The document discusses key performance indicators (KPIs) that publishers should track to measure their online performance. It recommends tracking visits, new visits as a percentage of total visits to measure loyalty, and pages per visit to measure engagement. Other proposed KPIs include traffic sources like search, referral, social media and the number of pageviews from each. Social media metrics like followers, likes and engagement on Facebook and Twitter are also important. Consistently measuring and aligning KPIs to business goals can help publishers improve online performance over time.

1. © Rich Gordon 2013
What Gets Measured Gets Done:
Web and Social Analytics for Publishers
Local Media Association – May 15, 2013
Rich Gordon
@richgor

2. © Rich Gordon 2013
The problem for publishers
• The Web: “the most measurable medium ever”
• We are awash in measurement data
• What should we keep track of?
• Publishers have unique measurement needs
Use of phrase “Key Performance Indicators” in books 1990-2008
Source: books.google.com ‘ngram viewer’

3. © Rich Gordon 2013
Key Performance Indicators
for publishers
• Based on three years of classes in which I
had Medill students examine “networked
audience development practices” – and
metrics – for locally focused websites:
– Links & content referrals
– SEO
– Social media
• Based mostly on Google Analytics
• A work in progress – I welcome your
feedback

4. © Rich Gordon 2013
Propositions for today
• Every publisher should have a set of KPI’s
that are tracked consistently and regularly
• These KPI’s should be shared throughout the
organization
• Performance on KPI’s should be factored into
personnel decisions
• KPI’s should align to business goals – they
will be different for every publisher

5. © Rich Gordon 2013
Data point: Nielsen Net/Ratings counts
4,600 news & information websites
• Top 7% of
sites (300) …
… get 80%
of traffic
Source: http://stateofthemedia.org/2010/online-summary-essay/nielsen-analysis/

6. © Rich Gordon 2013
Why are category leaders
so dominant?
• Network effects from links, search, social
media: “the rich get richer”
• Networks tend to produce “power law
distributions” of attention
• The “80/20” rule: A small fraction of the
total number of nodes in the network
gets a disproportionate share of the
attention

7. © Rich Gordon 2013
Basic metrics
• Which of these metrics is best for
measuring audience over time?
– Size/scale
– Loyalty/frequency
– Audience engagement

8. © Rich Gordon 2013
User clicks
on link,
requests page
Content
server
delivers page
Ad requests
go to
ad server
To understand online metrics and audiences,
consider how the technology works

9. © Rich Gordon 2013
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”

10. © Rich Gordon 2013
Audience vocabulary,
for starters
• Unique Visitors (Unique Audience): 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 reporting period are
counted only once.
• Visit (Session): A continuous series of URL/page
requests. A gap of 30 minutes between URL requests
ends a session/visit.
• Page views: 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 visits that are exactly one page
view.
computers visiting

11. © Rich Gordon 2013
Unique visitors vs. visits
• Remember that what’s really being counted here
is cookies
• A visit happens any time the server delivers a
new cookie or reads an existing cookie on the
user’s computer.
• 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 given time period
(typically a month)

12. © Rich Gordon 2013
Among basic metrics,consider …
• Size/scale: VISITS
• Loyalty/frequency: % NEW
VISITS
• Audience engagement:
PAGES/VISIT

13. © Rich Gordon 2013
Problems with other metrics
• Unique visitors: Each browser has its own
cookies!
– Users with four browsers on one computer – or a
work PC, home PC, tablet and smartphone – are
counted as four separate visitors.
• Pageviews: Easily manipulated – can reward
site practices that users hate
• Bounce rate: More appropriate for direct
marketing campaigns ... but strive for
improvement over time

14. © Rich Gordon 2013
The problem with ‘unique visitors’:
a newspaper example
Unique visitor
numbers look
impressive …
Source: “The Story So Far: What We Know About the
Business of Digital Journalism” (Columbia U. / Tow Center 2011)

15. © Rich Gordon 2013
… but most users
don’t visit very often
Number of visits per month
1 2 3-6 7-9 10+
Source: Nielsen Company and PEJ Research

16. © Rich Gordon 2013
Newspaper example:
core users drive vast majority of traffic
Source: “The Story So Far: What We Know About the Business of Digital Journalism” (Columbia U. / Tow Center 2011)
(>2 visits/week)
(1-2 visits/week)
(2-3 visits/mo.)
(1 visit/mo. or
less)
25% of the visitors
generate 80%
of the page views
Page views
per mo.
143
31
10
3

17. © Rich Gordon 2013
The real size
of the core, loyal audience
Source: “The Story So Far: What We Know About the
Business of Digital Journalism” (Columbia U. / Tow Center 2011)

18. © Rich Gordon 2013
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

19. © Rich Gordon 2013
Visit duration with browser tabs:
How it’s calculated
http://www.kaushik.net/avinash/2008/01/
standard-metrics-revisited-time-on-page-and-time-on-site.html

20. © Rich Gordon 2013
Where does site traffic come from?
Search, links, social media

21. © Rich Gordon 2013
Where does site traffic come from?
• Search: from
Google, etc.
• Referral: links on
other sites
• Direct: type URL
or bookmark
• Campaigns: you
define in GA;
often an e-
newsletter
Traffic Sources | Overview

22. © Rich Gordon 2013
“Branded visits”:
Direct + search for <sitename>
• A significant share
of search-driven
visits are really
direct visits “in
disguise”
• Add these to
Direct, deduct
from Search
Traffic Sources | Sources | Search
Overview | Keyword

23. © Rich Gordon 2013
Referring visits
from social media
• Percentage of
referral visits (and
all visits) driven by:
– Facebook
– Twitter
– Other social
sources
Traffic Sources | Sources | Referrals
Social | Overview

24. © Rich Gordon 2013
Which referrals are most valuable:
Pages/visit by source
Traffic Sources | Sources | All Traffic
Compare
pages/visit from:
•Direct
•Search
•Social media
•Other key
referring sites

25. © Rich Gordon 2013
Engagement:
Visits starting on home page
• Visitors arriving on the home page
should view more pages and not
“bounce”
Content | Site Content | Landing Pages

26. © Rich Gordon 2013
Engagement:
Mobile vs. computer
• Pages/visit for mobile will likely be lower
• Mobile-friendly (“responsive”) design should
reduce this difference
• Can drill down to specific devices (phone vs
tablet)
Audience | Mobile | Overview

27. © Rich Gordon 2013
Social media:
Facebook Insights
• Total reach: People who have seen any
content associated with your page
• People talking about this: People who have
created a “story” (like, comment, share,
answer question, respond to event)

28. © Rich Gordon 2013
Social media:
Facebook Insights
• Engaged users: People who have clicked on
your post
• Virality: People talking about this divided by
total daily reach

29. © Rich Gordon 2013
Social media:
Facebook Insights
• Likes
• Growth in likes
• Likes per 1,000
visits
• Over 28 days:
– Engaged users
– People talking
about this
– Virality

30. © Rich Gordon 2013
Social media:
Twitter
• Followers
• Growth in followers
• Followers per 1,000
visits
• Retweets / month

31. © Rich Gordon 2013
Social media:
Twitter
Follower : following ratio
•High: Many people are
listening to you
– Using Twitter mostly
for distribution
•Low: You’re listening to
many people
– Using Twitter to
monitor your
community

32. © Rich Gordon 2013
Social media:
“Influence” scores
• Klout
• TweetLevel
• PeerIndex
• Many others
Each seeks to
measure your
“influence” on
social media
channels

33. © Rich Gordon 2013
Thank you!
richgor@northwestern.edu
@richgor