social-media-analysi.. - Webmetricsguru INC – Marshall Sponder

Social Media Analytics Proposal for Monster Worldwide
Marshall Sponder
Monster Insights
12/10/08
Table of Contents
Social Media Analytics Proposal for Monster Worldwide ................................................. 1
Table of Contents........................................................................................................ 1
Part 1: Social Media Reports we can do or could be doing –............................................. 3
IPhone Apps Tracking ................................................................................................ 3
Facebook Apps tracking ............................................................................................. 4
Develop – Track GPhone apps for Monster jobs........................................................ 4
Tracking Blogs mentioning CareerBuilder/Monster/Hotjobs..................................... 5
Blog Traffic from Blogs (Comparison) ...................................................................... 6
Youtube tracker........................................................................................................... 7
How many Micro job sites have implemented services like Jobamatic.com?
(129,000 on December 9th, 2009?).............................................................................. 9
Monitor Traffic from job aggregation sites vs. regular partner traffic vs.
Google/yahoo/msn .................................................................................................... 10
Monitor how much traffic comes from business social networks like Xing or
LinkedIn (the big two) .............................................................................................. 10
Determine and monitor how classified sites like oodle, craigslist, backpage.com can
be utilized to drive traffic to monster........................................................................ 10
What could monster do with "smaller" social networks such as high5, netlog, orkut,
Friendster and local Facebook clones like studivz.de in Germany? ......................... 10
Use Monster Employees to Crowdsource Social Media responses; get in touch with
bloggers - measure Brand Uplift using traffic and quality score metrics in Visual
Sciences..................................................................................................................... 11
Use Eric Peterson’s Engagement Score mapping - recently ported into Visual
Sciences (by Nikolay) to measure Visitor Engagement. .......................................... 13
Monitor Jan 10th launch and subsequent reactions (via Radian6, CI) on Twitter,
Facebook Superbowl ad promo and reactions to it................................................... 14
We can use Comscore to Measure Conversational Media to Monster and its
Competitors............................................................................................................... 16
Measure Engagement by Frequency and Duration of Visits .................................... 17
We can use WebTrends Profiles to for Data mining – they now include Geo Data
from Cities (proxy DMA’s) that were not available before we upgraded –these can
be lined up with Comscore ....................................................................................... 18
Part 2: Towards a Social Media Dashboard...................................................................... 20
Component parts ....................................................................................................... 20
Web Traffic............................................................................................................... 20
Rollup of Monster Worldwide? No doable at this time........................................... 21
Social Media Traffic ................................................................................................. 22
Classify Site Referral Traffic by the following criteria: ........................................... 22
1
2. Use the same table, created in step 1, for Social Media Conversions .................. 23
3. Calculating ROI of Social Media.......................................................................... 26
Mobile Traffic........................................................................................................... 27
Search Engine Data................................................................................................... 28
Part 3 – What we’ll need................................................................................................... 31
Comscore .................................................................................................................. 31
Visual Sciences ......................................................................................................... 31
WebTrends................................................................................................................ 31
Social Media Buzz Monitoring................................................................................. 32
Summary ........................................................................................................................... 32
2
Part 1: Social Media Reports we can do or could be
doing –
IPhone Apps Tracking
1. WebTrends Profiles are now able to track mobile traffic – but not as well as
they could be (Note: Unless the WebTrends system administrator has configured
the profile to track visitor IDs, visit counts can be inaccurate. This is because
WAP devices connect to the Internet through a gateway server; therefore, the
number of visits counted in the log file will reflect visits by gateway servers,
rather than individual visitors.)
2. We can track IPhone usage as a browser type (see Monster US Profile –Browsers
and Systems – Platforms)
.
3. There are reports for Palm like devices and Blackberrys –under the WAP Browser
settings – since many people use BlackBerry that can be tracked as well.
I think we need to define what we’re going to track around wireless and why –
right now the numbers are fairly low.
3
We could count Mobile traffic as a component of a Dashboard – we can pick out
devices by screen resolution if we know the screen resolutions that go with
different mobile devices.
Facebook Apps tracking
4. There are a few applications that Monster Worldwide has on Facebook that we
could track – MonsterTrak has one, there may be others I’m not aware of.
a. Use site referral logs in VS and WT to track traffic from Facebook (better
done in VS) Use Quality Scoring, similar to what we did for Clay Fisher
last week – tie in with MH data joined with VS.
b. Acknowledge / Adonomics application tracking
Develop – Track GPhone apps for Monster jobs
5.
Encourage development of such an application and track it in VS – can also be
tracked using WebTrends 4
Tracking Blogs mentioning CareerBuilder/Monster/Hotjobs
6. Easiest way is via Radian6 or Collective Intellect Profiles – we have test accounts
on both at this time. (We can also get daily alerts mailed to us which are easier
to digest and respond to – see #19).
7. We can come up with influential for a set profile (keywords phrases) here’s one
for Monster Worldwide profile I set up in Radian6 recently:
5
We can also datamine the information and there are several additional views which
could be useful – esp. if we can combine with Search Data – both external and
internal.
Blog Traffic from Blogs (Comparison)
8. Worked with Breanna Wigle at Military.com, earlier this year, in identifying sites
that were Social Media (blogs, message boards, micro blogging, photo sharing
sites, social networks) and qualifying the conversion rate, time spent on site, etc.
We could do this with Monster.com, most effectively via Visual Sciences.
a. Take the monthly referrer list – qualify it for Social Media, classify it (is it
a blog, a social network, a photo sharing site, a message board, a micro
blogging site?) and maintain a master lookup table in a database or Excel
– then use it (keeping it up to date each month) to qualify Social Media
traffic to Monster properties.
b. I’ve done similar types of projects, freelance, for others – and it’s quite
revealing and helpful – esp. if we can tie in conversions – this begins to
develop an ROI case for Social Media,
c. As Web Analysts – our approach differs from Communications and
Marketing in that we’re trying to tie Social Media to a site, a visitor
metric, a Conversion – whereas – the Buzz monitoring tools – work more
on Sentiment and Share of Voice – but there’s room for overlaying that
data and coming up with useful insights that helps Monster shine over it’s
competitors.
6
Youtube tracker
9. YouTube Tracking against Monster Profiles (we would have to set them up –
input could come from Search Stakeholders, Corporate and PR/Legal) is best
done with a tool like Radian6.
Yields this
7
a. we could crowd source the viewing of these videos, classify them
(positive/negative) from within our Monster Insights Group – decide to
respond or not – and put the numbers in a Social Media Dashboard to be
presented to Corporate on a regular basis (Weekly/Monthly) – and where
there are Product Launches – monitor and classify those as well – put time
lines in our charts and monitor response.
8
b. You can also look at Videos in a timeline by using a different Widget,
click a period of time, see all the YouTube and similar type videos – view,
classify and count (and flag for response, by Corporate, if they want to
respond).
How many Micro job sites have implemented services like
Jobamatic.com? (129,000 on December 9th, 2009?)
In order to qualify both the threat to Monster Worldwide that Jobamatic (via Simply
Hired) poses we can go about it in a few ways
10. Search on Google that is executed regularly and counted – in this case, today it’s
14,800 urls being indexed –assuming they are de-duplicated – that’s that many
sites that are out there, taking job listings away that Monster could also have – if
it rolled it’s own version of Jobamatic.
IE: http://www.google.com/search?hl=en&q=*.jobamatic.com&btnG=Search
11. However, a better search in Google would be
http://www.google.com/search?hl=en&q=%22Jobs+powered+by+Simply+Hi
red%22&btnG=Search - here we’re searching on "Jobs powered by Simply
Hired" and come up with 129,000 instances of Jobamatic! We could set up a
Job Alert in Google to track each day – put the number of urls – qualify the value
of a typical job listing – and a typical job rate, average over the 129,000 came up
with a number of listing Monster is losing to Simply Hired via Jobamatic – that
we cold reclaim with our own site.
12. We could use Radian6 or Collective Intellect for the same thing and also produce
a timeline chart if we can get the profile to work properly to isolate
.jobamatic.com jobs “"Jobs powered by Simply Hired", etc.
13. We can also use Comscore to monitor Jobamatic and SimplyHired
9
Monitor Traffic from job aggregation sites vs. regular partner traffic
vs. Google/yahoo/msn
14. We’d identify traffic from Search Engines and vs. Traffic from Monster
Subsidiaries vs. traffic from Indeed, SimplyHired. Why would we do this?
a. Determine where we get the most value (use VS. for Quality Scores)
b. Proactively determine when aggregator traffic is leaving Monster and
pointing somewhere else – say at CareerBuilder.
Monitor how much traffic comes from business social networks like
Xing or LinkedIn (the big two)
15. This is best done in Visual Sciences where we can also gather Quality Scores –
right now (I just checked) there’s nothing from Xing and little from LinkedIn,
however.
Determine and monitor how classified sites like oodle, craigslist,
backpage.com can be utilized to drive traffic to monster.
16. We could try measuring the impact of Oodle working with Facebook and
MySpace marketplace using Comscore Source Loss Report – create a Trend line
by pulling up to 15 months of data – use Unique Visitors – can also use Reach
and Pages per Visitor.
UV (000) Traffic coming to Facebook from Oodle – Oct 08
3793
[P]
Oodle
9
UV (000) Traffic coming to Facebook from Oodle – May 08
Oodle
14
UV (000) Traffic leaving Facebook to Oodle – Oct 08
3151
[P]
Oodle
10
UV (000) Traffic leaving Facebook to Oodle – May 08
Oodle
13
What could monster do with "smaller" social networks such as high5,
netlog, orkut, Friendster and local Facebook clones like studivz.de in
Germany?
17. At this time I would look at Source Loss data from Comscore for each network –
tracking if traffic is going up/down to Monster – and why – as part of a
dashboard.
18. Could Ning, KickApps be leveraged to drive high quality niche traffic? At this
time, it’s possible for Monster to leverage branded Social Networks.
10
Use Monster Employees to Crowdsource Social Media responses; get
in touch with bloggers - measure Brand Uplift using traffic and quality
score metrics in Visual Sciences.
19. In many cases, there are opportunities to respond to questions, issues, problems
on the Web that can further Monster’s Brand and Good Will immensely. Up to
now, we rarely responded, or did so, belatedly. I’m suggesting we monitor and
respond proactively and immediately (within 24 hours) – and Crowdsource the
response mechanism to Monster Insights and other teams from within the
company. True, it’s not Monster Insights’ job to respond, BUT, it’s almost
impossible to see how anyone else but MI could respond in a timely way – since
HR, PR, Marketing, would not, often, have access to the data. By the time they
could get it and decided how they wanted to respond – it would be too late to
respond – and doesn’t really fit into the Social Media model of transparency.
a. Here’s an example of issues, questions and problems picked up on
December 8th (evening) for Monster.com profile in Radian6 and emailed
to me the following day (December 9th, early). I can forsee responding to
there kinds of question – everyday, and tracking the responses and any
traffic/sentiment improvement (correlate with dollars gained) at Monster.
b. It might be we don’t have anyone, or the right people, able to “marshall”
the information – or they’re afraid of legal issues with– which make it
next to impossible to respond in any kind of timely manner. Maybe we
need a “dispatcher” to review and assign –using a ticketing system (but
not ClearQuest – it’s too cumbersome) – tracking both the responds and
the customer sentiment resulting from creating dialogs where there were
none, before.
Getting the Best Computer Software Training
I was surfing Monster.com and CareerBuilder.com just last night and spotted a
number of job opportunities that specified computer software training. If you stop
to think about it, this is not bizarre in any way. How many computers do you think
there are in use on any given day? I would wager that there are quite a few.
Lacking history? Try LinkedIn
Get linked If you've never heard of LinkedIn before, it's the monster.com of
social networking. Think of it as MySpace for resumes. (we could have
responded to that - tell them what we're launching in Jan 10th, etc).
A chance to see the world ... or not
I have a saved "search" with Monster.com. Every week or so, they send me an
email with possible jobs that I might be suited for. I have applied for a few. One
yielded an interview last week, so we'll see what happens with that (hey, don't
we need some positive press - why don't we ask him if we can quote him - of
course, the rest of the post - I'm not too sure about)
11
Online Demand For EU Workers Below Year-Ago Levels Monster (The Forex Market)
LONDON (Dow Jones)–Online demand for workers in the European Union fell in
annual terms in November for the first time in the history of the employment
survey conducted by Monster Worldwide Inc. and published Tuesday. (there's
an opportunity to comment - but we'd have to get the right information from our
site)
TWEET FROM: CHRISPOWELL
Source: twitter.com, Posted on: Dec 08, 2008 10:02 PM
@jakrose I haven't, have had some interviews from Monster.com (This guy is
fairly well known on Twitter )
Tribune Co. files for bankruptcy . We had a surefire business model
for about a century and then the Internet and other developments disrupted it.
We’ve lost all kinds of classified advertising to Craigslist and all kinds of
employment advertising to Monster.com. The big department stores have
consolidated and buy many fewer full-page ads. (here's a mainstream media blog
we could have posted a comment in - Brand Awareness starts going way up =
Monster Cares.
Laid Off - Day Five: More Networking and Job Searching
. I’ll
have some networking opportunities which may lead to a job. I’ll gain valuable
experience that will improve my skill set and résumé. It’ll get me out of the house!
Job Searching I continued to search for job listings on Monster.com and some
local job boards. I’m not having much luck finding jobs in finance-related fields,
which is what I expected given the current market and economy. It could take a
while to find another job in financial planning, but I’m going to keep looking for a
while. In the meantime, I’ll continue to work on Crackerjack Greenback and
explore my other options. (wish we'd respond with some helpful tips on how to
use Monster.com - stuff that's coming up next year to help the job searcher).
TWEET FROM: EXIVA
Source: twitter.com, Posted on: Dec 08, 2008 06:13 PM
Browsing monster.com for a tech job on Long Island... if anyone knows of any
openings.. Let me know :)
TWEET FROM: JBELL2
Source: twitter.com, Posted on: Dec 08, 2008 05:33 PM
@jigitz fastweb.com. sign up, and itll give you a lot of scholarships that you're
eligible for
TWEET FROM: HTXLISAKATE
Source: twitter.com, Posted on: Dec 08, 2008 05:05 PM
i was just told to "not take it personally". oh, okay. then i hope you dont take my
being on monster.com all day personally either.
The Real Way to Get a Job Using Social Media Revealed
Source: personalbrandingblog.wordpress.com, Posted on: Dec 08, 2008 08:01 AM
12
I’d also recommend that you ensure your resume is on Monster.com,
eRecruiting.com and Careerbuilder.com, in addition to JobFox.com and
Jobster.com. 3. Sleeping is not an option I’ve talked about how sleep is an
opportunity cost in a web 2.0 world. Sleep is unnecessary if you’re in a job
search because every hour you don’t have a job, that’s money you can’t use to
support your life. Instead of sleeping for 8 hours every night, why not try 5 or 6.
Use Eric Peterson’s Engagement Score mapping - recently ported
into Visual Sciences (by Nikolay) to measure Visitor Engagement.
20. Nikolay was able to add Peterson’s Engagement Indices into VS, but I can’t find
them – however, I would think they’d belong under the Extended Dimension
menu
Note: it’s likely that Nikolay has the “engagement mapping” examples in the VS QA
environment – I can’t get into it right now – License issue.
13
If we could have a report that lays out the dimensions much in the way Peterson
envisions them in his writings –that would help a lot – all of us – we could then do a lot
with these reports – for example:
URL
Search.aspx Total Score 2.7
Getajob.aspx Total Score 2. 6
Etc.
3 | 4 | 2.5 | 3 | 0 | 1.5 | 3
3 | 4 | 2.0 | 3 | 0 | 1.0 | 3
And here are other applications of Peterson’s formula we could translate into VS
http://ebiz2.byu.edu/analytics/content/track-visitor-engagement-using-google-analytics
We have the raw information, but we don’t necessarily have it organized in a way that
makes it easy to pull, easy use, or easily accessible for MI group to use for their own
reports with their own stakeholders.
Maybe that’s something we ought to focus on right after Redux launches – because we
can use this kind of report to enhance many of our deliverables.
Monitor Jan 10th launch and subsequent reactions (via Radian6, CI)
on Twitter, Facebook Superbowl ad promo and reactions to it.
21. I have access to Collect Intellect’s Media Intellect Beta for a period of time – they
want my ideas on how to improve the product, in general – not related to Monster
in particular, – I’ve asked them to set up a Monster Profile so I could use it in
conjunction with my work here
14
I’m envisioning possibilities where we can pull the data from CI and use it for Ranking
Reports and in VS – to see how that traffic is interaction on our site – and then tie it back
to the Scatter Charts that are produced by CI.
For example, we’d determine if the keywords as identified in Social Media generate more
“engaged” visitor than those that are not from Social Media – we’d look at Quality
Scores from VS, as well, as defined by Clay Fisher (time spent by keyword Job Searches,
Job Views, etc). For example – terms such as “Search Powerhouse”, “home
opportunities”, “employment opportunities” have higher quality scores than key
phrases that aren’t being picked up in Conversations.
November 08
work at home opportunities for nurses
employment opportunities
Average of all Keywords
Sessions
0
0
1641.21
Session
Duration
0:00
0:00
0:03
Active
Job
Postings
0
0
7.32
JSR P
0
0
3548.65
The result would be – if we can prove conversational media generates higher quality
scores using VS – we can then justify focusing on it more. At this point, what we can
pick up from Search doesn’t work so well for us because conversational media is
different than search – and we probably need other tools and focus than we have,
currently in order to datamine traffic that comes to our site for Social Media.
15
JV P
0
0
2847.04
Also, the terms from CI don’t show Social media is an advantage – it has more to do with
not having the right tools, right filters, set up, than anything else.
We can use Comscore to Measure Conversational Media to Monster
and its Competitors
Conversational Media Traffic UV (000)
2000
1800
UV (000) Social Media Traffic
1600
1400
1200
1000
800
600
400
200
0
Jan2007
Feb2007
Mar2007
Apr2007
May2007
Jun2007
Jul2007
Aug2007
Monster.com CM Traffic
Sep2007
Oct2007
Nov2007
Dec2007
Jan2008
Feb2008
Mar2008
CareerBuilder CM Traffic
Conversational Media Traffic % of Total Traffic - ComScore Media Metrix
16%
14%
% Social Media Traffic
12%
10%
8%
6%
4%
2%
0%
Jan2007
Feb2007
Mar2007
Apr2007
May2007
Jun2007
Jul2007
Monster.com CM Traffic
Aug2007
Sep2007
Oct2007
Nov2007
Dec2007
Jan2008
Feb2008
Mar2008
CareerBuilder CM Traf fic
16
22. This kind of chart would be much easier to do and more valuable (we could
isolate low, medium and high usage visits) were we to purchase Comscore
Segment Metrix. As it is, not, it was a lot of work to produce it – you had to pull
all of Conversational media traffic for each month shown, and then all
Source/Loss traffic for any property you want to look at, and then do a VLookup
on it - not the most elegant way of doing this kind of work.
Measure Engagement by Frequency and Duration of Visits
I posted about this at Webmetricsguru.com - The Engagement Ramp
try a Engagement Ramp chart by using ComScore to divide the Average times a visitor
visited a Virtual World site by the average minutes per visit - and came up with this chart,
below:
Without knowing for sure what was happening in Second Life last May, it’s impossible
for me to say if my “Engagement Ramp” is accurate or not - but when I listed to the
session last week - what I saw in my mind was a “ramp” or co-efficent, that is created
from the two measurements (times per month you visited divided by minutes per visit).
An accelerating “ramp” means “engagement” is going up, and vice versa.
If my “Engagement Ramp” is in fact, measuring engagement, then it’s fairly flat for the
leading virtual worlds.
Forget about this post being about Virtual Worlds – maybe it’s about visits from a
referrer to Monster.com – the same metrics could be used and pulled out of VS.
Question is – do you agree with the methodology – does this kind of metric reflect
momentum? (There’s two measures of momentum – one for Advertisers and one for
Publishers)
17
We can use WebTrends Profiles to for Data mining – they now include
Geo Data from Cities (proxy DMA’s) that were not available before we
upgraded –these can be lined up with Comscore
While UV and Visits are not the same metric (there’s the repeat visitor aspect) - there are
existing reports such as Local UVS where this data can be overlaid – where we can put a
“confidence” factor into Comscore – and say – we feel this number is got a
18
low/medium/high confidence level – based on our actual Web Data for corresponding
properties.
We were never able to do that before – and while we can’t do it for every DMA – we can
do it for the majority of them.
However, pulling Comscore Visits instead of Unique Visitors showed just how far off
and “dirty” their data is (also, we can’t pull numbers for DMA’s – though I have seen
reports WT reports that do provide it – but not at Monster) – which gives me pause in
suggesting we use Comscore, at all, the way it has been for a Local UVS report –
19
Some DMA’s like Charlotte, are very close, but others are so far off, there is no
confidence these numbers can be used for anything but planning – certainly not the way
they are used for the reports now.
The best we can hope for, if we’re going to continue to use Comscore as a forecasting
and reporting tool, is to publish a confidence percentage next to our own numbers – and
extend them to the competitors in each DMA we’re pulling – if we only have a 10%
confidence in the data – either we should not be using it (that’s my hope) or else, we level
set expectations from Stakeholders on what this data means.
Part 2: Towards a Social Media Dashboard
Component parts
-
Monster.com Traffic (the data presented is just for illustration – format
presentation will come later) We need basic data to measure Social Media
traffic against.
o Visits (WT )
o Visitors (WT)
o Pageviews
Web Traffic
20
Note: We can adapt a dashboard for Monster Worldwide (global)– would need a
bit of work since we don’t have a good way to roll up data in WT and VS not
ready yet. Any Global Dashboard for Monster Worldwide would need to be done
with Comscore now, with all its limitations and inaccuracies.
Rollup of Monster Worldwide? No doable at this time
I attempted to provide a rollup to Eric Stutzke that he could use for Corporate but it was
impossible to provide unduplicated numbers or a break down that work for Global
Traffic
I attempted to provide a line item report that had IAF properties – deriving Asia from
subtracting US, CA, ME, EU from Worldwide numbers – the US numbers for Military
Advantage are larger than the Worldwide.
Unless we bought all the countries Comscore provides – it would be next to impossible to
do a Global Dashboard in Comscore, and right now, it can’t be done in WebTrends or
Visual Sciences (with out a lot more work).
So, that leaves us without the means today, to do a Global Dashboard that has any level
of Confidence in the data – so I won’t suggest we undertake this unless we have the right
21
tools in place and the work has been done to create profiles in VS for all of Monster
Worldwide Properties
Social Media Traffic
We’ll require a master list of Social Media sites for Social Media Attribution – There’s
some interest from Abby on this as well – I worked with Breanna Wigle at Military.com
earlier this year and it took me about 10 hours of work to go though the referral logs of
those who signed up for newsletter on Military.com who came from DodBuzz.org – with
one month of data.
To do the same for Monster would take a bit longer – probably three or 4 days of work to
look through the entire Referral logs (out of Visual Sciences) and categorize the urls
I’ve done a similar project outside Monster that did exactly what I’m proposing here –
but we used Omniture Site Catalyst instead of WebTrends. Here are the Steps
Classify Site Referral Traffic by the following criteria:
-
Is it a blog? (any blog)
Is it a message or chat board?
Is it a photo sharing site? (for example, Flickr)
Is it a Social Network? (Facebook, MySpace, etc)
Is it a forum?
Is it a Video Sharing site? (YouTube, Google Video, etc)
Is it a collaborative news site (where anyone can submit a story)?
Is it a mashup site (i.e.: Google Maps combined with additional information)?
Is it a mobile site that allows members to interaction (i.e.: Loopt)?
Is it a Micro Blogging site (i.e.: Twitter)
Collect a sufficient amount of data in a report covering a designated period of time – 1
month, 3 months, 6 months or 1 year (50,000 deep), Domain Referrals are recommended
as it’s easier to work with and can be more generally used.
Example - Omniture:
22
We generated up to a 50K deep report of Referring Domains which was used to create a
list of Social Media Sites. We also suggest that list should further be categorized by
blog/social network/message board/photo sharing site, etc, as mentioned, above.
The resulting “filter” list is maintained on a weekly, monthly basis and used as an
advanced filter or Vlookup for traffic in your referral logs that is attributed to Social
Media.
2. Use the same table, created in step 1, for Social Media Conversions
Required – a report for Conversions by Original Referral Domain –
Original Referring Domains Report - Comma Separated Values
Report Name:
Original Referring Domains Report
Compression:
Zip
Date Created:
Aug 06, 2008 11:47 AM EDT
Site Title:
Site URL:
User:
Company:
Reporting Date:
July 2008
Search:
None
23
Graph:
Percentages
Number of entries
requested:
50000
Selected Original Referring
Domains:
All Original Referring Domains
Broken down by:
Categories
Showing:
Referral View, Registrations, Sign In/Log In, Email, Create Account, Create
Account 1, Add to Wishlist and Add to Registry
The output of the report looks like this:
The data from the report needed to be assembled in a useable format so that it could serve
as the basis for lookups – here’s an example of what we did.
Note: You can use Referrers instead of Referring Domains – but it’s a lot more work with
little more to show for it – that’s why we recommend using Domains.
Also, we needed to take the list above, and filter by Social Media traffic (see the
following page).
We were able to take that data and do something like this (see below), which showed the
result of Social Media Optimization for the client.
24
We also pulled a Referral Report (for this we used “Referrers” rather than “Referring
Domains”, to get greater granularity – but might as well have used Referring Domains for
that, as well:
We could add up the Social Media Traffic to the Client’s domain by lookup tables against
a referral report for each month – the result is above.
Now that we’ve assembled “Social Media Attribution” by Referring Domain – we’re in a
position to scorecard the information and possibly, determine ROI of that traffic.
25
We added a few additional metrics
-
Conversation Size = the number of unique domains/referral sources
Social Media
= count of referral traffic from Social Media Sources
(outlined in step 1)
3. Calculating ROI of Social Media
June 07
Once the conversions are collected and attributed to Social Media (or not) – you can go
one step further and assign a value to the conversion event – allowing estimation of
Social Media ROI (in this case $13,911 for the month).
In this case, we assigned a value of $100 for a Registration and $10 for an Email – the
point is not the value is correct or not, that will vary from organization to organization –
the value is in making a determination of the value that’s realistic, and that you can base
calculations off of.
June 08
We were able to show, given this example, an estimated ROI for Social Media, given
these values, of $30,923 for June 08, about a 250% increase Year to year.
The final step is to subtract the cost of running the Social Media Optimization program
against the revenue generated by it –
26
Cost of Social Media
The profit would then be $30,923 - $3,900 = $27,023.
Mobile Traffic
IPhone traffic in Light Blue (do we know what happened between 9/27 and 10/25)?
We could track Mobile Usage with Comscore – but we’d have to buy their Mobile
offerings. We could also track video usage – but same story, we’d have to buy their
video measurement data.
27
Search Engine Data
Monster Traffic Stats
50,000,000
45,000,000
40,000,000
35,000,000
Visits
30,000,000
25,000,000
20,000,000
15,000,000
10,000,000
5,000,000
0
Sept '07
Oct '07
Nov '07
Dec '07
Jan '08
Paid Search Visits
Feb '08
Mar '08
Organic Search Visits
Apr '08
May '08
Direct Traffic Visits
Jun '08
Jul '08
Aug '08
Sept '08
Total Traffic Visits
Data from WebTrends is not that helpful right now – but we can definitely superimpose
Social Media Traffic with Search Traffic (not shown yet).
Percent Organic Search and Job Postings Corrolation
40.0%
30.0%
10.0%
Sep'
08
'08
Aug
Jul '0
8
Jun '0
8
May
'08
Apr '0
8
Mar '0
8
Feb
'08
Jan '0
8
Dec
'07
-10.0%
Nov
'07
0.0%
Oct '0
7
percent
20.0%
-20.0%
-30.0%
% change in Job Postings
% Change in Organic Search Traffic
We could also attempt to co-relate Social Media outreach (as suggested in #19 on page
12) increases site traffic much as I’ve shown Job Postings (numbers) impact Search
Traffic.
28
We can run probability assessments and regression analysis to determine what the
likelihood that an increase of Social Media related traffic (which we’d have categorized
in #8 and on page 24) affects other Dimensions of Monster’s traffic and KPI’s.
% Social Media Traffic
% Social Media Traffic
2.50%
2.00%
1.50%
1.00%
0.50%
'0
8
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ly
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ay
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% Social Media Traffic
Linear (% Social Media Traffic)
29
LA
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14000
12000
10000
8000
6000
Social Media
4000
2000
0
Blog Traffic
8000
7000
6000
5000
4000
3000
2000
1000
0
Jan '08
May '08
Jun '08
Feb '08
Jul '08
Mar '08
Aug '08
Sep '08
Apr '08
May '08
Jun '08
July '08
Blog Visits
We can produce similar types of charts in an integrated dashboard – we can also tie in
MonsterHouse data. We did something similar with the Local UVS report recently.
1800000
1600000
Monster Career Network UV
1400000
1200000
1000000
800000
600000
400000
200000
0
30
(M
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40000
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Sep '08
Sep '08
Job Postings by DMA
35000
30000
25000
20000
15000
10000
5000
0
80000
70000
Resumes Posted
60000
50000
40000
30000
20000
10000
0
It would be possible for us to do overlays of traffic, or some other KPI, with internal
Monster House data such as Job Postings or Resumes Posted, or even Resumes Sumitted.
If we can isolate a Social Media aspect to this Mashup, I think it can be even more
valuable.
Part 3 – What we’ll need
Comscore
One account – 20 users – all countries offered + Segment Metrix, possibly Media
Builder, and Local Market (~450K per year)
Visual Sciences
We’ll need the rest of the Monster Properties added (Military, Affinity,
MonsterTrak, Fastweb, etc)
Enhances for Search (Paid Search vs. Organic)
Joins with Monster House data and Search Traffic
Social Media Segmentation
Methodology mentioned in pgs 24-28 (to be maintained, updated
monthly)
WebTrends
A special profile for Mobile Technology
31
A Social Media Profile similar to what we have for Search Engines
Social Media Buzz Monitoring
Radian6 and or/ Collect Intellect Self Serve (~6K-12K per year).
Summary
Presented anything I can think to we could or should track, today, and the associated
metrics / KPI’s and Dashboard to go with it. This is not a finished document – I expect
it to grow, there are many gaps.
For example, there’s no good solution for Global Dashboards right now – there’s also no
clear home for Social Media at Monster – most would put it in Marketing or
Communications, where I would put it in Monster Insights – because it’s also a large
measurement component that isn’t addressed when it’s in Marketing or Communications.
Finally, there’s an Outreach aspect (covered in #19, on page 12) that hasn’t really been
addressed at Monster.
This document is created before any meeting took place between Ketchum and Monster
Insights – or Vanina’s group – we don’t know any plans yet that are in place which might
affect anything I’ve collected herein.
32