facets such as data leadership, data literacy, and A/B testing, illustrating concepts with examples from different industries as well as personal experience.
A short workshop from MERL Tech 2016 on how we can think more purposefully about telling stories with our data and designing visualizations to bring those stories to life in global health and development.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
Metrics, Metrics, Everywhere: Choosing the Right Ones for Your Website and So...Brian Alpert
Social media has connected millions of people in ways never before possible, disrupting the landscape and breathing new life into the old questions: "Why is this important and how do we know it's working?" Only now, the answers are more complex. Today's landscape is a splintered collection of new channels, sublimely named yet inscrutable metrics, and a dizzying array of tools both free and paid, offering a dizzying range of possibilities with which to answer the classic analytics question, "What do I measure?" and its first cousin, "What does that have to do with our program?" At this MCN 2013 workshop, the presenters worked with participants to refine and articulate this conversation through a series of examples, case studies, and recommendations. In addition to social media, a healthy dose of web analytics is included, with a particular focus on Google Analytics.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
Marketing Data Sources PowerPoint Presentation Slides SlideTeam
Enhance your audiences knowledge with this well researched complete deck. Showcase all the important features of the deck with perfect visuals. This deck comprises of total of twenty slides with each slide explained in detail. Each template comprises of professional diagrams and layouts. Our professional PowerPoint experts have also included icons, graphs and charts for your convenience. All you have to do is DOWNLOAD the deck. Make changes as per the requirement. Yes, these PPT slides are completely customizable. Edit the colour, text and font size. Add or delete the content from the slide. And leave your audience awestruck with the professionally designed Marketing Data Sources PowerPoint Presentation Slides complete deck.
A quick overview of two techniques from design thinking that can help us better tailor data visualizations to the needs of our audiences. Personas can be used to identify illustrative audience members who represent large groups within our target audience, and journey maps help us understand how an audience receives, interprets, and acts on information.
The illustrative example presented here is rooted in a real world experience, but is not an actual persona and journey used in that work.
Cut Through the Web Analytics Fog: Using GA Data Grabber to Act on Google Ana...Brian Alpert
A common chorus from museum professionals is how challenging it is to make data-driven decisions with which to improve their programs. Popular tools such as Google Analytics are intuitive and seemingly easy-to-use, yet when the time comes to use data to measure a program's stated goals, too often the main question surrounding the data is "So what?" This workshop will focus on bringing clarity to this challenge. Presented at MCN2012, on 11/7/12.
the current state of... Search Engine Optimization (SEO) (Oct, 2015)Brian Alpert
Presented at the Smithsonian National Museum of Natural History Social Media Summit, 7/21/15, updated 10/1/15. A presentation exploring the current state of affairs vis a vis Search Engine Optimization (SEO). Areas of exploration include on-page and off-page SEO, the role social media plays, and tips for search-optimizing the leading social media sites. Overview of the current state of App Indexing. Links to many resources are sprinkled throughout.
Visualisation & Storytelling in Data Science & AnalyticsFelipe Rego
This is a presentation I put together for a talk I gave a while back on data visualisation and storytelling in the context of data science and analytics. The content was a produced from a mix of my own experience in industry and teaching at various schools and also from the work of Edward Tufte, Nathan Yau, Angela Zoss, Peter Beshai, Mike Bostock, among others. I wanted to highlight some basic concepts of what data visualisation is and what are some of the fundamental steps I believe are important in creating analytical dashboards and visualisations. It also contains a bunch of visualisation examples that I find interesting in telling a story with data.
Developing Dashboards with User-Centered DesignAmanda Makulec
Design sprint session hosted at the TechLady Hackathon, focused on the basic principles and techniques for starting a design process with who will use the data, rather than the tables and tools.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
Google Analytics: MVPs and Game-Changing New FeaturesBrian Alpert
Part two of Seb Chan & Brian Alpert’s "Web Metrics and Google Analytics for Museums" workshop looks at some of the most significant recent changes to Google Analytics. With many improvements released over the course of the 2013-14, Google dramatically altered the landscape of the tool's capabilities. The presentation discusses such GA "MVPs" as Advanced Segmentation and Event Tracking, and provides an overview of some of the many new features, including Demographics and Interests reports, custom channels and content grouping, and the coming change to Universal Analytics. Case studies and slides showing best practices and "tips and tricks" are also included, as well as links to the valuable resources used to collect the information. Presented 4/2/14 at Museums and the Web 2014, Baltimore Maryland.
How To Get Into Data Science & Analytics - feliperego.com.auFelipe Rego
These are the slides from my talk at Academy Xi on How to Get Started in Data Science and Analytics. On the day, I had the pleasure of having Joel Stein from Precision Sourcing and his team presenting with me. Also, big thank you to Byron Allen for providing valuable content. Finally, thank you yo Academy Xi for hosting us.
Metrics, Metrics, Everywhere - Choosing the Right Ones for Your Website and S...Brian Alpert
Museums and the Web 2015 workshop includes the analytics process, case studies and a social media framework. Presented by Brian Alpert, Erin Blasco, Effie Kapsalis and Sarah Banks, Smithsonian Institution.
Analytics Tune Up! Google Analytics workshop for beginners, intermediatesBrian Alpert
Workshop presented 6/14/2016 to digital practitioners at the Smithsonian Institution, Washington D.C. Workshop includes:
- Web Analytics Process
- GA Basics
- Exercise: “Solutions Gallery”
- Exercise: Segments
- Exercise: Custom Reports
- Demo: Goals
- Exercise: Dashboards
- New(ish) features
- Universal Analytics
- A few best practices
- A few ‘real world’ questions
You'd like to be more rational and data-driven in your decision making. You know that your museum has been collecting web traffic metrics using Google Analytics, but you've never fully understood what those reports mean for you or your department. How can you use this popular software to find actionable data that helps you do your job better? In this session you will get a practical tutorial, led by two Google Analytics veterans at the Smithsonian, who will provide an overview of the current Google Analytics, including some of its newest, most powerful features. The presenters will also discuss the step-by-step process for moving beyond measurement just for measurement's sake, using real-life museum case studies as examples.
Presenters: Sara Snyder, Smithsonian American Art Museum; Brian Alpert, Smithsonian Institution.
Presented at the American Alliance of Museums 2016 Annual Meeting & MuseumExpo, 5/27/2016.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
Metrics, Metrics, Everywhere: Choosing the Right Ones for Your Website and So...Brian Alpert
Social media has connected millions of people in ways never before possible, disrupting the landscape and breathing new life into the old questions: "Why is this important and how do we know it's working?" Only now, the answers are more complex. Today's landscape is a splintered collection of new channels, sublimely named yet inscrutable metrics, and a dizzying array of tools both free and paid, offering a dizzying range of possibilities with which to answer the classic analytics question, "What do I measure?" and its first cousin, "What does that have to do with our program?" At this MCN 2013 workshop, the presenters worked with participants to refine and articulate this conversation through a series of examples, case studies, and recommendations. In addition to social media, a healthy dose of web analytics is included, with a particular focus on Google Analytics.
Data Visualization Design Best Practices WorkshopJSI
This introduction was presented as part of a workshop at the Measurement and Accountability for Results in Health Summit at the World Bank (June 2015). The workshop focused on simple ways anyone working with data can improve their presentations, and included visualization redesign activity to put these principles in practice.
Marketing Data Sources PowerPoint Presentation Slides SlideTeam
Enhance your audiences knowledge with this well researched complete deck. Showcase all the important features of the deck with perfect visuals. This deck comprises of total of twenty slides with each slide explained in detail. Each template comprises of professional diagrams and layouts. Our professional PowerPoint experts have also included icons, graphs and charts for your convenience. All you have to do is DOWNLOAD the deck. Make changes as per the requirement. Yes, these PPT slides are completely customizable. Edit the colour, text and font size. Add or delete the content from the slide. And leave your audience awestruck with the professionally designed Marketing Data Sources PowerPoint Presentation Slides complete deck.
A quick overview of two techniques from design thinking that can help us better tailor data visualizations to the needs of our audiences. Personas can be used to identify illustrative audience members who represent large groups within our target audience, and journey maps help us understand how an audience receives, interprets, and acts on information.
The illustrative example presented here is rooted in a real world experience, but is not an actual persona and journey used in that work.
Cut Through the Web Analytics Fog: Using GA Data Grabber to Act on Google Ana...Brian Alpert
A common chorus from museum professionals is how challenging it is to make data-driven decisions with which to improve their programs. Popular tools such as Google Analytics are intuitive and seemingly easy-to-use, yet when the time comes to use data to measure a program's stated goals, too often the main question surrounding the data is "So what?" This workshop will focus on bringing clarity to this challenge. Presented at MCN2012, on 11/7/12.
the current state of... Search Engine Optimization (SEO) (Oct, 2015)Brian Alpert
Presented at the Smithsonian National Museum of Natural History Social Media Summit, 7/21/15, updated 10/1/15. A presentation exploring the current state of affairs vis a vis Search Engine Optimization (SEO). Areas of exploration include on-page and off-page SEO, the role social media plays, and tips for search-optimizing the leading social media sites. Overview of the current state of App Indexing. Links to many resources are sprinkled throughout.
Visualisation & Storytelling in Data Science & AnalyticsFelipe Rego
This is a presentation I put together for a talk I gave a while back on data visualisation and storytelling in the context of data science and analytics. The content was a produced from a mix of my own experience in industry and teaching at various schools and also from the work of Edward Tufte, Nathan Yau, Angela Zoss, Peter Beshai, Mike Bostock, among others. I wanted to highlight some basic concepts of what data visualisation is and what are some of the fundamental steps I believe are important in creating analytical dashboards and visualisations. It also contains a bunch of visualisation examples that I find interesting in telling a story with data.
Developing Dashboards with User-Centered DesignAmanda Makulec
Design sprint session hosted at the TechLady Hackathon, focused on the basic principles and techniques for starting a design process with who will use the data, rather than the tables and tools.
A quick reference on designing data visualizations that delight and leverage best practices from the design world to ensure your data is presented in meaningful, usable, fun ways.
Google Analytics: MVPs and Game-Changing New FeaturesBrian Alpert
Part two of Seb Chan & Brian Alpert’s "Web Metrics and Google Analytics for Museums" workshop looks at some of the most significant recent changes to Google Analytics. With many improvements released over the course of the 2013-14, Google dramatically altered the landscape of the tool's capabilities. The presentation discusses such GA "MVPs" as Advanced Segmentation and Event Tracking, and provides an overview of some of the many new features, including Demographics and Interests reports, custom channels and content grouping, and the coming change to Universal Analytics. Case studies and slides showing best practices and "tips and tricks" are also included, as well as links to the valuable resources used to collect the information. Presented 4/2/14 at Museums and the Web 2014, Baltimore Maryland.
How To Get Into Data Science & Analytics - feliperego.com.auFelipe Rego
These are the slides from my talk at Academy Xi on How to Get Started in Data Science and Analytics. On the day, I had the pleasure of having Joel Stein from Precision Sourcing and his team presenting with me. Also, big thank you to Byron Allen for providing valuable content. Finally, thank you yo Academy Xi for hosting us.
Metrics, Metrics, Everywhere - Choosing the Right Ones for Your Website and S...Brian Alpert
Museums and the Web 2015 workshop includes the analytics process, case studies and a social media framework. Presented by Brian Alpert, Erin Blasco, Effie Kapsalis and Sarah Banks, Smithsonian Institution.
Analytics Tune Up! Google Analytics workshop for beginners, intermediatesBrian Alpert
Workshop presented 6/14/2016 to digital practitioners at the Smithsonian Institution, Washington D.C. Workshop includes:
- Web Analytics Process
- GA Basics
- Exercise: “Solutions Gallery”
- Exercise: Segments
- Exercise: Custom Reports
- Demo: Goals
- Exercise: Dashboards
- New(ish) features
- Universal Analytics
- A few best practices
- A few ‘real world’ questions
You'd like to be more rational and data-driven in your decision making. You know that your museum has been collecting web traffic metrics using Google Analytics, but you've never fully understood what those reports mean for you or your department. How can you use this popular software to find actionable data that helps you do your job better? In this session you will get a practical tutorial, led by two Google Analytics veterans at the Smithsonian, who will provide an overview of the current Google Analytics, including some of its newest, most powerful features. The presenters will also discuss the step-by-step process for moving beyond measurement just for measurement's sake, using real-life museum case studies as examples.
Presenters: Sara Snyder, Smithsonian American Art Museum; Brian Alpert, Smithsonian Institution.
Presented at the American Alliance of Museums 2016 Annual Meeting & MuseumExpo, 5/27/2016.
How much time do you spend mashing up web analytics data vs. looking for data insights? Your Analytics Site automates the data extraction form multiple marketing channels, including WebTrends, Google Analytics, Twitter, YouTube, Slideshare and Flickr with more be added. Each dashboard is customized to satisfy each clients specific business needs. What you get, one cohesive, actionable and visually interactive reporting mechanism for your all your analytics.
It’s Not About Big Data – It’s About Big Insights - SAP Webinar - 20 Aug 201...Edgar Alejandro Villegas
Presentation slides of:
It’s Not About Big Data – It’s About Big Insights - SAP Webinar - 20 Aug 2013 - PDF
Scott Mackenzie - Sr. Director, Platform & Analytics CoE
Michael Golzc - CIO for SAP Americas
Ken Demma - VP, Insight Driven Marketing
20 Aug 2013 - Webcast - http://goo.gl/T74WAL
[DSC Europe 22] The Making of a Data Organization - Denys HolovatyiDataScienceConferenc1
Data teams often struggle to deliver value. KPIs, data pipelines, or ML driven predictions aren't inherently useful - unless the data team enables the business to use them. Having worked on 37 data projects over the past 5 years, with total client revenue clocking at about $350B, I started noticing simple success factors - and summarized those in the Operating Model Canvas & the Value Delivery Process. With those, I branched out into what I call data organization consulting and help clients build their data teams for success, the one you see not only on paper but also in your P&L. In this talk, I'll share some insight with you.
The Softer Skills Analysts need to make an impactPaul Laughlin
25 min presentation given at London Business School, to the OR Society's Analytics Network. Summarising Laughlin Consultancy's 9 step model of Softer Skills for Analysts.
Hosted by MCN Data & Insights SIG co-chair, Elena Villaespesa, this hangout is an introduction to Google Analytics. Brian Alpert, Web Analyst at the Smithsonian will join Elena and show you how to get a handle on this important analytical tool.
Topics covered:
Introduction to digital analytics
Navigating Google Analytics reports
Setting goals and targets
Google Analytics features
Segmentation
Custom reports
Event tracking
Views and filters
Dashboards
Resources & tools
Q&A
Video
https://www.youtube.com/watch?v=kQDCWS4bye4
Whether you are interested in healthcare data analytics or looking to get started with big data and marketing, these fundamental principles from data experts will contribute to your success. http://www.qubole.com/new-series-big-data-tips/
5 Steps To Measure ROI On Your Data Science Initiatives - WebinarGramener
Gramener's Chief Decision Scientist & Co-Founder Ganes Kesari conducted an exciting webinar on how to measure ROI on your data science initiatives.
In this webinar people from the C-suite level CEO, COO, Directors, Managers across various industries joined.
Ganes Kesari covered the following points with industry examples:
-Identifying business use cases with a high impact
-Choosing effective success indicators
-Ascertaining that the consequences may be traced back to your data project
The attendees had a good time. Learnings from the webinar:
-Why do businesses struggle to get a return on their data investments?
-A straightforward framework for calculating the return on investment from your data projects
-Benchmarking of typical payback from data initiatives in the industry
To check out the complete recording of the webinar please visit:
https://info.gramener.com/5-steps-to-measure-roi-on-your-data-science-initiatives
To know more about data advisory check out:
https://gramener.com/advisory-consulting/
Interactive Metrics, What You Really Need to Knowharrisonm10
In this informative presentation, Maria Harrison will take you through the good, the bad and the ugly of interactive metrics. Interactive marketing is a double-edged sword when it comes to metrics.
Just because everything can be counted, doesn’t mean it’s important in making business decisions that will help you have a positive impact on your interactive marketing initiatives.
Ms. Harrison will show you how simplistic interactive metrics can really be, how to set benchmarks, and develop meaningful executive dashboards that will help you make the right decisions to improve your interactive marketing efforts. She will define some basic interactive metric terms and teach you how to immediately apply those metrics to your business.
Data Quality in Data Warehouse and Business Intelligence Environments - Disc...Alan D. Duncan
Time and again, we hear about the failure of data warehouses – while things may be improving, they’re moving only slowly. One explanation data quality being overlooked is that the I.T. department is often responsible for delivering and operating the DWH/BI
environment. What ensues ends up being an agenda based on “how do we build it”, not a “why are we doing this”. This needs to change. In this discussion paper, I explore the issues of data quality in data warehouse, business intelligence and analytic environments, and propose an approach based on "Data Quality by Design"
4. What do you mean, “So what”?
• The typical proxy for website success is quantity of stuff.
– Aggregated “big numbers”
– Pageviews / visits / visitors
• Aggregated data doesn‟t indicate success.
– It doesn't reflect a website‟s efficiency or quality.
– It doesn't reflect a website user‟s experience.
– It doesn't help us understand how to improve the website.
• We can‟t act on this data.
• “All data in aggregate is crap.”
– Google “Analytics Evangelist” Avinash Kaushik
4
5. What web analytics is really about:
Furthering Program Goals
Reuters: Toru Hanai
5
6. Articulating your goals is the hard part
Sometimes your institutional goals:
Aren‟t precisely articulated.
Aren‟t articulated at all (!)
Are too broad to meaningfully measure.
“An institution for the increase and
diffusion of knowledge."
-- James Smithson
Source: Smithsonian Institution Archives
6
7. Your goal: storyteller
Use data to tell a story.
Management loves stories.
The “So what?” factor melts away
because it makes sense:
What was happening.
What it meant.
What you did.
What‟s happening now.
Source: http://www.squidoo.com
7
8. A systematic, step-by-step process
Articulate your program‟s goals.
Decide strategies to achieve those goals.
Decide tactics to pursue the strategies.
Decide what and how to measure:
Benchmark to get a sense of what‟s normal.
The process isn‟t “one size fits all”!
Interpretation and consensus-building are important .
8
9. Start by articulating specific goals
Not too many!
Express what your institution is trying to accomplish.
Distill high-level goals into more specific sub-goals:
“Increase influence” >> “Become the definitive source on
Smithsonian history.”
Making the broad goal specific makes it easier to identify
strategies and tactics.
By being specific, strategies can emerge.
Articulate goals & next steps on your own.
What do you think they are?
Work with management to redefine and finalize.
9
10. Determine strategies & tactics
Strategies – the plans you make to achieve the goals.
Marketing, social media are strategic pursuits.
Tactics – the things you do to advance the strategy.
Advertising, search engine optimization (SEO) are tactics.
Per the example:
Goal: “Become the definitive source on Smithsonian history.”
Strategy: search engine performance.
Rationale: search engines have sophisticated algorithms that
determine which websites are highly relevant, or, "authoritative.“
Tactic: SEO.
Search metrics become proxies for authority.
10
11. Decide how to measure your tactics
Choose a few measurements.
Trend them over time.
Per the example:
Measure: segment history-specific content in GA
Directories (site.edu/history)
Dedicated content (site.edu/historyblog)
Google Analytics custom variables.
Apply SEO metrics to that content:
Number of keywords referred per month.
Number of history pages drawing visits from search engines.
11
12. You can‟t set targets w/o benchmarks
Set targets and timeframes based on benchmarks.
You need at least six months of data.
Data fluctuates; is often seasonal.
Six months is just an opinion.
It also depends on how much traffic your site gets.
Peer data is valuable, but hard to come by.
Balance your targets with factors beyond your control:
Are the improvements you‟re seeking known to be difficult to achieve?
What is the current status of your program (i.e., brand new, mature)?
How much resources will you have to devote to implementing tactics?
12
13. Keep it simple
Don‟t do too much.
Once you‟ve selected your strategies
and tactics, minimize the number of
measurements.
If they turn-out to be inconclusive,
refine or change them!
It‟s an ongoing process.
Source: Matt Groening
13
14. Connecting all that to Google Analytics
You‟ve made progress:
Your goals/strategies/tactics are set.
Your measurements are chosen.
You want to use GA data to understand:
What‟s happening.
How it impacts your program.
What you can do.
Google Analytics Custom Dashboard
Enables segmentation and trending.
Datapoints mostly relate to „engagement.‟
GA Data Grabber
Flexible, Excel-based GA automation tool.
Enables you to see trends better than in the GA U-I.
14
15. GADG Custom Dashboard
„Engagement‟ oriented metrics
Visit Frequency
Visit Length
Visit Depth
New vs. Returning Visits
Bounce Rate
Conversion Rate
Search Engines
A foundation to make data actionable
“Key Trends and Insights”
“Impact on Site/Museum”
“Steps Being Taken”
The easily updated, trended data is
what makes the dashboard powerful.
15
16. Dashboard pages are designed:
1) To help orient you toward action
2) To communicate with management
Red/Yellow/Green
Summary defines status marker
and puts the shows at-a-glance
metric in context each metric‟s
status.
Chart shows „Action‟ section answers
segmented data the question “So what?”
tracked and • Key Trends and Insights
trended over time.
• Impact on Website / Unit
• Steps Being Taken
Profile data pulls
automatically from
GADG; shows
metrics at-a-glance.
Suggestions for GADG
Possible Instructions; show
Additional how to create the
Segments. reports from
scratch.
16
17. GA Data Grabber (GADG)
Extracts data from the
Google Analytics API.
Easy-to-use and customize.
Exceptional charting
capabilities.
14 days free.
$300 per year.
Limited documentation and
support.
Excel for Windows
2003/2007/2010/2011. http://gadatagrabbertool.com
Excel 2011 for Mac (slow!)
17
19. All Visits data tells a nice story...
Key Trends
and Insights
Minimal loyalty
group (purple)
downward trend
indicates
improving content
engagement
High loyalty
group (blue)
upward trend
indicates same
This Impact of this Data on the Site or Program
• This good-looking chart may indicate high content engagement and/or perceived value
• This data may correlate to increasing conversion behaviors
Acting on this Data
• Identify moderate and high loyalty pages as a means of duplicating, or improving others
• Examining conversion behaviors of these segments may yield add'l insights
• Correlating high bounce rate pages to one-time visits may yield add'l insights
• Test different content types in an attempt to move 'minimal' visitors into 'moderate' group
19
20. …But applying segmentation tells a different story
Key Trends
and Insights
Minimal
frequency group
upward trend
indicates organic
listings are not
appropriately
targeted
Moderate
frequency group
downward trend
indicates same
High frequency
group trending
slightly
downward, in
This Impact of this Data on the Site or Program contrast to
• Organic search listings are driving poorly-targeted traffic previous chart‟s
upward slope
• Will result in decreased organic search performance over time
Acting on this Data
• Refocus title tags, meta-description tags and page content for important pages
• Perform link analysis to see where other SEO improvements can be made
20
23. Additional Information in the
Downloadable Presentation:
Additional Case Studies
How to Use GA Data Grabber
More About the Dashboard
Useful GA Practices
Useful Links
23
24. Thanks!
Brian Alpert
Smithsonian Institution
alpertb@si.edu
202-633-3955
24
26. Wikipedia Case Study
One Smithsonian unit worked closely with Wikipedia, incorporating a
range of their content within the online encyclopedia.
The purpose was to make their content more accessible for younger
students, those less sophisticated than the academics and professional
researchers who comprise one of the site‟s core audience segments.
The hypothesis was that by doing so, this group would have their needs
met more quickly and easily, without having to navigate the Smithsonian
website‟s more advanced, research-oriented structure.
The data (shown on the following slides) shows that the needs of the
group referred from Wikipedia – a likely starting point for younger
students – were largely being met by the content posted on Wikipedia.
They were increasingly less likely to need to visit the Smithsonian site
many times.
This is in contrast to the relatively stable trend of the overall population of
visitors shown on the next slide.
26
29. Is the trend statistically significant?
Four of thirteen datapoints
are outside of the upper
and lower control limit
ranges, 30% of the data.
Is that enough to say yes,
that‟s a statistically
significant trend? The
answer is subjective, but
arguably so.
• Control Limits Definition
• Avinash‟s blog post
• „Instant Cognition‟ (Clint
Ivy) blog post
32. Customized GA Data Grabber
Ten custom reports that
work with the Dashboard
Do not rename
GADataGrabber.xlsm !
„Querystorage‟ is unhidden
Change date ranges
Change profile #'s
Change advanced segments
Make changes by hand
Do not change cell formatting.
The „querystorage‟ tab is the key to
editing the dashboard‟s GADG reports.
32
33. Getting Started Click here to synch
The two files that work with GA.
together are:
GaDataGrabber.xlsx (don‟t Clicking „RUN THE The „REFRESH ALL
REPORT‟ does not REPORTS‟ button
rename this one)
refresh the runs the custom
GADG_Custom_Dashboard_ dashboard – it adds dashboard reports.
template.xlsx new reports to
GADG.
Save the files
Don‟t open from an email
From Dropbox, use Save As
Store both spreadsheets
in the same directory.
Find and select your Your GA Profiles.
profile. New GADG Reports
are programmed
Note the Profile ID number here.
on the right.
Profile ID Numbers.
33
34. Run your dashboards!
Login to GA.
Open and login to GaDataGrabber.xlsx
Make sure macros are enabled.
Customize „querystorage‟ with your profile number – row 67.
Refresh all reports.
Open GADG_Custom_Dashboard_template.xlsx
Data should be updated in the dashboard.
Let‟s look at some examples. Select the first profile ID cell
(C67), then click at the top of
the spreadsheet. Edit-in your
profile ID by hand.
Don‟t risk altering the cell
formatting by selecting the cell
and doing copy/paste.
Filling to the right is OK.
34
35. Detail: customizing profile numbers
Altering the cell formatting in
„querystorage‟ breaks the macros.
1) Select cell C67.
2) Click at the top of the
spreadsheet to hand edit your
profile ID number.
3) Filling the rest of the row to
the right is OK.
35
36. Working with GADG
Clicking the big,
green RUN THE
REPORT button
adds new
worksheet-reports to
your copy of GADG.
They are named
“report1”, “report2”,
etc.
They are easily
removed by clicking
the red “Remove
sheet” button on the
worksheet.
36
37. Working with GADG
On the customized
GADG, the all-important
„querystorage‟ tab is
already showing.
If you‟re working from a
clean copy of GADG,
unhide this tab by right-
clicking on the tabs at the
bottom
Select „Unhide‟ and then
„querystorage.‟
37
38. Working with GADG
Editing reports in querystorage:
Advanced segments (rows 19,20)
Custom segment #‟s are
obtained by creating a one-off
report using that segment, and
finding it in querystorage
Dates (rows 26,27,28)
Profile ID numbers (row 67)
############ is normal
You can run reports from the
„Analytics‟ page OR querystorage
Keep track of important
querystorage elements
Profile ID numbers
Segment names and numbers
38
39. Working with GADG
To “save” a snapshot of
your work and continue
experimenting, rename
your GADG files and
Dashboard files.
To ensure the renamed
Dashboard doesn‟t
automatically update,
follow these steps:
Save as
Data
Edit Links
Select the dashboard
you want to save
Execute “Break Links”
39
40. Troubleshooting
Never double-click the files from an email, always „Save-as.‟ Opening from an email
breaks the spreadsheet relationships.
Be sure you‟re logged into GA as yourself.
In querystorage, always edit by clicking at the top of the spreadsheet, and either
editing by hand, or selecting and copying, then selecting and pasting in another cell.
Never select the cell itself and copy/paste. Filling to the right is OK.
Do not change the cell formatting in querystorage; that will break the macros.
Peculiarities can sometimes be attributed to Google‟s API, and not GADG.
Data labeled “(other | other)” sometimes appears – occasionally data has to be hand-
manipulated to get it properly into the Dashboard charts.
Occasionally a blank worksheet remains after refreshing (“report1”) – it can be
deleted.
If you change profiles and re-run a report, GADG occasionally leaves the previous
profile name in the worksheet chart. I removed profile names from the charts, but they
sometimes reappear.
I‟m happy to answer questions, but the real expert is GADG creator Mikael Thuneberg.
Post questions to his Google Group – automateanalytics. He‟s pretty responsive.
40
42. No-filters (raw) profile
Create a profile that has no filtering of any kind, a so-
called “raw” profile
Leave this profile alone – it serves as a backup
Protection against unintended consequence
Possible names:
Unit/profile name (backup)
Unit/profile name (unfiltered data)
42
43. Filter-out internal-traffic
If you want to exclude visitors surfing from within the SI network
Admin >> Profiles >> Filters >> +New Filter >> External Traffic Only
43
44. Measure only traffic taking place on your site
Scraping and re-publishing website content is a common practice.
Those sites exist to serve Google Adsense ads and make money.
Unfortunately they also
scrape your GA “UA”
account number.
Their traffic goes into GA
as your traffic!
Include all domains, if
you use others than
si.edu.
Filter pattern:
si.edu
si.edu|example.com
44
45. Use annotations
Super easy – a great way to know at-a-glance what
happened on your site, launches, promos, etc.
You think you‟re gonna remember – you‟re not!
45
46. Custom segment: social media visitors
The Regex can
also be edited to
include smaller
groups, or types
of social sites,
i.e., facebook
and twitter.
Keeping it up to
date is up to
you!
Regular expression:
bit.ly|bitly|blogfaves.com|blogger|bloglines|blogspot|delicious|digg|facebook|feedburner|flickr|f
oursquare|goo.gl|groups.google|groups.yahoo.com|hootsuite|instagram|linkedin|m.facebook.
com|newsgator|ow.ly|pinterest|plus.google|plus.url.google.com|reddit|stumbleupon|t.co|techn
orati|tweetdeck|twitter|typepad|tumblr|wordpress|youtube
46
47. Custom segment: engaged visits
These visits:
Were
deeper
than three
pages.
Were
longer than
three
minutes.
47
48. Custom segment: highly-engaged visits
These visits:
Were deeper than
four pages.
Were in frequency
more than two
times in the
measured period.
Were longer than
two minutes.
These values can be
tweaked for your site,
of course!
A nice blog post on
this topic is here.
48
49. GA‟s (relatively new) “Social” reports
Make data-driven decisions for social media
programs:
Identify the value of traffic coming from social
sites.
Measure how they lead to direct or “assisted”
conversions.
Understand social activities happening on and off
site.
Some of the reports require programming goals
and assigning values
Understanding „likes‟ and „shares‟ involves
tagging with the _trackSocial tag
Google‟s „social analytics‟ guide
Google‟s „social reports‟ launch blog post
49
50. Social conversions
“Social performance at a glance and its impact on conversions.”
“Which goals are being impacted by social media.”
Requires adding chunks of code to all your pages.
50
51. Social sources
“Find out how visitors from different sources behave.”
This is similar to the custom advanced segment.
Other reports:
• Social Plugins data
• "Activity Stream" (lacks
facebook & twitter)
51
53. Frequency of Visits (“Loyalty”)
Useful engagement metric for
content sites.
Provides insight into how
compelling and/or valuable
content is perceived to be.
Frequent visitors are:
More likely to be loyal visitors
Exhibit higher levels of engagement
than infrequent, and especially one-
time visitors
53
54. Length of Visits
Useful engagement metric for
content sites.
Measures quality based on the
amount of time spent
consuming content.
Segmentation is critical.
Segments of time
Types of content consumed, or
activities pursued.
For example, spending lots of
time searching may indicate a
poor website search
experience.
54
55. Depth of Visits
Useful engagement metric
for content sites.
Number of pages per visit.
Helps understand content
consumption patterns,
which can help paint the
picture of the longer term
relationships visitors have
with the website.
55
56. Segmented Bounce Rate
Number of times a person
visits one site page and leaves
without clicking, divided by the
total number of visits.
Easily misinterpreted as
always negative.
Sometimes a high bounce rate
is desirable or expected.
Visits to single-use
informational pages
(location/hours)
Blog visits
56
57. Goal Conversions – Primary and Secondary
Any high-value behavior that
supports the site's goals.
PDF downloads
Videos watched
Donations
Completed orders
Conversions indicate higher
engagement, deeper commitment
than viewing pages.
"Conversion Rate" is the number
of conversions divided by visitors.
57
58. Resources
GA Data Grabber
http://www.gadatagrabbertool.com/
Automate Analytics Google Group
http://groups.google.com/group/automateanalytics/topics
Avinash Kaushik‟s “Occam‟s Razor”
http://kaushik.net/avinash
Lunametrics blog
http://www.lunametrics.com/blog
Google Analytics Blog
http://analytics.blogspot.com/
Slides and future dashboards will be made available.
Send me email (alpertb@si.edu)
Questions welcome!
58
Editor's Notes
One Smithsonian unit worked closely with Wikipedia, incorporating a range of their content within the online encyclopedia. The purpose was to make their content more accessible for younger students, those less sophisticated than the academics and professional researchers who comprise one of the site’s core audience segments. The hypothesis was that by doing so, this group would have their needs met more quickly and easily, without having to navigate the Smithsonian website’s more advanced, research-oriented structure. The data shows that the needs of the group referred from Wikipedia – a likely starting point for younger students – were largely being met by the content posted on Wikipedia. They were increasingly less likely to need to visit the Smithsonian site many times. This is in contrast to the relatively stable trend of the overall population of visitors shown on the previous slide.
Four of thirteen datapoints are outside of the upper and lower control limit ranges, 30% of the data. Is that enough to say yes, that’s a statistically significant trend? The answer is subjective, but arguably so.
An additional datapoint to support the previously stated hypothesis. The group referred by Wikipedia was increasingly less likely to need to ask the Smithsonian staff for help via the site’s contact form. In addition to indicating that the Wikipedia-referred audience was finding the content it needed on Wikipedia, the project resulted in a reduced burden on the Smithsonian staffers who attend to these requests. The same datapoint for two other referral segments are shown, returning visitors, and visitors from search engines, showing marked contrast with the Wikipedia segment.