Click Here For Customized DataGoogle Analytics Automated Dashboard

and Case Studies

MW 20134/20/2013

Brian AlpertWeb Analytics and SEM Analyst

Office of the CIO

Smithsonian Institution

Effie KapsalisHead of Web & New Media

Smithsonian Archives

Smithsonian Institution

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Topics• Web Analytics Process• GA Data Grabber• Data Grabber Dashboard• Case Studies• Dashboard copying for attendees

Web analytics 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

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GA Data Grabber (GADG) Extracts data from the Google Analytics

API Easy-to-use and customize Exceptional charting capabilities Commercial product

14 days free $300 per year

Limited documentation and support Excel for Windows

2003/2007/2010/2011 There are other GA automation tools GADG was chosen for its ease of use

and charting http://www.google.com/analytics/apps/result

s?category=Reporting%20Tools

http://gadatagrabbertool.com

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Data Grabber Dashboard ‘Engagement’ 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

makes the dashboard a powerful tool.

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Case Studies

Smithsonian Archives Smithsonian-History Goal

One of SIA’s goals: “become the definitive source on the Smithsonian’s history”

History content was segmented Compared visit-depth for ALL web

visitors to HISTORY visitors Data for high-visit-depth segment

was remarkable Percentage of HISTORY visits

was 94% higher than ALL visits 1.21% average for ALL visits 2.35% average for HISTORY visits

History-content visits

All visits

Smithsonian Archives Women’s History Month Campaign

Month-long, image-focused, crowdsourcing/outreach campaign

Pinterest, Facebook, Tumblr

Goal: attract / engage audiences with “women in science” collections

Compared all visits vs. “WHM social” visits for moderate / high visit frequency segments

Social media website visits are "streaky" – they reflect daily activity

WHM segment exhibited higher percentages of moderate (2-9) and high (10+) visit frequency

Peaks as much as 2-4X higher

Referral traffic from the targeted social media sites increased by 52%

WHM ‘social’ visits

All visits

WHM ‘social’ visits

All visits

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Archives of American Art / Wikipedia Collaboration

AAA wanted to make their content more accessible to younger students

They worked with Wikipedia to expand their offerings

We compared segments of Wikipedia visitors to other visitors

Wiki-referred visitors were increasingly less likely to (need to) visit the AAA site many times

This contrasts with the stable trend of all visits

All visits, high frequency

Wikipedia visits, high frequency

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Archives of American Art Wikipedia Case Study

Wikipedia-referred visitors were less likely to ask Smithsonian staff for help via “contact us”

Reduces the burden on Smithsonian staffers

The same datapoint for two other segments is shown Returning visitors Visitors from search engines

Returning visitors

Wikipedia visitors

Visitors from search engines

Backup

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Is the trend statistically significant?

• Control Limits Definition• Avinash’s blog post• ‘Instant Cognition

’ (Clint Ivy) blog post

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.

All Visits data tells a nice story...

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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

Key Trends and Insights

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This Impact of this Data on the Site or Program• Organic search listings are driving poorly-targeted traffic• 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

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 contrast to previous chart’s upward slope

Key Trends and Insights

…But applying segmentation tells a different story