Web User Journey Analysis

JAOU Website
2018 Performance Review
June 01 thru December 31 (v2 Jan 18)
Precision Medicine Initiative, PMI, All of Us, the All of Us logo, and “The Future of Health
Begins with You” are service marks of the U.S. Department of Health and Human Services.

Observations & Findings
Recommendations
❑ Use 2018 as a benchmark period. Begin applying monthly or quarterly KPI Milestone
performance goals to drive overall strategic execution.
❑ Begin setting up campaign tracking for all consortium partners. Develop a reporting
mechanism for partners to review their own marketing performance and attribution
measured against national program influence.
❑ Place greater marketing campaign emphasis on creating site traffic. More aggressively
retarget site visitors for return visits before conversion (expand implementation beyond
current email retargeting).
❑ Leverage landing page A/B testing for multiple objectives including lowering bounce rate,
with added objectives for improving return visits, content consumption and pageviews.
❑ Adjust the Google default configuration bounce rate. Apply a ‘time out’ formula to better
represent a true bounce.
❑ Consider the impact of designing specific culturally correct Spanish landing pages and
Spanish content pages for Hispanic heritage self identification.
❑ Reinforce high visitation content pages with greater site design visibility and positioning to
aid in the user experience.
❑ Expand the use of co-branded landing pages and consider more Community Partner
cobranded landing pages as a means to have specific campaigns drive traffic to specific
brand identifiable and trusted brand landing pages.
❑ A large amount of conversions are coming from 12+ site visits which indicates there are
users that engage with the site multiple times before first conversion. Consider what landing
pages may help a returning visitor learn more about the program and entice them to take
action.
❑ Create additional landing pages to vary how users enter the site. As of now most landing
page visits are to the homepage which the data suggests might be suboptimal for first-visit
conversions.
❑ Implement insights from earlier survey data that may have key insights into landing page
creation for optimal demographics targeting, copy creation and imagery.
❑ Expand email list growth strategy past simple newsletter signups. Create a compelling
reason for users to engage with the email campaign to drive visitors back to the site.
❑ Consider varying video and thumbnail preview locations throughout each landing page with
media content to test for conversion optimization.
❑ Improve communication across creative, analytics and development teams to give a more
accurate representation of the entire journey through each channel that drives traffic to
JAOU.
❑ The Return Path for visitors is 50% lower when they have had no prior exposure to the
program. Further supporting the argument of advertising retargeting or email list growth to
drive traffic back to JAOU.

DRC ENROLLMENT COUNTS
Program Conversion Trend Patterns

Need Registrations + Consents by Geo Region from
Scott Sutherland

Enrollment Count Trendlines Time Period: Jan 01 thru Feb 28 2019
DRC Dataset: as Tracked and Reported by Sage Bionetworks & Scott Sutherland.
Blended DRC Dataset + GA View: 176339261 …
(GA datapoints are not absolute which do not remove traffic from bots or stakeholder blacklist IP addresses, but can be used with statistical confidence to identify trending patterns.)
DRC Enrollment Counts Trending Pattern:
Updated enrollment data as reported from the DRC reflects moderate
conversion performance with highs and lows per any given month. We
can see as the year came to end, conversion counts weakened from a
previous (5) five month steady growth pattern. However, moving into
2019, we see a strong reverse trend for enhanced performance.
The ‘quality ratio’ (measures account to conversion ratio) has
remained reasonably steady month over month and is performing
extremely well with an overall 83 percent average.
This affirms that when people make the personal commitment to
create an account, they are following through in high numbers to
complete the Consent process.
It also reveals we are securing quality prospects (leads) via the
various marketing channels and program events. Furthermore, it’s a
good indicator that when candidates arrive at the site and consider
enrollment, they are finding sufficient content to help make a personal
decision to move trough the enrollment path.
The objective moving forward remains to be the need to create a
steady stream of new and return website traffic. Our data shows that
there is a moderate correlation to site visitors vs. enrollment count
correlation (see chart below).
2018 Roundup Counts
177,115 (Accounts / Registrations Created) ꟷ 146,447 (Consent Completions)
83% (Avg. Consent Rate / Quality Ratio)

Enrollment vs. New User Site Visits Trendlines Time Period: Jun 01 thru Dec 31 2018
DRC Dataset: as Tracked and Reported by Sage Bionetworks & Scott Sutherland.
Blended DRC Dataset + GA View: 176339261
DRC Enrollment Counts Trending Pattern:
There doesn’t appear to be a strong correlation with new
(unique) site visitor site traffic and registrations. Consents
closely map to registrations representing that when an enrollee
commits to making an account, they move on to the Consent
process at an 83 percent quality of lead ratio.
Compared to a published report by Smart Insights (19 Aug
2018), industry conversion rates for the Health industry sector
was 12.3% for the best conversion rate and 2.8% as the median
conversion rate.
Our own Conversion Rate of 15.6% (based on unique site
visitors) surpasses the closest industry average we have
identified to benchmark against and represents the program
is doing extremely well for this KPI.
https://www.smartinsights.com/ecommerce/ecommerce-
analytics/ecommerce-conversion-rates/
Conversion Rate (Accounts Created divided by New (unique) Users.
Raw Google Analytics user visit counts does not remove traffic from bots, spiders or blacklisted IP addresses. n = 743,899.

SITE TRAFFIC
Acquisition Trend Patterns

Baseline KPIs
Aggregate Baseline Site Visit Metrics:
Site visits continue to show fluctuation month over month with an
overall downward trend pattern after the initial launch. Of the core
tracking metrics, the objective should be to set monthly or quarterly
target goals to ensure consortium marketing efforts are aligned and
optimized for reaching month over month site traffic growth
milestones.
It would also be beneficial to be put into place monthly UTM referral
tracking for all consortium partners so that they may review their own
marketing attribution performance as to the impact on site traffic.
Overall, new users represent the majority of site traffic with return
visitors accounting for 22 percent of all monthly website traffic.
Sessions, pageviews per user, and average session duration are all
respectable with average pageviews per user increasing over time.
The average Bounce Rate for the time period represented is also
within levels on the low range of similar nonprofit websites (60-75%) -
further representing many new visitors are arriving to find information
and content expected.
Moving into 2019, these early 2018 performance metrics should be
used as benchmarks to set track and monitor core KPI monthly
milestone targets.
Time Period: Jun 01 thru Dec 31 2018
Average Session represented in minutes + fractional minutes. Multiply fractional decimal minutes by (60) to convert to seconds.
GA View: 176339261

Website User Visits Traffic
Site Visit Trending Pattern:
Residual influence carried over into June from Launch, but has since
declined.
Ideally, we would like to see a continuing upward trend (even with
modest month over month improvement) as program awareness
grows among the general population. Yet we are actually seeing a
flat monthly trendline pattern for both new and returning users with
the exception of the August anomaly.
Sustaining month over month growth is critical for both user types.
Placing greater emphasis on traffic growth as one measurable
campaign KPI objective (for all partners, campaigns and channels)
ensures we are continually optimizing content, messages and CTAs
for growing program awareness while enriching our understanding
for content and message resonance as part of the enrollment
journey path.
Although not represented here (see next slide series), Bounce Rates
are a leading indicator for understanding site traffic and landing page
content design and influence, (i.e., are our landing pages delivering
on pre-arrival expectations?).
Industry nonprofit benchmarks for similar programs reveal we
essentially have one opportunity (one site visit) to make an initial
impression for a person to decide whether to return and to act on the
call to action.
Therefore, a goal moving into 2019 should be to leverage the
landing page A/B testing to gauge and measure (as one objective) if
simplified landing pages further decrease our bounce rates and how
they may impact return visits, content consumption and deeper site
navigation.
Overall, published benchmarks bounce rates for Non-Profits typically range between 60% to 75%.
GA View: 176339261

Bounce Rate + Avg. Session Duration (All Visits)
Bounce Rate + Session Trending Pattern:
When reviewing Bounce Rates and Session Duration in general, we
must review these metrics with special considerations. What we
need to understand is the default configurations Google assigns
using single pageview visits for these metrics do not statistically
represent the real behavior of our user for a site visit.
Therefore, we need to consider what is a bounce? How should we
look at session duration?
The JAoU web design uses expansive content on the primary
landing page, and many first visitors may not navigate beyond the
entrance page. For a first time visitor, this is totally understandable.
Therefore, what we must determine is how much time in a visit
constitutes a bounce and adjust the bounce rate formula accordingly.
This can be achieved by using a ‘time out’ function in minutes
instead of using the standard one ‘pageview’ formula. This will more
accurately represent if site visitors are arriving and finding a site and
content as expected which will aid us in our own site design and
strategic execution.
Over time, we can continue to adjust the bounce rate formula to
better reflect a ‘true’ bounce and a ‘true’ session duration via close
monitoring of the user journey and conversion tracking.
The key benefit will be our ability to better determine if our site
design and the marketing messaging designed to drive traffic to the
site is aligned to user expectations.
(Our current average bounce rate for this time period view and as
reported by Google Analytics is within low thresholds for nonprofit
industry averages at 55 percent.)
Average Duration represented in minutes + fractional minutes. Multiply fractional decimal minutes by (60) to convert to seconds.
Average Bounce Rate is the percentage of single pageview visits to a website. Average Session Duration is the reported average time a user spends on the website (min/sec).
GA View: 176339261
Clarification note: Google Analytics bounces are counted as single pageview site visits, and Session Duration time calculations
remove bounced users from the session time reported conveying a potentially misleading and inaccurate representation.
Avg. Session Duration for this time period view is 7 minutes & 17 seconds (00:07:17).
Should visitors spending a fair amount of time on the landing page gathering information be considered a bounce?

Bounce Rate + Avg. Session Duration (New Visits)
New Visits Bounce Rate + Session Trending Pattern:
Reviewing New Visitor site traffic patterns measured against
average monthly Bounce Rates and average Session Duration, we
can begin to see the nuances when compared to overall (all user
site traffic) averages.
Both Bounce Rate and Session Duration do modestly move in
opposite (negative) directions as expected from overall averages
when new users are isolated and when return user visits are
removed.
However, in large part, users are still arriving at the site to find a
site and content they expected. Furthermore, they are spending a
fair amount of time on the site during their first visit (average
session duration).
This data view begins to help us define a new Bounce Rate Time
Out formula. The initial new Bounce Rate formula can be set to an
arbitrary time out time calculation based on an average of monthly
averages, or even a lower time duration consideration based on
what we define as a true bounce (e.g. 90 seconds).
It would be further recommended this process be repeated and
tested over defined time periods to continuously keep the bounce
rate calculation as accurate as possible.
And once a new bounce rate formula is implemented, we can
expect to see our numbers to perform better while giving us a much
truer representation of user site visits both for bounce rate and for
average session duration.
GA View: 176339261
Raw Google Analytics user visit counts does not remove traffic from bots, spiders or blacklisted IP addresses.
Using a Time Out function for reflecting a more accurate Bounce Rate would better represent if a user
is not finding a site and content they were expecting upon arrival.

Bounce Rate + Avg. Session Duration (Return Visits)
Return Visit Bounce Rate + Session Trending Pattern:
The value for reviewing Return Visit traffic patterns is to more
accurately understand how much users are engaged upon their
second or subsequent visit.
We can clearly see bounce rates go down and average session
duration goes up significantly over new visit patterns.
This represents return visitors are navigating to other site pages
and diving into the site content much more frequently and with
much more consideration.
As a new bounce rate formula is considered, adopted and
activated, over time we will continue to have a better picture as to
what is occurring to help steer strategic directions.
As one objective moving forward, we should set monthly or
quarterly milestone goals for reducing bounce rates and increasing
average session duration for both new and return visits.
This will allow us to continually align and optimize site content /
design as well as to strategically plan campaign activity to sustain a
continuous upward swing in better performing averages.
GA View: 176339261

Top 20 Landing Pages (view 1)
Site Arrival (Landing Page / Non-Bounce) Trending Pattern:
Marketing Campaigns, the main thrust behind creating website traffic,
have been primarily designed to drive traffic to the main home page on
the JAoU website. As a result, the Top 2 primary landing page
destinations for new user visits are as expected and are aligned with the
either the English or Spanish home page.
Other campaign and retargeting activity (national and/or local efforts)
may frequently drive traffic to other landing destinations per defined
objectives, e.g. email retargeting with CTA links to ‘Get Started – Sign
Up’, ‘How to Join’, or cobranded campaign efforts, et al.
One observation for this visitor type we want to pay attention is the
amount of time people are consuming content upon their arrival to the
site and on the landing page before navigating to interior pages as part
of their overall session visit.
For the primary home page, new visitors clearly outnumber return
visitors and are spending a fair, but small amount of time consuming
content before clicking through to another page. This suggests they are
scanning the page for content and information of personal appeal
without diving too deep into the page.
This trend further reinforces our current direction for testing lightly
populated content landing pages.
It’s also interesting to note for non-primary landing pages, where visitors
are spending the most time on page. Getting Started, How to Join and
the FAQ pages are within the Top 5 Landing Pages and are prime
destinations for returning visitors for which we can categorize as visitors
moving through the enrollment journey path.
Other significant journey path pages include Program Overview, Who
Can Join, What You Need to Do, and Benefits of Taking Part. All of
which represent content that visitors are placing a high value.
Entrances represent the number of Visits that started on a specific Web page.
GA View: 176339261
Ranked by Entrances: Time measurements are in (minutes / seconds) using base 10 decimals.
Deeper analysis is planned in the next review cycle to review influence by device, page load times, session duration, pageviews, page depth, conversion impact, among other key metric attributes to be determined.
Filtered View: This view represents visitors who arrived at the site on a landing page and subsequently navigated into interior pages
for a deeper session and site experience. Approximately 40 percent of all site visits. (bounce visits [single page visits] removed)

Top 20 Landing Pages (view 2)
Site Arrival (Landing Page / Bounce) Trending Pattern:
Primary Landing Pages remain the top destination for visitors
classified as single pageview Bounces.
Since these visits are categorized as Bounces using Google’s default
configuration, we are unable to review time on page or session
duration to determine deeper engagement behaviors.
The key takeaway from this view is the percentage of ‘single
pageview’ return visits to specific pages which reveal what content is
deemed a key consideration and worthy of a return vist in the
enrollment journey path.
Another insight we can begin to draw upon by comparing the two
views for visitor types, there is a lack of Spanish language pages in
the top rankings. The question that needs to be asked, “are Spanish
language visitors returning to the site to advance in the journey path?”
Only one Spanish language page other than the Spanish home page
shows up in either list in the Top 20.
Does landing page design (and potentially overall Spanish site design)
for Spanish visitors matter for self identification?
Would a Spanish language landing page specifically built for the
Hispanic community perform better? Would greater emphasis on
culturally fitting pages to the Spanish visitor impact return visits,
session duration and ultimately conversion?
Currently, the English and Spanish landing pages and interior content
pages are essentially the same using the same content and visual
images. A consideration for 2019 is whether A/B testing is warranted
for a Spanish re-design that is specifically representative of the
Hispanic community.
Entrances represent the number of Visits that started on a specific Web page. %Exit represents the number of visits who left the site on the page.
GA View: 176339261
11% of all Landing Page visits are for the Spanish landing page. This may represent a much truer representation for Spanish site usage
over the Google Analytics reporting based on user language demographics.
Filtered view: visitors who have been classified as a bounce). Time Period: Jun 01 thru Dec 31 2018
Ranked by Entrances
v
v
v

Top 10 Content (Interior) Pages
Top Content Pages Trending Pattern:
Removing the primary landing pages we can begin to see which
pages and content is being valued most after arriving at the site and
upon a return visit.
A clear observation is much of this content is largely being consumed
by return visitors. This represents a logical and natural user journey
conversion path for gathering more information after initial program
awareness and first site visit.
It further reinforces that it is imperative for us to get first time visitors to
return to the website to move candidates through the enrollment
journey path.
A prime objective should be to reinforce these content pages via
prominent site design profiling and positioning within the overall user
experience. And beyond site design, these pages with high visitation
afford opportunities to disseminate verified valued content and
messaging across all active campaigns.
Another observation when reviewing the exit rate percentage for each
content page is that these individual pages are part of a larger user
session. This is verification that visitors are navigating deeper into the
site for greater program information as part of their personal
enrollment consideration.
One last observation is that visitors are spending the most time on the
‘Get Started – Sign Up’ page with an average reported time spent at 6
minutes, 20 seconds. But it’s inexplainable as the limited ‘on-page’
content doesn’t necessarily warrant such time averages.
This may be a Google Analytics nuance associated with default
configurations, which we will need to investigate further. For the near
term, it’s advised that all GA time metrics be used only as a single and
not exclusive benchmark to gauge differentials aligned with assorted
metric views.
GA View: 176339261 Average Time on Page represented in minutes + fractional minutes. Multiply fractional decimal minutes by (60) to convert to seconds.
Ranked by Pageviews
Of note, Privacy Safeguards does not show up in this list. It may indicate ‘privacy’ is not as big of a concern for enrollees as we originally believed
and as we launched the program.

CHANNEL & CAMPAIGN
Attribution Trend Patterns

Attribution Tracking Disclaimer
The current Google Analytics setup does not allow us to track site traffic and/or conversion attribution with a high degree of confidence.
Unresolved technical problems associated with UTM links, the lack of consistent UTM use overall among all partners, and reliability issues
surrounding Goal Setup and tracking within Google Analytics limits our ability to analyze traffic and conversion attribution with accuracy.
As a result, we can provide only limited preliminary Google Analytic views based on traffic and conversion patterns which we have verified are
significantly underreported across all campaign activity. This also limits our ability to track and analyze the user journey accurately via
attribution throughout the site.
Therefore, the analytic views to follow are limited in scope and should be reviewed with caution without any assurances they accurately reflect
the true nature of site performance. We advise that the results presented within this section for attribution should only be used as a
representation and are not qualified counts. However, there may be opportunities to use these views as a single benchmark going forward.
Steps are being applied to correct this in 2019. It is proposed we set up a task force to address all open areas for improvement with Google
Analytics, and to re-review the UTM tagging process and implementation which requires cooperation and collaboration among various
stakeholders. We are optimistic we can resolve open issues and have much cleaner and more accurate attribution reporting within the next
several months.

Goal Tracking Attribution (Google Analytics)
Goal Setup (GA) Attribution Trending Pattern:
Goal Setup and Conversion counts from within Google Analytics is
under reporting. Therefore, our review of attribution reporting will not
reflect actual confirmed counts.
As one example, we can clearly see Display media is being under
reported by thousands. A data verification of the DRC data reveals
GA Goal conversion counts for accounts and completions are under
reported by as much as 20 percent.
This is the problem the program continues to face. As such, Google
Analytics for Goal Conversions can only be used as one reporting tool
to loosely gauge performance across the site.
Going forward, we will need to augment the Google reporting where
possible with other marketing reporting platforms in use or are coming
online, and when marketing pixels have been reinstated which we
have a greater degree of confidence.
GA View: 176339261
Accounts Created
Channel Attribution

Traffic Attribution (Default Channels)
Default Channel Traffic Attribution Trending Pattern:
Another word of caution regarding Google Analytics and Default
Channel attribution reporting.
There are default configuration nuances associated for how Google
Analytics arbitrarily applies channel attribution. As a result, the
current UTM tagging and lack of tagging in place across many partner
marketing campaigns creates a slightly different picture for results by
over reporting and under reporting channel attribution results.
To take this into consideration, we conducted a data grooming
exercise for the last six months. The net result is that we determined
the GA reporting is close enough to use as an approximate, single
benchmark with the understanding actual counts may vary by channel
with some channel counts impacted more than others.
After data grooming, Direct and Display Advertising + Paid Social are
the leading channels for site traffic attribution. Of note, Organic Social
is surprisingly less representing a much smaller part of overall traffic
acquisition.
Referral traffic needs to be reviewed with the understanding that it
comes from both partner activities largely a result of direct backlinks,
and via improper channel assignment for online domains that are
likely display advertising clicks which are missing associated UTM
parameters.
Email, as a channel of site traffic influence, is on the lower end of the
acquisition scale.
Organic Search is consistent, but minimal indicating mass awareness
among the general population has yet to reach critical mass.
The Other category, when the data is properly groomed and with
proper attribution assigned using source/medium parameters is
marginal as expected.
DirectTrafficattributionincludes anyuserswhoclickeddirectlytothesiteaswellasallunknownsourcetraffic.The‘Other’distinctionisthatuserssessionsdonotmatchanychanneldescription.
GA View: 176339261
744,354
Site Visits
-------------
100%
Overall Site
Traffic
Attribution
-------------
66,615
Account
Conversions

Traffic Attribution (National Marketing)
Marketing Campaigns Traffic Attribution Trending Pattern:
National media is the leading campaign and channel of influence for
national marketing campaigns.
The media buy has been active since launch and runs across display
and includes social media (primarily Facebook and Instagram), with
continuing assorted testing across other online channel outlets.
Cobranded media is also a part of the national media buy and
supports the local HPOs and Consortiums. It runs in tandem with the
national campaign to complement overall program awareness and site
traffic media trends.
A consideration to keep in mind and which could increase these
numbers is the national media traffic attribution which may be
currently assigned to Referral traffic by Google Analytics.
Email retargeting site traffic attribution from newsletter subscriptions is
smaller, but plays a vital role for return visits.
Social media attribution at the national level is virtually non-existent.
However, the national social media program to date has yet to
implement a consistent tagging process. The impact is that much of
national traffic is currently being assigned to unattributed social traffic
as reported by Google Analytics. In 2019, we look to change this
practice for better, cleaner reporting and analysis.
GA View: 176339261
224,641
Site Visits
-------------
30%
Overall Site
Traffic
Attribution
-------------
688
Account
Conversions
Campaign Channel Traffic Acquisition Acct Conversions
National Media 113,446 130
Cobranded Media 67,135 28
Email Retargeting 43,923 528
Organic Social 137 2

Traffic Attribution (DV Partners) Time Period: Jun 01 thru Dec 31 2018
GA View: 176339261
141,420
Site Visits
-------------
19%
Overall Site
Traffic Attribution
-------------
2,089
Account
Conversions
DV Partner Traffic Attribution Trending Pattern:
Three DV partners are accounting for most of the new site traffic
among all DV Partners.
WebMD, Blue Cross / Blue Shield and Walgreens all have active
monthly campaigns across varying channels. As detailed on the
next slide, media and paid social constitute the channels for most
influence for site traffic.
The San Diego Blood Bank, the MEA Journey Bus Tour and the
Scripps managed MediaPlanet campaign account for the remaining
low number of visits.
Of note, Journey Bus Road Exhibit attribution still needs deeper
consideration for how best we track attribution both from on-site
kiosks and after the initial in-person engagement.
DV Partner Traffic Acquisition Acct Conversions
WebMD 58,896 840
BCBSA 40,593 14
Walgreens 35,371 27
BCBSA Regence 2,463 1
SDBB 1,879 479
MEA – Journey Bus 1,209 477
MediaPlanet 1,007 251
CBCC 0

Traffic Attribution (DV Channels) Time Period: Jun 01 thru Dec 31 2018
GA View: 176339261
Marketing Campaigns Attribution Traffic Trending Pattern:
In aggregate across DV Partners, we can see display media and
paid social advertising are the biggest traffic creation channels for
site visits.
Email to date has been used sparingly, but with the notation the
San Diego Blood Bank uses it almost exclusively as their primary
communications channel.
Other channel traffic including Referral backlink traffic from Partner
websites are having small influence in a complementary role. Of
note, organic social media is not currently a major focus of any
partner.
Campaign Channel Traffic Acquisition Acct Conversions
Display Advertising 87,770 109
Paid Social Media 38,360 47
Referral Backlinks 7,631 660
Email 7,592 1,271
Organic Social 67 2

HPO Campaign Traffic Attribution Trending Pattern:
Overall in aggregate, HPO Consortiums are having much less
influence compared to DV Partners.
We can clearly see the standouts, i.e., New England, TACH, Arizona-
Banner and Wisconsin. However, what these early results reveal is
the need for more awareness campaigns and marketing support
driving traffic to the HPO landing pages to maximize site visits and
enrollments in each of the HPO Consortium regions.
All current traffic attribution is identified as Referral traffic. Plans are
underway to begin working with each HPO Consortium for applying
tracking codes to their marketing efforts. In the coming months, we
should start to be able to track HPO activities and attribution much
closer.
Traffic Attribution (HPO Consortiums) Time Period: Jun 01 thru Dec 31 2018
GA View: 176339261
39,213
Site Visits
-------------
5%
Overall Site
Traffic
Attribution
-------------
7,702
Account
Conversions
HPO Partner Traffic Acquisition Acct Conversions
New England 9,357 490
TACH 5,468 2,848
Arizona-Banner 3,204 1,763
Wisconsin 3,205 717
Pennsylvania 2,631 898
Illinois (IPMC) 1,999 603
California 1,202 96
New York 900 134
Southern 623 89
Southeast 466 60
Jackson-Hinds 78 4
HRHCare 4 0
Cherokee Health 1 0
Attributable Conversion Counts

Traffic Attribution (Community Partners) Time Period: Jun 01 thru Dec 31 2018
GA View: 176339261
Community Partner Traffic Attribution Trending Pattern:
Influence is minimal on site traffic. The standouts include the San
Francisco General Hospital Foundation (SFGHF), the National
Alliance for Hispanic Health (NAHH), and the WBRC.
Most of the current traffic attribution is identified as Referral traffic,
with social media being experimented with at some levels. Other
channels show up in the mix, but account for less than one percent of
the total traffic attribution.
Near-term, we will engage this group our new UTM tracking process
as it is readied in early 2019. Another consideration may be more
Community Partner landing pages which can be the prime landing
destination for all partner marketing campaign activites.
32,631
Site Visits
-------------
4%
Overall Site
Traffic
Attribution
-------------
252
Account
Conversions

NIH Support Traffic Attribution Trending Pattern:
NIH support is being realized for site traffic and conversions via it’s
digital online properties. Although representing a small percentage of
overall site traffic, the visits coming from the NIH are consistent month
over month.
Of note, we can see the Director’s Blog is having minimal impact on
return traffic back to the JAOU website.
Potentially one of the problems, is that on frequent occasions, marketing
campaigns may be sending traffic to the NIH.gov site to view the
Director’s Blog videos (and possibly other content). Ideally, all
marketing campaign traffic should be directed to the JAOU website.
As we can appreciate, we want to keep user clicks to a minimum to get
users to the JAOU website.
Moving ahead, we should begin scrutinizing much more closely as to
where JAOU specific marketing is sending site visitors.
Monitoring the NIH backlink traffic flow will help us identify which
marketing campaigns are reversing the user path, which we can then
address individually with the campaign owners.
Traffic Attribution (NIH Support) Time Period: Jun 01 thru Dec 31 2018
GA View: 176339261
37,682
Site Visits
-------------
5%
Overall Site
Traffic
Attribution
-------------
5,363
Account
Conversions

Traffic Attribution (Unspecified Campaigns)
Unspecified Campaign Traffic Attribution Trending Pattern:
A fair amount of monthly website traffic and conversions are not
attributable due to the lack of proper campaign tagging. Although
these monthly totals may not be large, when we factor in other non-
attributable Direct and Referral traffic, the representation becomes
much bigger.
In the coming months, the analytics team will be working more closely
with various partners to implement better tracking through the use of a
renewed UTM tagging effort.
However, of note, Social Media is most impacted here. Our own
national social media efforts are likely not being given credit for the
influence they are creating. In the same mention as above, we will
work with the social team to put into place a tagging process and
system to make sure they are given credit for their campaign
activities.
GA View: 176339261
Unattributable Conversion Counts
21,838
Site Visits
-------------
3%
Overall Site
Traffic
Attribution
-------------
1,330
Account
Conversions

USER ATTRIBUTES
Visitor Characteristics Trend Patterns

Language Use Traffic Patterns
Language Use Trending Pattern:
Spanish language use as reported by Google Analytics (and
which can be used as one benchmark) is not growing.
A consideration is whether there are sufficient and sustaining
campaigns designed for the Hispanic audience to grow site
traffic and participation.
Across all marketing touchpoints, more native language
campaigns may need to be executed. And ideally, as a
continuous targeted effort without starts and stops for reach
high Hispanic population regions across the country.
As another consideration, our discussion surrounding a
strategic Spanish site redesign direction may enhance the
Hispanic user experience complete with language and visual
imagery speaking directly to the targeted audience.
GA View: 176339261
Spanish Visits by State Region
Google Analytics language visit counts are based on user browser settings and the use of cookies. Inaccuracies do exist. n=758,007.
Landing Page analysis suggest 11% of all Landing Page visits are for the Spanish landing page. This may represent a much truer
representation for Spanish site usage over the Google Analytics reporting based on user language demographics.
English,
95%
Spanish
, 5%

Gender + Age Visit Traffic Patterns
Gender + Age Visit Identification Trending Pattern:
There are inherent limitations for collecting aggregate
demographics from within Google Analytics. The data views
we can collect represent a very small percentage of overall
site traffic and should not be used to make strategic
directional decisions. Google heavily samples this data from
a very small percentage of site traffic (typically less than 10
percent.)
Therefore, the sample size is simply too small. In the
coming months as we get reinstate our DMP platform, we
will be in a much better position to report on accurate site
visitor demographics.
Data View
Limitations
16,010
Site Visits
-------------
2%
Time Period
Site Traffic
Attribution
-------------
15
States
Represented
GA View: 176339261
Google Analytics heavily sampled user demographic visit counts. n=16,010.

Geographic Visit Conversion Patterns (Top 25 States)
Geographic Trending Pattern:
We see an identified trend which may have correlation with
HPO regional presences and active campaigns underway in
those regions, including national cobranded media.
Virginia in isolation, as part of the Capital beltway area, could
be influenced by its proximity of program stakeholders.
Washington state site traffic is influenced by both BCBSA
and Washington University which have active campaigns.
When reviewing average site performance metrics across all
50 states and the District of Columbia, the Top 15 states
surpass the mean averages.
Of note, Arizona leads all states across all benchmark
metrics with an excellent 3.1 pageviews per session and with
an 13 min / 15 sec average session duration.
Although these geographic data views may not provide much
value for considering how regional results impact site design,
it should create some ideation as to how we might be able to
tailor content aligned with specific regional populations.
GA View: 176339261
Ranked by Conversion Rate (Accounts Created divided by New (unique) Users.
Raw Google Analytics user visit counts does not remove traffic from bots, spiders or blacklisted IP addresses. n=749,237.

Geographic Visit Traffic Patterns
State Region Site Visit Trending Pattern:
From the table presented from previous slide, the Top 15
states ranked by number of Accounts Created conversions
are all states where there is an HPO presence.
In support of the HPOs, the National Media Campaign has
active regional media campaigns running in support of the
Consortiums which can be one leading influencer for creating
site traffic levels.
GA View: 176339261
Raw Google Analytics user visit counts does not remove traffic from bots, spiders or blacklisted IP addresses. n=749,237.
State of Texas Site Visit Traffic
(Campaign Review Trendline)

Geographic Conversion (Account) Patterns
State Region Site Visit Trending Pattern:
From the table just presented (previous slide), the Top 15
states ranked by number of Accounts Created conversions
are all states where there is an HPO presence.
In support of the HPOs, the National Media Campaign has
active regional media campaigns running in support of the
Consortiums which can be a leading influencer for creating
the site traffic levels.
GA View: 176339261
Google Analytics Goal Conversion attribution counts. Conversion count: 66,281. n=749,237.
State of Texas Conversion Attribution
(Campaign Review Trendline)

CONTENT ENGAGEMENTS
Site Visitor Trend Patterns

Top Bounce Pages
Top Bounce Pages:
Out of all pages the bounce rates are highest for the main
homepage (which also accounts for the majority of traffic to
the site, so this is an expected result). Some specific landing
pages like the San Francisco General Hospital Foundation
landing page has a higher bounce rate.
Usually, a high bounce rate is a sign that users because they
aren’t finding what they are looking for. We can improve
bounce rates by analyzing which pages they occurred on and
the traffic sources leading to that page.
Considering: Were the steps preceding this page visit
consistent with messaging, style and imagery?
GA View: 176339261

Newsletter Subscribe Activity
Newsletter Signup Event Flow Mapping:
Emails have a sizable impact on the conversion of what
appears to be a main part of the DV journey. 449 Account
Creations originated from email campaigns. The current email
list size is ~166K.
13.3% of users that sign up for the newsletter continue on to
create an account. This indicates Newsletter Signup activity is
tied to higher site conversion activity.
Action Item: Conversions should be sent to the Newsletter
Subscription or creation of another offer in exchange for
contact information that will lead to future nurturing toward
Account Creation.
Based off of a Google Analytics sample of 8.98% of total
interactions on the site. Some data is unavailable due to
constraints between Digital Marketing Protocol’s restrictions
against cross-site tracking.
Newsletter Signup Event Flow is a representation of events in Google Analytics that contribute to conversion.

Top 10 Videos
Top 10 Videos:
Videos are a significant step in the user journey, as seen in
the next slides, this has an impact on the User Experience
through to conversion.
GA View: 176339261

Video Average View Duration & Traffic Sources
Video Average View Duration:
Most of the video traffic inside of YouTube’s analytics came
from native advertising. The rest were site driven with a small
minority of traffic coming through suggested videos or
YouTube search. When considering content that falls outside
of the consent process there are videos that rose to the top.
Other top videos that filter out consent videos include:
• All of Us Anthem
• What is All of Us?
• Why All of Us? Why Now?
• Mayo Clinic Biobank
• A conversation with Bill Gates
• The Dish | Update on All of Us’s Genomics Plan
Suggestions: For future content considering how new landing
page strategies may be enhanced with video content and
utilizing existing content throughout parts of the journey.
GA View: 176339261

Video: Impact on Sign Ups/Events
Video Event Flow Mapping:
Video appears to be a major step in the journey to Login and
Signup events on the JAOU site. From the sample taken
below 22.7% of all traffic watched a video on the site that led
to Logins and Sign Ups.
It’s not clear whether these events occur only as a component
of the website design. For example, a video Call To Action can
influence the clickthrough rate of a particular campaign
because they are either at the top of the landing page or are
required to advance forward in the process
Ways to Improve:
- Consider video button and thumbnail preview location
throughout each landing page to test for conversion
optimization.
Video Event Flow is a representation of events in Google Analytics that contribute to conversion.

Top Landing Page Social Shares Pages
Landing Pages Social Shares:
Facebook and Twitter lead the referrals for Social Activity on
JAOU. A majority of the pages include the main landing
pages, All of Us Journey, Getting Started and direct links to
the Prevent Health Disparities video.
GA View: 176339261

Visual Site Flow
Visual Site Flow:
(Note that banner graphics may vary in size, content and
creative. The included graphic is only a sample
representation.)
The entire DV journey from a visual standpoint is worth
considering for future site design and marketing messaging.
When a user clicks the ad they are sent to the JAOU site
where they visit a series of pages leading to the Account
Creation step.
The visual flow includes representations of the typical journey onto the site.
Discovery Research
Customer
Engagement

CONVERSION PATHS
User Journey Behavior Trend Patterns

Customer Journey
Customer Journey:
In the case of supporting the DV journey we must consider the
complex multi-stage customer journey that JAOU prospects
and participants flow through to completion.
With our current and future analysis we will recommend the
strengthening of steps which will contribute to additional
retargeting efforts.
The visual flow includes representations of the typical journey onto the site.
consideration account consent referral
awareness
PR
Radio/TV/Print
Online Ads
Social
Email
Website
Portal
FAQ
Newsletter

Top Landing Page URLs for Conversion
Top Landing Pages for Conversion:
Most site traffic arrives first on the homepage then is driven
through the conversion path to Account Creation. 49.16% of
conversions occur this way.
13.19% of site traffic arrives at the Get Started page before
moving through to Account Creation.
GA View: 176339261

Program vs. Industry Standard Conversion Rates
Program vs. Industry Standard Conversion Rates:
Based on our Program Conversion Rate of 11% from 600,000
unique visitors and 66,000 sign up conversions we are above
the non-profit Industry Standard of 2%.
Source: MarketingSherpa Website Optimization Benchmark Survey
11%
Program
Conversion
Rate
-------------
2%
Industry
Non-Profit
Conversion
Rate

Conversion Journey Paths: Direct
Conversion Journey Paths:
The report shown is generated from conversion paths, the
sequences of interactions (i.e., clicks/referrals from channels)
that led up to each conversion and transaction.
Direct traffic is normally attributed to a user manually typing
the site URL into their browser to arrive at the site. When we
factor in the known issues with analytics implementation these
visits are from an unknown source.
These may be visits that arrived to the site from advertising
campaigns or other referral sources.
GA View: 176339261

Conversion Journey Paths: Email
Email is a growing and viable part of the site growth strategy
since it is responsible for leading visitors back to the site. In
the cases recorded here the users first signed up for the JAOU
newsletter before returning to the site to create an account.
GA View: 176339261

Conversion Journey Paths: Social
Social network activity in this sample timeframe have led to
conversions and in many cases make up the overall journey
path that a user goes through.
GA View: 176339261

Conversion Journey Paths: Search
Organic Search traffic may account for portions of the journey
that began through prior education of the program or
awareness of JAOU from media.
GA View: 176339261

Account Creation Time Lag Conversions
Account Creation Time Lag Conversions:
Out of 69,142 Account Creation events 61.16% of those had
no prior recorded sessions as determined by Google
Analytics. 20,715 Account Creation events occurred 12+ days
after the first interaction. That behavior indicates either
successful advertising retargeting or effective customer
journey path behavior back to the JAOU site for conversions.
To measure the ROI of our content marketing or social media
marketing campaigns, we’ll have to look at the entire
conversion paths with multiple sessions, as opposed to the
contribution of a single channel with a single session.
Time Lag is the number of days it takes for your visitors to complete the final conversion after their first interaction.

Consent Complete Time Lag Conversions
Consent Complete Time Lag Conversions:
Out of 51,989 Account Creation events 54.59% of those had
no prior recorded sessions as determined by Google
Analytics. 17,989 Account Creation events occurred 12+ days
after the first interaction. That behavior indicates either
successful advertising retargeting or effective customer
journey path behavior back to the JAOU site for conversions.
To measure the ROI of our content marketing or social media
marketing campaigns, we’ll have to look at the entire
conversion paths with multiple sessions, as opposed to the
contribution of a single channel with a single session.
Time Lag is the number of days it takes for your visitors to complete the final conversion after their first interaction.

Additional Notes
It should be noted that much of the information contained within comes from Google Analytics. The platform may not be as accurate as we
would like for tracking users and attribution. However, the data sampling collected and the views built on this data can be used as a valid
representation for identifying traffic pattern trends without using the numbers presented as absolute.
As a result, there may be missing data points we simply can not collect, or data points that are not as accurate as we would like based on this
consideration.
Part of the problem is that user data can not currently be exported from Google Analytics with applied filters that have been set up in the
platform, and which removes traffic from bots, spiders or blacklisted IP addresses. Therefore, the raw data we are using is all inconclusive
including all hits to the website. The other problem remains with lingering technical issues associated with UTM tracking where UTM user link
association beyond a visitor landing on the site does not remain linked to the user throughout their sessions. This may prevent us (or creates
limited visibility) into tracking aggregate attribution of users through the holistic website experience and ultimately through to goal conversions
and post conversion.
The Wondros analytics team will continue to work with Vibrent to identify and resolve open Google Analytics issues and to work with more
accurate data, but to date there may remain limited abilities to collect comprehensive and accurate website performance data for a more
detailed analysis.
It should also be noted this is a first preliminary review and more work is forthcoming with plans to dig deeper into the data for a more
expansive review in the coming weeks and months.

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