Measuring Digital Success with Web and Social Analytics

© Rich Gordon 2014

What Gets Measured Gets Done: Web and Social Analytics for Publishers

Knight Digital Media Center – April 2014

Rich Gordon @richgor

© Rich Gordon 2014

The problem for publishers

•  Lots of metrics: What should we keep track of? •  Publishers have unique measurement needs

© Rich Gordon 2014

What all businesses need: Key Performance Indicators

Use of “Key Performance Indicators” in books 1990-2008

Source: books.google.com ‘ngram viewer’

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008

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Propositions for today •  Every publisher should have a set of KPI’s that

are tracked consistently and regularly – align to business goals (can be different for every

publisher) – should be shared internally – can be factored into personnel decisions

•  Make a spreadsheet, update monthly •  Compare to last month, same month last year,

year over year, YTD this year vs. previous years

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•  The most popular Web metrics toolkit •  Easy to set up, free to use •  Built more for direct marketers than

publishers – “acquisitions” and “conversions”

•  Constantly being modified by Google

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What do publishers need to track?

•  Scale: How big is our audience? •  Loyalty: How likely is our audience to

come back? •  Engagement: Once on the site, how

engaged is the audience with our content?

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Seven top-level metrics: Which ones matter?

•  Which metrics are best for measuring audience over time? –  Size/scale –  Loyalty –  Audience engagement

Audience | Overview

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User clicks on link,

requests page

Content server

delivers page

Ad requests go to

ad server

To understand online metrics, consider how the technology works

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Your browser assembles files, presents them to the user as a page

Each server that delivers a file (HTML page, image, ad banner, Google Analytics code) can also deliver a “cookie”

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So … what’s a cookie?

•  A small text file saved to your computer

•  In concept: benign –  Only the site that served you the cookie can access it –  No personal information is stored in the cookie

•  Cookies exist because HTTP protocol is “stateless,” and provide real utility

•  They also enable the server to recognize you’re the same computer that did something previously

.google.com TRUE / FALSE 2147368450 PREF ID= 3205648b2ceffdf1:TM=1001091062:LM=1001091062

© Rich Gordon 2014

Google’s vocabulary keeps changing

•  Unique Visitors è People è Users •  Visits è Sessions •  Time on Site è Visit Duration è

Session Duration

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Audience vocabulary, for starters

•  Users (Unique Visitors): The total number of unique persons visiting a Web site at least once in a time period (usually one month). Persons visiting the same site more than one time in the period are counted only once.

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browsers visiting

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•  Session (Visit): A continuous series of URL/page requests. A gap of 30 minutes between URL requests ends a session/visit.

•  Pageviews: The total number of times a Web page is requested by a user. Counted only when page fully loads in browser window.

•  Bounce Rate: Portion of sessions that are exactly one page view.

browsers visiting

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Unique visitors vs. visits (GA: Users vs. sessions)

•  Remember that what’s really being counted here is cookies

•  A session (visit) happens any time the server delivers a new cookie or reads an existing cookie on the user’s computer.

•  Users (unique visitors) are counted each time a cookie to a new user/computer (or a user/computer the server believes is new)

•  A new visitor is a computer/browser that has not been seen before in the selected time period (a week, a month, a year, etc.)

© Rich Gordon 2014

Users or unique visitors: Totals are getting worse and worse •  Every browser on every device has its own

cookies •  To Google Analytics, in a given month, I could be

as many as 12 users: – Chrome and Firefox on my work laptop – Chrome and Firefox on my home laptop – Chrome and Firefox on my iPad – Safari and Chrome on my iPhone – Occasionally, Safari and Chrome on my son’s Mac – Occasionally, Chrome and Firefox on my wife’s PC – And that doesn’t count shared classroom computers

© Rich Gordon 2014

Questions so far?

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Among basic metrics, track …

•  Size/scale: SESSIONS (visits) •  Loyalty: % RETURNING

VISITORS •  Engagement: PAGES/SESSION

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Another metric for measuring loyal vs. infrequent visitors

Audience | Behavior | Frequency & Recency Over 1 year: •  % of sessions

by Fly-Bys (1-2 sessions)

•  % of sessions by Regulars (51+ sessions)

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What about the other metrics? •  Pageviews: Easily manipulated – can reward

site practices that users hate – Articles spanning multiple pages, slideshows, etc.

•  Bounce Rate: More appropriate for direct marketing campaigns, but worth tracking – strive for improvement over time

•  What about Average Session Duration (previously Time on Site or Visit Duration)?

© Rich Gordon 2014

http://www.kaushik.net/avinash/2008/01/ standard-metrics-revisited-time-on-page-and-time-on-site.html

The problem with visit duration: How it’s calculated

The last page of any visit counts as zero duration!

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Where does site traffic come from?

Acquisition | Overview

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Where does site traffic come from? Search from Google, etc.

Type URL or bookmark

* From Twitter, Facebook, Tumblr, etc.

Links from other sites

Other

Clicks from email clients

Paid ads on Google, etc.

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Referring sessions (visits) from social media

Percentage of referral sessions (and all sessions) driven by:

–  Facebook –  Twitter –  Reddit –  Disqus –  LinkedIn –  Blogger –  etc.

Acquisition | Social | Overview

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For social visits, also look at the “Other” category

Acquisition | Overview | Channels | Other For many sites, the largest “other” referrers will be services that publishers use to distribute headlines via social media.

Consider counting these as social media referrals

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Which referrals are most valuable: Pages/session by source

Compare pages/session from specific referring sites: •  Google •  Facebook •  t.co (Twitter) •  other sites

Acquisition | All Referrals

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Percentage of sessions starting on home page

Direct visitors (most start on home page) view: •  6x as many pages/session as Facebook visitors •  5x as many pages/session as search visitors

Behavior | Site Content | Landing Pages

http://www.journalism.org/2014/03/13/social-search-direct/

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Behavior | Site Content | Landing Pages

Engagement: Sessions starting on home page

•  Visitors arriving on the home page should view more pages and not “bounce”

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Engagement: Phone vs. tablet vs. computer

•  Pages/session for mobile & tablet will likely be lower •  Mobile-friendly (“responsive”) design should reduce this

difference •  Can drill down to specific devices

Audience | Mobile | Overview

© Rich Gordon 2014

Can you improve your metrics? Some ideas

Goal Tactics

Scale More sessions

•  Increase social media activity •  Build traffic-building partnerships •  Improve SEO

Loyalty More returning visitors

•  Add email newsletters •  Increase social media activity

Engagement More pages/session

•  Better navigation •  Display links to more content (especially

related content) on article pages

Mobile engagement More pages/session

•  Use “responsive design” approach so your site is more usable on phones/tablets

© Rich Gordon 2014

Useful Facebook metrics •  Growth in “likes” – month over month, vs.

same month last year •  Likes per 1,000 sessions •  Total reach (people who saw your posts)

– by day, week, 28-day period •  Engaged users (share, like, click, comment)

– by day, week, 28-day period

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Useful Facebook metrics •  Engagement rate (formerly “Virality”): Engaged

users / Total reach – By week, 28-day period

•  Click rate: Post clicks per total reach – By week, 28-day period

•  Share rate: Post shares per total reach – By week, 28-day period

•  Comment rate: Post comments per total reach – By week, 28-day period

© Rich Gordon 2014

Social media: Twitter

•  Followers •  Growth in followers •  Followers per 1,000

sessions •  Retweets per week •  Retweets per month

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Social media: Twitter

Follower : following ratio •  High: Many people are listening to you

– Using Twitter mostly for distribution

•  Low: Youre listening to many people

– Using Twitter to monitor your community

© Rich Gordon 2014

What could we learn if metrics were aggregated for many sites?

•  Sites that outperform could be examined to understand what they were doing differently

•  Northwestern journalism/computer science team is prototyping a benchmarking tool

•  Share your metrics with us (and no one else) by filling out this survey:

http://bit.ly/pbenchmark

© Rich Gordon 2014

Thank you!

[email protected] @richgor

Help us prototype a benchmarking tool Share your metrics with Northwestern team

(and no one else) by filling out this survey:

http://bit.ly/pbenchmark

Measuring Digital Success with Web and Social Analytics

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