DV Journey Analysis

JAOU Website
Attribution & Journey Path Benchmark (Phase 1)
Q1 2019
Jan. 1 thru Mar. 31, 2019
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.

Preface: Methodology
i. Scope & Objective
ii. Insights to be Collected
iii. Workstream & Process
iv. Goal Alignments
v. Variable Journey Paths
Section 1: Our Story
i. Key Findings
ii. Learnings & Takeaways
iii. Actionable Insights
Section 3: Impact Review
vii. Goal Milestones
viii. Next Steps
ix. Appendix
• Production Schedule
• Data Considerations
• Data Analysis Needs
• Reference
Sectional Content
Section 2: Analysis
vi. Analytic Lens
a. Benchmarks
b. Traffic Acquisition
c. Conversion Attribution
d. User Behaviors
e. User Attributes
f. Device & Platform Use
g. Site Navigation
h. Content Engagements
i. Journey Paths
j. Conversion Paths
k. Enrollment Paths
l. Engagement Variances
Q1 2019 Benchmark Review

PREFACE
METHODOLOGY

SCOPE & OBJECTIVE
Our guiding approach.

⦿ This analysis is aimed to deliver a program review of website performance and user experience insights via applying a
geo-filter attribution lens through to the prime account creation conversion point, beyond (where possible) as part of the
holistic enrollment journey path.
⦿ We have segmented available Google Analytics data into three dataset categories and cross tabulated the datasets
against each other to represent identifiable nuances in attributable journey paths. The three geo-filtered data segments
include isolating DV Partner, HPO Partner and aggregate (all visitor) attribution.
⦿ There will be three phases to modeling the final analysis: 1) a filtered view by geography, 2) a filtered view by campaign
attribution, and 3) a cross-tabulated hybrid view leveraging both filters with final insights and learnings. This review
covers the geographic analysis for Phase 1.
⦿ An extended Phase 4 analysis (where deemed valuable) is proposed to include filtered attribution views for MEA
Journey, Community Partners and National Marketing campaigns.
Analysis Scope

⦿ The objective will be to demonstrate (with confidence) we can build a journey path attribution model by separating
unique journey paths with actionable insights as a repeatable exercise. The initial emphasis will be on the DV Partner
journey path with consideration as to how it may differ measured against other attribution site traffic and user behaviors.
⦿ Our goal is to publish quarterly updates deliverable 30 days past each quarter to all relevant stakeholders while building
a visual dashboard for real-time insights.
Prime Objective

INSIGHTS
What we are looking to learn.

Insights To Be Collected Within Final Analysis (Guiding Directions)
Q. (Benchmark) How has the program performed in the past, and which we
can begin to benchmark current performance against?
Q. (Attribution) What channels, metros, and campaigns are driving traffic to
the website? What conversions can we track via geo-location and/or
campaign attribution?
Q. (User Metrics) What are user behaviors upon arriving at the site? What
do we know about the visitors?
Q. (UX) What devices and platforms are visitors using? How are they
accessing the site upon first visit? Upon return visit? Are their
identifiable patterns?
Q. (UX | CX) How are visitors arriving at and entering the site? How are they
navigating the site upon first visit? Upon return visit? What nuances do
we see between the two types of visitors?
Q. (Content Engagements) What content are visitors consuming? What
content has high appeal? What content is influencing conversion? What
patterns do we see in the data?
Q. (Journey Paths) What does the journey path look like from initial site
visit through to primary account conversion?
Goal & objective is to be able to apply quarterly insights to optimize strategic directions.
Q. (Conversion Paths) What are the site usage patterns identified for
conversion?
Q. (Enrollment Paths) Can we link attribution and journey paths after
account creation to understand deeper enrollment through to full
participant? If so, what insights can we glean?
Q. (Variances) How does baseline DV Partner journey paths differ from
either HPO or other defined journey paths?
Q. (Data Nuances) Are there any nuances we see in the data based on
filtering and/or campaign or channel attribution, and which needs to be
analyzed deeper?
Q. (Insights) What are the key actionable insights identified?
Q. (Insights) Are there areas of strategic execution which could be
enhanced?
Q. (Next Steps) Does this analysis review require further analysis? Do we
need to apply a different analytical lens for deeper insights?
Q. (Next Steps) Are there missing data points? If so, where can we access
any missing data? How can we leverage data analysis for greater
program performance?

WORKSTREAM & PROCESS
Phased analysis and reporting.

Our process aims to isolate distinct user journey paths per the scope of the analysis, which we will conduct in three separate
analyses.
 Phase 1: Attribution and journey analysis by defined filtered geographies.
Metro (DMA) geo filters applied by DV Clinic and HPO geographies where they are physically present.
 Phase 2: Attribution and journey analysis by campaign filtered UTM tagging.
UTM campaign/source/medium filters applied as implemented for DV and HPO campaign attribution.
 Phase 3: Cross tabulation hybrid analysis by filtered views.
Cross-tabulated filtered views compared to determine best future analytical model approach.
Process: Analysis Levels

Of special note, geo filtering attribution assumes no other touchpoint was present in the defined geography which
could have been the primary, single or assisted catalyst for a site visit or conversion.
To make the assumption all activity by geography is attributable to the partner under review would be inaccurate, but it
remains to be a limitation for the desired geo data filtering analytics direction.
Conversely, UTM attribution is much more closely aligned to reality but also has limitations for technical and applied use.
Therefore, neither direction should be considered absolute, but together they can provide degrees of insights to steer future
program execution.
Phase 3 will seek to create a hybrid model by identifying nuances and to determine the best analytical model and
approach going forward.
Process: Geo-Modeling (Filtering)

The U.S. metros and cities identified with DV Clinic presence and to be analyzed include:
Process: DV Partners Geo-Filtering
Geo Filter Location
Metro Albuquerque-Santa Fe NM
Metro Baltimore MD
Metro Baton Rouge LA
Metro Casper-Riverton WY
Metro Charlette NC
Metro Greensboro-High Point-Winston Salem NC
Metro Houston TX
Metro Las Vegas NV
Geo Filter Location
Metro Memphis TN
Metro Nashville TN
Metro Phoenix AZ
Metro Raleigh-Durham (Fayetteville) NC
Metro Sacramento-Stockton-Modesto CA
Metro San Diego CA
Metro Seattle-Tacoma WA
Metro Washington DC (Hagerstown MD)
Note: tracking metros and cities represented above submitted by Scripps and as segmented using a DV Clinic Metros filter built by
Vibrent. Does not include MEA2 metros. (MEA tour stops and other regions may be added in the future.)
DV Outreach &
Enrollment Partners
BCBSA
(TX, NM, LA)
BCBS Regence CBBC SDBB Walgreens WebMD MEA2
EMSI (CPGI) QTC Leidos (CP) Quest (CP) DMV (TPC) Scripps Media (Media Planet) Scripps Media (Houston Research)

Our prime objective is to cross-tabulate and compare like attribution data patterns using geo-filters as the common
dimensional view. Therefore, the U.S. regions with HPO presence identified and to be analyzed include:
Process: HPO Geo-Filtering
Consortium Type DMA Market (GA Metro Filter)
Arizona/Banner HPO Yuma AZ-El Centro CA - Tucson (Sierra Vista) AZ - Phoenix AZ
Calif. Precision Medicine HPO
Sacramento-Stockton-Modesto CA - San Francisco-Oakland-San
José CA - Los Ángeles CA
Illinois Precision Medicine HPO
Chicago IL - St. Louis MO - Champaign & Springfield-Decatur IL -
Quincy IL-Hannibal MO-Keokuk IA - Peoria-Bloomington IL -
Davenport IA-Rock Island-Moline IL
New England Consortium HPO
Albany-Schenectady-Troy NY - Providence-New Bedford, MA -
Boston MA-Manchester NH - Portland-Auburn ME
New York Consortium HPO New York NY - Philadelphia PA
Southeast Enrollment Center HPO
Augusta GA - Atlanta GA - Greenville-Spartanburg-Asheville-
Anderson - Chattanooga TN - Macon GA - Savannah GA - Albany
GA - Dothan AL - Jacksonville FL - Tallahassee FL-Thomasville
GA - Panama City FL - Gainesville FL - Tampa-St. Petersburg
(Sarasota) FL - Orlando-Daytona Beach-Melbourne FL - Miami-Ft.
Lauderdale FL - Ft. Myers-Naples FL
Southern Consortium HPO
Huntsville-Decatur (Florence) AL - Nashville TN - New Orleans LA
- Baton Rouge LA - Montgomery-Selma, AL - Columbus GA -
Birmingham (Ann and Tusc) AL - Meridian MS - Columbus-Tupelo-
West Point MS - Greenwood-Greenville MS - Jackson MS -
Hattiesburg-Laurel MS - Monroe LA-El Dorado AR - Mobile AL-
Pensacola (Ft. Walton Beach) FL - Biloxi-Gulfport MS
Of special consideration, state regions with no DV or HPO presence include: (19) Alaska, Colorado, Delaware, Hawaii, Indiana, Iowa, Idaho,
Kentucky, Kansas, Missouri, Montana, Nebraska, Ohio, Oklahoma, Oregon, South Dakota, Utah, Vermont, West Virginia.
Consortium Type DMA Market (GA Metro Filter)
Trans American
Health (TACH)
HPO
Sherman-Ada, OK - Amarillo TX - Tyler-Longview(Lufkin &
Nacogdoches) TX - Dallas-Ft. Worth TX - Wichita Falls TX &
Lawton OK - Abilene-Sweetwater TX - Waco-Temple-Bryan TX
- San Angelo TX - Houston TX - Austin TX - Duluth MN-Superior
WI - Minneapolis-St. Paul MN - Fargo-Valley City ND - Detroit
MI - Lansing MI - Springfield-Holyoke MA - Grand Rapids-
Kalamazoo-Battle Creek MI - Traverse City-Cadillac MI
UPMC - PA Cares HPO
Pittsburgh PA - Johnstown-Altoona-State College PA - Erie PA -
Youngstown OH - Buffalo NY - Elmira (Corning) NY
Wisconsin
Consortium
HPO
La Crosse-Eau Claire WI - Milwaukee WI - Madison WI -
Wausau-Rhinelander WI - Green Bay-Appleton WI - Rockford IL
CHC Inc FQHC Hartford & New Haven CT
Cherokee FQHC Knoxville TN
Eau Claire FQHC Columbia SC
HRHCare FQHC New York NY - Albany-Schenectady-Troy
San Ysidro FQHC San Diego CA

Process: Applied Metro Filters and Overlap
Applied Metro Filters
Legend
 DV Metro
 HPO Metro
OVERLAP metros include Houston, Phoenix, Sacramento and San Diego.
Combined Populations
187,231,950
--
African-American
35,916,863
--
Hispanic-Latino
38,580,907
--
Asian-American
13,341,369
--
Pacific-Islander
518,893
--
Caucasian
125,556,098
NATIONAL REACH
DV 11% - HPO 46%
DV Metro Population Reach: 34,726,920 . HPO Metro Population Reach: 152,505,030
[ 2019 United States Population Estimate: 328,919,763 ]

GOAL ALIGNMENTS
Mapping the analysis to program strategy and goals.

Goal Alignments: Who Are Our Audiences
Source: AOU Communications Strategy: June 2017
• Consortia & corporate partners
• Those who enroll and/or recruit
Providers
Those who will use the collected data
Researchers &
Clinicians
Congress
Policymakers
• 1 out of 4 need to be a person of color
• 3 out of 4 need to be UBR
Potential Participants
For all marketing communications purposes, the prime emphasis is on potential participants.
Baseline Reference

Potential Participants Providers Researchers & Clinicians Policymakers
• Paid Media
• Digital
• Print & Outdoor
• Owned Media
• Websites
• Social Media
• Email Campaigns
• Earned Media
• Press
• Bloggers
• TV + Radio PSAs
• Social Shares
• Sponsored Events
• Community Engagements
• Social
• Press/Earned Media
• Email via associations or list rentals
• Events
• Community Engagement
• Partner Platform
• Website
• MedScape Website
• Allofus.nih.gov
• Social
• Email
• Events/Conferences
• Training tools
• Website
• MedScape Website
• Allofus.nih.gov
• Social
• Events
Goal Alignments: What Are Our Channels
CHANNEL LANDSCAPES WORKING IN TANDEM
• Website
• Allofus.nih.gov
Baseline Reference

Goal Alignments: A 360 Approach to Participant Recruitment
Media Channels
Social
Paid
Press
TV
Radio
Online
Print
Outdoor
Owned Channels
AOU Website
AOU Email Sign Up
AOU App
RMC Channels
Websites
Provider Offices
Events
Email Databases
Grassroots Channels
Faith Based and Community Orgs
Advocacy Organizations
Events
Mobile Unit
Web and Email
Corporate Channels
Walgreens + WebMD
Emails
Banner Ads
Editorial Content
In-Store (where possible)
Whether a potential participant, a provider, a researcher or a policy maker, the overarching goal is to ensure
communications are presenting multiple opportunities to learn and to enroll.
Baseline Reference
Call Center
Sponsored
Events
Journey
Bus
RMCs
Campaigns

Goal Alignments: What Is Our Message
Digital paid media / Print
outdoor:
● Relatable imagery
paired with targeted
taglines
Social & earned media:
Website:
● Educational content about AoU & precision
medicine
Community events:
Potential Participants
➔ You can trust the All of
Us Research Program
➔ Awareness around the
All of Us brand
➔ Education about
Precision Medicine
➔ Acknowledgement of
past injustices in
research
➔ Importance of diversity
in treatment
➔ Data security
● Building trust
● Faith-centric
● Diversity in
research
● Data Security
● Family
● Community
● Creating connection
through interaction
● Building trust through
community
engagement
● Establishing a lasting
relationship through
consistency
Digital Paid Media / Print Outdoor
● Relatable imagery paired with targeted taglines
Website
● Educational content about AoU & precision medicine
Social & Earned Media Community Events
Baseline Reference
Needs Updated

20
Goal Alignments: What Are Our Enrollment Targets
Total
% Target
Year 1
Enrollment
numbers
NH White 50.0% 10,000
Hispanic 23.0% 4,600
Black / AA 17.0% 3,400
AIAN 0.0% 0
Asian 6.2% 1,240
NHPI 0.8% 160
Other 0.0% 0
2+ race 3.0% 600
Total 20,000
DIRECT VOLUNTEER TARGETS
Diversity targets year 1-5
HPO TARGETS
Baseline Reference

JOURNEY PATHS
A review of variable touchpoint journey paths.

Registration Consent PPI #1 PPI #2 PPI #3 Bio-Samples
Decision Join Enrollment
PM&B Eligible…………………………………………………………………..
Surveys EHR Medical
Enrollment Paths: What Is The Enrollment Path
Enrollment Statuses
• Participant: signed primary consent
• Full Consented: signed primary consent + either HER consent, DV HER “life”, agreeing to share
• PM&B Eligible: fully consented + complete PPI #1 “The Basics” survey
• Core Participant: fully consented + PPI #1, #2, #3 complete + DNA sample for sequencing received at biobank
Baseline Reference
Primary Marketing
Conversion Point
Participant Fully Consented Core Participant

New Salivary Kit DV Path: F2F Meeting: June 13, 2019
Enrollment Paths: What Is The New DV Enrollment Salivary Kit Path Baseline Reference

24
Journey Paths: Discovery & Awareness Touchpoints
What are the touchpoints a candidate can discover the program and gain awareness?
01 Digital Marketing
Advertising, email, social media,
earned media, website promotions.
03 Community
Grassroots channels, web and
email, forums, events, outreach.
05 WOM
Advocacy organizations, trusted
friends, friends of friends.
07 Random Exposure
Online web surfing, broadcast media,
outdoor media and promotion.
02
04
06
Events
Journey bus, sponsored
community events.
Medical
RMC websites, offices, events,
care provider discussions.
Lifestyle
In-store, press and earned
media, social shares, editorial
content, mailing lists, PSAs.
Baseline Reference

25
Journey Paths: Consideration Touchpoints
What are the touchpoints which keep the program top of mind and which a candidate can learn about the program?
CONSIDERATION
TOUCHPOINTS
Digital Marketing
Advertising, email, social media,
testimonials, CTAs.
Community Engagement
Grassroots channels, web and
email, forums, events, outreach.
Events
Journey bus, sponsored events.
Medical
RMC websites, offices, events,
care provider discussions.
WOM
Advocacy, trusted friends,
friends of friends.
Lifestyle
Press, blogs and earned media, social and
editorial content, direct mail, PSAs.
Self Proactivity
Website, call center.
Baseline Reference

26
Journey Paths: Enroll/Consent Touchpoint Options
What are the ways a candidate can create an account and start the enrollment process?
Self Guided
Interested person
elects to sign up online
without assistance.
Special Event
Interested person
signs up at a special
event.
MEA Journey Bus
Interested person
signs up at a journey bus
tour stop.
A
Option
HPO Direct Assist
Interested person
has HPO guide them
through the signup
process.
B
Option
C
Option
D
Option
Baseline Reference

Journey Paths: A Holistic Variable Touchpoint Journey Path
D
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s
O
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t
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Content Sharing
Organic Search
Website Content
Partner
Touchpoints
News/Influencer
3rd Party Sites
Earned Media
Partner Direct
Assist Engagements
Self Guided
Website Consent
& Full Enrollment Path
Community Forum
IM/Chat
Biosamples
FAQ
Knowledge Base
& Health Sharing Tools
Call Center
Testimonials
Social Networks
Newsletter
National + Partner
Email Retargeting
Channel CTAs
AOU Landing Page
Email
Social Engagements
News Feed Content
AOU Return Visits
Email Subscribe
Social Media Follow
Press
Media
In-Store, Special Events
& Journey Bus Tour
Advocacy &
Word of Mouth
Social Media &
Groups/Forums
Partner &
Community
Engagements
Display +
Social Ads
Other Ad Channels
Radio, TV, Print, Outdoor Ads
Added Media Impressions
Partner Websites
MEA Journey
& Special Events
Community
Grassroots
Advocates
Call Center
Social Networks
Q1 2019 Benchmark Review No touchpoint is a silo. Each channel and touchpoint (in combinations) are dependent on each other to deliver a holistic user journey experience.
Baseline Reference
What are the variable touchpoints throughout the user experience journey?

28
Journey Paths: What A Participant Journey May Look Like
Events Community
Medical Media
Eager to get started, Edgar
begins enrollment process
As one possibility, these are the touchpoints (channels) that Edgar (Persona 1) may encounter along his enrollment journey.
Edgar talks to
AoU rep at AoU
booth at blood
drive
Feels hopeful
Wow! This seems
amazing, exactly what
should be done to help
people.
Using tablet, rep
shows Edgar AoU
videos
Edgar asks rep
questions
Feels eager
While Edgar recovers from donating at a
blood drive, phlebotomist gives him AoU
Research Program brochure.
DISCOVER CONSIDERATION ENROLL/CONSENT
Edgar’s motivation to participate: help kids and grandkids
(his own and the world’s).
Edgar enrolls with AoU rep at
blood drive and, after lunch date,
completes PPI at home.
Those answers make
sense. It feels right. I’m
ready to be part of this.
Sign me up!
At blood drive, uses tablet
to enroll and sign consent
At home, uses desktop to
complete PPI
Edgar Persona
Baseline Reference

SECTION ONE
OUR JOURNEY STORY

KEY FINDINGS

 Legacy site visit to conversion ratios (15.2% average) are performing extremely well for the program.
 Individual DV and HPO account conversion counts are comparative to one another respective to partner market population reach.
 DV impact on site traffic outpacing HPO influence.
 Channel traffic is aligning to expected channel performance and influence within the pre-consent touchpoint journey. Channel touchpoints do align to
expected journey path influence for traffic, single page visits (bounces), page content consumption, time on site, and conversion counts.
 Nuances do exist based on user type visit. Large percentages of account conversions require successive site visits over successive days. Return visit
conversion ratios (17.5%) are much higher compared to new visit ratios (7.9%).
 Page Navigation: visitors are largely making an enroll/consent decision based on landing page content and information as they are not navigating deep
into the interior website content pages.
 Only 13% of new user visits navigate to a second page and a mere 5% to a third page on a first website visit. Return users are generally more engaged:
27% navigate to a second page, 10% a third page.
 When interior page content is consumed, the information deemed most valuable for a decision are content pages explaining How to Join, Who Can Join
and the FAQs. Deeper value proposition information content pages; About and Program Overview, represent only 1.5% of all time period pageviews
representing the content on the main landing page is delivering sufficient program information for people to begin the consideration process without the need for
expansive information.
 HPO conversion rates outpace DV conversion rates (likely directly attributable to the HPO assisted journey path as anticipated).
 Over saturation of select metro markets may be overshadowing larger population pools across more expansive urban, suburban and rural national
regions. (10) metros constitute 60% of all conversions within Q1 2019. DV + HPO combined geographies (187M) extend reach to only 57% of 2019 national
population estimate.
Top Key Findings / Takeaways (common truths)

 National Quality Ratio average of 84% (consents/accounts) demonstrates the high quality of the prospects being recruited into the program.
 Gender and age program engagement predisposition is being demonstrated: females over males and older (55+) generations.
 Mobile platforms are the predominant platform of choice and requires re-consideration for a mobile first site design.
 DV conversion counts appear to be surpassing Year One target enrollment goals. HPO conversion counts appear to be underperforming to Year One
apportioned (5) year goals. (Based on Registrations and not full enrollment.)
Top Key Findings / Takeaways (common truths)

LEARNINGS & TAKEAWAYS

 Website Traffic Acquisition
o State website traffic attribution is aligning to partner physical locations and active campaigning. National marketing is supporting partner geographies as
well as having reach into gap state regions. (reinforces marketing coverage across all 50 states)
o DV traffic attribution accounts for 30% of all site traffic (31% of all new traffic) with a 19% comparative market population reach (35M) in national
metropolitans where DVs and HPOs have a presence (187M). (reinforces DV influence and impact on program awareness)
o Channel traffic is aligning to the expected pre-consent touchpoint impact journey. Digital media is by far the leading channel for creating program
discovery, awareness and website traffic across all campaigning, channels and geographies. (reinforces media is a prime channel for creating awareness
and interest at scale)
o (37%) Display: discovery, awareness and interest; first click
o (18%) Social: awareness, interest and consideration;
first, second or successive click
o (9%) Referral: awareness, interest and consideration;
first, second or successive click
o (7%) Email: consideration and purposeful intent;
second, successive or last click
o (6%) Search: consideration and purposeful intent;
o (20%) Direct: consideration and purposeful intent;
o Houston, New York and Los Angeles are the three largest metros for site traffic. (reinforces campaign influence & impact on regional populations)
Q1 2019 Quarterly Benchmark Insights & Learnings (common truths)
Second, Successive, Last Click
Consideration & Purposeful Intent
.
First Click
Discovery, Awareness & Interest
First or Successive Click
Awareness, Interest &
Consideration.
Awareness, Interest & Consideration.
Consideration & Purposeful
Intent
Direct Display
Email Referral
Social
Search
-----
GA
Channel
Traffic
Attribution
---

 Account Conversion
o There is a direct correlation to accounts created and the continuous need for new site visitors. (reinforces daily new site traffic is paramount to success)
o The (DRC) lifetime 15.2% conversion rate average (accounts created/visitors) represents an outstanding conversion ratio and further represents the high
quality of the site visitor leads clicking through and coming to the website. (reinforces landing pages, overall web design and messaging are delivering
results with special consideration average could be artificially inflated from assist enrollment paths)
o Account conversion percentages are much higher on a return visit (17.5%) than first visit (7.9%) representing larger numbers of people require a second
or successive visit to sign up for an account and start the enrollment process. (reinforces need for retargeting and/or multiple impressions early in the pre-
consent user touchpoint path)
o Aligned to market population counts, DV and HPO partners are both performing at proportionate levels for conversion counts (accounts created) as
aligned with their own market reach population densities. (reinforces comparative performance among partners)
o Adjusted total aggregate conversions for the reviewed time period, DV conversions account for 20% of all aggregate (total) conversions and HPOs
account for 91%. (reinforces population reach findings but does represent common overlap and double attribution counting in select metros using geo
filters)
o HPO (GA) average conversion rates (11.2%) are modestly higher than DV peer average conversion rates (7.8%). (suggests assisted journey path impact
and influence)
o (10) metros constitute 60% of all conversions within Q1 2019. (aligns with HPO and DV market presence and large metropolitan population densities and
reinforces partner and campaign influence)
o Of the top national metropolitans for conversions, many key markets are missing from the list. (may suggest over saturation in select markets and regions
with mainstream suburbia and rural America being overshadowed by over emphasizing a number of major metropolitan population centers)
o Channel conversion rates are aligning to the user touchpoint journey and which aligns to site traffic acquisition. (reinforces channel purpose and value for
each touchpoint in the overall pre-consent user journey path)
o DV conversion counts appear to be surpassing Year One target enrollment goals. HPO conversion counts appear to be underperforming to Year One
apportioned (5) year goals. (needs deeper analysis for adjusted counts)

 Consent Completion
o National quality ratio average of 84% (consents/accounts) represents the high quality of leads and the level of commitment people are making to move
into consent and into the full enrollment process once an account has been created. (reinforces program value proposition resonance continues through
to step two (consent) in the enrollment process)
o DV and HPO quality ratios (80% and 85%, respectively) represent quality leads are being acquired across both partner enrollment levels. (further
reinforces value proposition resonance continues through to step two in the enrollment process)

 Site Visit (User) Behaviors
o Site visitors in large percentages are making repeat visits to the marketing site before account creation conversion. (reinforces and re-verifies multi-visit
conversion path insight)
o In aggregate, and across partners especially with DVs, Return Site Visitors on second or successive visits significantly spend more time, consume more
content and convert in higher numbers than first time visits. (reinforces and re-verifies multi-visit conversion path insight)
o + (19%) Sessions per User
o + (187%) Average Session Duration
o - (16%) Bounce Rate
o Return Site Visits are paramount to program success yet only represent 27% of site traffic. (reinforces need for more retargeting and more pre-consent
program touchpoint impressions)
o Return Site Visit percentages for HPOs represent people are returning to the website after a first visit (28% of HPO visits). (reinforces more than one
journey path exists for HPOs beyond the assumed primary direct assist path)
o HPO visitors spend more time and consume more content than DV peer visits (on average 20% more). (suggests assisted journey path impact and
influence)
o + (11%) Pageviews
o + (45%) Pageviews per Session
o + (118%) Account Conversion Rate

 Site Visit (Delayed Conversion Response) Behaviors
o Time Lag and Path Length reports represent the delayed influence for creating an account upon a first site visit. (reinforces large percentages of
people are not converting on a fist click or first site visit)
o Time Lag results reveal 38% or more of visitors converting (creating an account) are doing so days after a first website visit. (reinforces
conversions are occurring over an expanded timeline and further reinforces the need for creating added program impressions after initial awareness)
o 29% of conversions occur 12+ days after a first website visit. (further reinforces just how far out a person is taking to make a final decision)
o Path Length results reveal 44% or more of visitors are requiring multiple site visits (interactions) to create an account. (reinforces two needs: a need
for an integrated and multi-touchpoint strategic marketing path and a more streamlined site and navigation to reduce number of visits)
o 22% of conversions occur after 12 or more visits to the website. (suggests several possibilities: content may not be effective in translating value
proposition quickly and succinctly or the personal decision to enroll is requiring deeper consideration and a longer timeline not anticipated)
o Overall insights reveal large percentages of people do not convert on the first website visit and multiple program impressions, touches and website
visits are required for a conversion. (further reinforces need for retargeting throughout the pre-consent journey path)
o Insights also reveal the trending pattern is consistent across all channels. (reveals delayed response trending pattern is independent of channel
touchpoints and when touchpoints are encountered)

 Site Visit (Geography) Behaviors
o The Top (5) states in aggregate for conversion align to the leading HPO states for conversion respectively: California, Arizona, Pennsylvania, New York
and Illinois, respectively. (represents strong HPO presence and influence)
o Comparing the Top (5) states for conversion in aggregate versus the top DV (5) states for conversion: Arizona, California, Texas, Virginia, Tennessee.
(represents common HPO regional overlap influence and which may result in a different view with campaign attribution filters)
o Eight (8) common national metros represent the top website traffic cross-tabulated by account conversion for both new and return visits. They include:
Pittsburgh, New York, Los Angeles, Chicago, Birmingham, Boston, San Diego, and Phoenix. Phoenix and San Diego metros are overlap markets. Other
six metros are HPO locations. (reinforces physical presence and assisted journey path influence)
o Based on conversions only, New York, Phoenix, Pittsburgh, Los Angeles and Boston represent the Top 5 national metros for account signup conversions.
Phoenix metro is an overlap market. Other four metros are HPO locations. (reinforces physical presence, medical care trust, assisted journey path
influence)

 Site Visit (User) Attributes
o Site traffic largely correlates to state population densities. As expected, heavier state traffic aligns with active national and partner campaign marketing
support. (reinforces campaign targeting emphasis)
o Greatest number of return visitors are coming from California, Texas, Arizona and New York, respectively ranked. (aligns with active campaigning and
suggests more retargeting is needed to enhance other state number counts)
o Demographics: (in lieu of Lotame audience profile tracking, demographics reinforce need for deeper analysis cross tabulated against DRC data to explain
differentiation)
1. Gender: female over male predominance. Elderly 65+ most engaged audience.
2. Young adults (18 to 24) least engaged audience.
3. Program resonating with older (55+) audiences especially among women.
4. Older millennials (25-34) firmly engaged.
o Marginal (2%) Spanish language use as reported by sampled Google Analytics data. Spanish language use concentration aligned within states with large
populations and Hispanic community sub-populations. (reinforces need to activate the at large Spanish community in larger numbers)

 Device & Platform Use
o Mobile is the predominant platform device of choice across all age groups for both new and return visits. However, desktop use does increase 2x to 3x
with return visits. Tablet use marginal at 3 percent. (high mobile use percentage counts need further verification but a mobile first design approach is
becoming critical for an enhanced UX)
o User behaviors differ based on device across all acquisition sources. Both DV and HPO audiences see the highest conversion counts for Accounts
Created on desktop. (suggests screen size does matter based on site engagement stage but also suggests lost conversions for those people who are
mobile only)
o The bounce rate for DV audiences is lowest on desktop and highest on mobile. (reinforces screen size dependencies and a need for a mobile first site
design for the audience we are reaching who are predominantly mobile first or mobile only)
o Extending on the need for a mobile first design, there is also a need to balance optimization across device platforms. (reinforces site should always be
platform agnostic and be highly functional regardless of device or platform)
o Reviewing mobile OS and browsers, Chrome and Safari (iOS) use create longer session duration times, lower bounce rates and have the highest
conversion rate among reviewed browsers across all audiences. Android underperforms significantly. (reinforces a specific need to optimize for Android
devices)

 Site Navigation
o Overall, nothing out of the ordinary for people arriving at the site.
o As expected, the primary English language home page is predominantly the main landing page.
o The Participant login page is the second most landing page used. (indicates high levels of active enrollee return users to the site)
o There is high landing page traffic to the Getting Started and Register pages. (demonstrates an active return user path for people moving into enrollment
process)
o New user landing pages including destinations to the participant portal logically do not align to a first time visit. (anomaly may be impacted by HPO assist
paths or may be a GA anomaly, but needs deeper review and analysis)
o Other new visits can be seen arriving at either the main home page or partner landing pages. (reinforces traffic is successfully being created via campaign
activities)
o Return users in reasonably large percentages are arriving at enrollment step page destinations (6 out of 10 Top 10 landing pages). (reinforces return
users are revisiting with specific intent and purpose)
o Page Navigation: visitors are largely making an enroll/consent decision based on landing page content and information as they are not navigating deep
into the interior website content pages. (reinforces landing page is delivering sufficient content to explain the program)
o Only 13% of new user visits navigate to a second page and a mere 5% to a third page on a first website visit. Return users are generally more
engaged: 27% navigate to a second page, 10% a third page. (reinforces the unique user paths based on new versus return visit)

 Site Navigation
o When interior page content is consumed, the information deemed most valuable for a decision are content pages explaining How to Join, Who
Can Join and the FAQs. Program value proposition information content pages; About and Program Overview, represent only 1.5% of all time period
pageviews representing the content on the main landing page is delivering sufficient program information for people to begin the consideration process
without the need for deeper information. (highlights the content of highest value within the decision making process)
o Channel touchpoints do align to expected journey path influence for traffic, single page visits (bounces), page content consumption, time on
site, and conversion counts. (verifies channel purpose, placement and value in the touchpoint user journey but also reinforces need to modify GA
attribution model)
o Overall, insights reveal the need to strategically develop programs and campaigns designed to help increase return site traffic and to stimulate
advancement into the enrollment process.

ACTIONABLE INSIGHTS

o A/B Testing: Landing Pages
- Split-level conversion testing for landing page
content density.
- 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.
- 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.
- Implement insights from earlier survey data that
may have key insights into landing page creation
for optimal demographics targeting, copy creation
and imagery.
o A/B Testing: Site Navigation
- Content page user path testing based on high
valued content
o A/B Testing: Weekend Performance
- Social media posting
- Banner advertising impressions
- Email publishing
Q1 2019 Quarterly Actionable Insights (Recommendations)
o Site Optimization: Mobile First Design
- Site optimization reconsideration.
- Android platform and Safari (in-app) browser
optimization.
o Site Optimization: Content
- Consider varying video and thumbnail preview
locations throughout each landing page with
media content to test for conversion optimization.
- 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.
o Retargeting: Return Visitors
- Greater planning and retargeting across all
channels and journey path stage levels.
- 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.
o Bounce Rates
- Adjust the Google default configuration bounce
rate. Apply a ‘time out’ formula to better represent
a true bounce.
- Review backlinking practices to content pages to
ensure alignment with destination linked pages to
reduce bounce rates.
o Email
- 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.
o Journey Paths
- 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.
o Greater Spanish Activations
- Consider the impact of designing specific
culturally correct Spanish landing pages and
Spanish content pages for Hispanic heritage self
identification.
o Benchmarking
- Use 2018 as a benchmark period. Begin applying
monthly or quarterly KPI Milestone performance
goals to drive overall strategic execution.

SECTION TWO
MEASUREMENT & ANALYSIS

BENCHMARKS
(Perspective) Year One: milestone measurements.

Lifetime Enrollment Counts
DRC Dataset: as Tracked and Reported by Sage Bionetworks.
 Good conversion performance with highs and lows per
any given month with an overall upward trendline.
 Quality Ratio (consent completion ratio) remains steady
month over month with an 83 percent overall average.
 Quality ratio reaffirms when people make the personal
decision to create an account, they are following
through in high numbers to complete the Consent
process.
 Quality ratios reveal we are securing quality prospects
(leads) via our marketing channels and program events.
 Objective moving forward:
Build and reinforce a consistent daily stream of new
and return website traffic to fill the top of the funnel.
193,168 Accounts Created . 160,150 Consent Completions . 83% Avg. Quality Ratio
Pre-Launch Friends Launch & Post-Launch Ramp Holiday Slowdown New Year Ramp
Time Period: Historic (Jan. 1, 2018 thru Mar. 31, 2019)

Conversion vs. New User Site Visits
DRC Dataset: as Tracked and Reported by Sage Bionetworks.
Blended DRC Dataset + GA View: 176339261
 There is a strong correlation to the number of new site
visitors to conversions.
 A continuous stream of daily new website traffic is
paramount to program success. We must continue to
fill the top of the funnel.
 All marketing touchpoints, channels and partners need to
be driving traffic to the enrollment website.
 Weekends may be a missed opportunity to enhance
weekly site traffic, engagements and conversions.
 Many of our marketing programs are scaled back over
the weekends with the belief that personal internet use is
less on Saturdays and Sundays.
 As one example, statistics actually reveal the best time to
post on many social networks is during the weekend.
 In general, weekends are a prime time people have more
time to consider their personal values and needs.
 Scaled A/B campaign testing may be warranted to test
whether more engagement activity can be created on the
weekends for greater performance.
Q1 2019 Daily Conversion Patterns Showing Valleys As Weekends
1,046,400 New User Visitors . 193,168 Accounts Created . 83% Avg. Quality Ratio

Average Conversion Rates (CVR)
Conversion Rate (CVR): accounts created / users visits
Blended DRC Dataset + GA View: 176339261
18.5% Avg. Conversion Rate . 193,168 Accounts Created . 83% Avg. Quality Ratio  Conversion rates are impressive (even on the low end)
for a medical research initiative like the All of Us Research
Program.
 Data analysis reveals there is a monthly fluctuation in
our conversion rate.
 Over the last six months, we are experiencing a
downward sloping trendline as the number of new site
visits increase.
Over time and as program awareness grows, a
downward conversion rate trendline is not
uncommon.
It is a natural occurrence in an evolving and dynamic
journey path as larger numbers of people gain
awareness, show interest and gather information.
 Net result: what do our conversion rates tell us?
1. We must have a continuous stream of daily new
site visitors to fill the top of the funnel and to increase
enrollment numbers.
2. Site visitors are indeed finding information they
need to enroll in the program.

 Highs and low in any given month with an upward
trendline in the new year.
 Return visits improving and represent a steady flow of
overall traffic, yet we would like to see this as a greater
percentage as its linked to enrollment patterns.
 Notable Influential Campaigns:
o National & Cobranded media campaigns
o National email marketing retargeting
o Consortium-wide social media communities
o DV & HPO Partner marketing campaigns
o Houston regional campaign (Oct. – Mar.)
 State traffic aligns with campaign marketing support
(national & partner) across all 50 states.
Time Period: Historic (Jun. 1, 2018 thru Mar. 31, 2019)
GA View: 176339261 (unfiltered view) Website User Visits Representation
1,223,124 Total Site Visits . 938,217 New Visits (77%) . 284,907 Return Visits (23%)
Website Visits (Aggregate Baseline)

 Evolving upward trendline into the new year.
 DV geographies represent 31% of overall new visitor
site traffic and 27% of all return traffic.
 As with the aggregate view, return visits represent a steady
flow of traffic, yet we would like to see this as a greater
percentage as its linked to enrollment patterns.
 Notable Regional Marketing Activity:
[25% of all attributable regional site traffic]
o DV Partner digital media campaigns (Jun. – Mar.)
o National digital media campaign (Jun. – Mar.)
[30% of all attributable regional site traffic]
 State traffic aligns with DV presence with some HPO
overlap; Houston, Sacramento, Phoenix, San Diego.
DV Website Visits (Geo Attribution)
368,509 Total Site Visits . 291,492 New Visits (79%) . 77,017 Return Visits (21%)
[ 30% Overall Site Traffic – 31% Overall New Visit Traffic – 27% Overall Return Traffic ]
Geo-filtering may inflate partner attribution user traffic by approximately 30 percent due to common overlap.

 Significant upward trendline into the new year.
 HPO geographies represent 76% of overall new visitor
site traffic and 84% of all return traffic.
 Return visits improving and represent a steady flow of
traffic aligning with enrollment trends.
 Notable Regional Marketing Activity:
o HPO Partner marketing campaigns (Jun. – Mar.)
o National digital media campaign (Jun. – Mar.)
 State traffic aligns with HPO presence with some DV
overlap; Houston, Sacramento, Phoenix, San Diego.
HPO Website Visits (Geo Attribution)
[ 78% Overall Site Traffic – 76% Overall New Visit Traffic – 84% Overall Return Traffic ]
Geo-filtering may artificially inflate attribution user traffic by more than 30 percent due to common overlap.

TRAFFIC ACQUISITION
Q. (Attribution) What does attribution look like for website traffic?

 Generally an upward trendline in the new year.
 Return visits improving month over month.
o National & Cobranded media campaigns
o DV & HPO Partner marketing campaigns
o Houston regional campaign (Jan. – Mar.)
 State traffic aligns with all campaign marketing support
(national & partner) across all 50 states.
User Visits Traffic (Aggregate Baseline) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)

 Mirrors upward aggregate trendline in the new year.
o DV Partner marketing campaigns
o Houston regional campaign (Jan. – Mar.):
large influence
o National media campaigns
(national & partner) across DV states.
DV User Visits Traffic (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)

 Mirrors DV upward partner trendline in the new year.
o HPO Partner marketing campaigns
o Houston regional campaign (Jan. – Mar.):
large influence
o National media campaigns
(national & partner) across HPO states.
HPO User Visits Traffic (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)

GA View: 176339261 (unfiltered view)
Metro Sessions Traffic (Aggregate Baseline)
Website Sessions Representation
Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
500,518 Total Site Visit Sessions
Metro Traffic Attribution
Largely consolidated across (15) fifteen metropolitan areas.
The Top (5) metros for website traffic and sessions include:
Houston, New York, Los Angeles, Chicago, and Boston.
Metro Filter Sessions
Houston TX 54,389
New York NY 43,646
Los Angeles CA 32,201
Chicago IL 27,230
Boston MA-Manchester NH 21,446
Pittsburgh PA 20,619
Atlanta GA 19,076
Phoenix AZ 18,932
Dallas-Ft. Worth TX 18,419
Washington DC (Hagerstown MD) 15,640
San Diego CA 15,227
Tulsa OK 15,044
Detroit MI 13,254
Birmingham (Ann and Tusc) AL 12,600
Sacramento-Stockton-Modesto CA 11,030
Miami-Ft. Lauderdale FL 9,654
Houston
Phoenix
Washington DC
Dallas-Ft. Worth
New York
Los Angeles
Chicago
San Diego
Pittsburgh
Atlanta
Boston

DV Sessions Traffic (Geo Attribution)
Largely consolidated across (5) five DV metro areas with
Houston outpacing all others, the bulk of website traffic and
sessions include:
Houston, Phoenix, Washington DC, San Diego,
Sacramento.
Houston TX 54,389
Phoenix AZ 18,932
Washington DC (Hagerstown MD) 15,640
San Diego CA 15,227
Seattle-Tacoma WA 4,292
Nashville TN 2,799
Raleigh-Durham (Fayetteville) NC 2,108
Charlotte NC 2,067
Memphis TN 1,832
Albuquerque-Santa Fe NM 1,045
Baltimore MD 897
Baton Rouge LA 739
Greensboro-High Point-Winston Salem NC 299
Las Vegas NV 152
Casper-Riverton WY 19
Houston
Phoenix
Washington DC
San Diego
Sacramento
Houston, Phoenix, San Diego and Sacramento are common partner overlap
areas which do impact actual attribution counts represented.

HPO Sessions Traffic (Geo Attribution)
HPO attribution is much more spread out than DV metros.
Of the 83 defined HPO metros, the top 10 metros constitute
65% of all geo-attributed website traffic and sessions.
Houston TX 54,389
New York NY 43,656
Los Angeles, CA 32,201
Chicago IL 27,230
Boston MA-Manchester NH 21,446
Pittsburgh PA 20,619
Atlanta GA 19,076
Phoenix AZ 18,932
Dallas-Ft. Worth TX 18,419
San Diego, CA 15,227
Detroit MI 13,254
Birmingham (Ann and Tusc) AL 12,600
Miami-Ft. Lauderdale FL 9,654
San Francisco-Oakland-San Jose CA 9,514
Other 68 HPO Metros 99,410
Houston
Phoenix
San Diego
Dallas-Ft. Worth
New York
Los Angeles
Chicago
Boston
Pittsburgh
Atlanta

Sessions Rankings Comparison (Geo Attribution)
Of the 93 defined partner metros, the top 10 constitute 65%
of all geo-attributed website traffic and sessions. Within
those Top 10, seven are HPO only metros; one is DV only;
and two metros are overlap markets.
Metro Filter Partner Sessions
Houston TX Overlap 54,389
New York NY HPO 43,656
Los Angeles, CA HPO 32,201
Chicago IL HPO 27,230
Boston MA-Manchester NH HPO 21,446
Pittsburgh PA HPO 20,619
Atlanta GA HPO 19,076
Phoenix AZ Overlap 18,932
Dallas-Ft. Worth TX HPO 18,419
Washington DC (Hagerstown MD) DV 15,640
San Diego, CA Overlap 15,227
Detroit MI HPO 13,254
Birmingham (Ann and Tusc) AL HPO 12,600
Sacramento-Stockton-Modesto CA Overlap 11,030
Miami-Ft. Lauderdale FL HPO 9,654
Other 77 Additional Metros Both 93,284
Houston
Phoenix
Washington DC
Dallas-Ft. Worth
New York
Los Angeles
Chicago
Boston
Pittsburgh
Atlanta

Default Channels Sessions (Aggregate Baseline)
Understanding Our Default Channels
 In aggregate, Display advertising (in large part due to
the national media campaigns) is the clear top
marketing channel for creating site traffic and sessions.
 Direct is a combination of visitors coming directly to the
website. It also includes any visit which Google
Analytics cannot determine a traffic medium.
 Social media ranks high over the time period as a
result of all consortium social online activity. Social
media’s attributed site traffic may be underreported due
to GA misclassification.
 Referral traffic is direct backlink clicks coming from a
variety of third-party and partner websites, including
NIH.gov.
 Email represents click traffic coinciding with newsletter
and email publishing schedules from national and
partner efforts.
 Organic Search is minimal but steady representing
general awareness is evident but can be improved
across all population groups.
 Other is the ‘catch all’ default channel which includes
any visit where Google Analytics can not determine a
source.
.
First Click
Consideration.
Intent
Consideration.
Intent
Direct Display
Email Referral
Social
Search

Channel touchpoints can shift within the journey path depending on an individual’s stage of engagement.
Where Do Channels Routinely Fit Into The Pre-Consent Journey Path?
Display Social Referral Email Search Direct
AWARENESS &
INTEREST
Discovery &
First Site Visit
AWARENESS &
CONSIDERATION
First or
Successive Site
Visit
AWARENESS &
CONSIDERATION
First or
Successive Site
Visit
RETARGETING &
CONSIDERATION
Successive Site
Visit
SPECIFIC INTENT
& PURPOSE
First or
Successive Site
Visit
SPECIFIC INTENT
& PURPOSE
Successive Site
Visit
No channel is a silo and when working together each channel serves a unique purpose.

DV Default Channels Sessions (Geo Attribution) v1
Channel Traffic Attribution Ranking
 #1 Display (discovery and first site visit) reveals digital
media is achieving its purpose for creating awareness
and site traffic.
 #2 Social media (first or successive visit) shows
notable influence as a high number of people are
consuming social content and messaging.
 #3 Direct (successive site visit) represents visitors are
showing intent at modest levels for revisiting the
website after initial awareness.
 #4 Referral (first or successive site visit) is a steady
source of partner website backlink traffic from initial or
secondary program digital impressions.
 #5 Email (successive site visit) represents retargeting
click traffic from national and partner email publishing
schedules.
 #7 Organic Search (successive site visit) represents
visitors are showing levels of consideration intent after
initial awareness.
Intent
.
First Click
Discovery, Awareness &
Interest
Consideration.
Intent
Direct Display
Email Referral
Social
Search

GA View: 176339261 (unfiltered view) Website Sessions Representation
Default Channel Traffic Trends
 Overall, a high degree of peaks and valleys across all
channels.
 Houston regional campaigns stimulating majority of
site traffic attribution.
 Display, social and email peaks correlate to
heightened campaign activity across four metros:
Houston, Phoenix, Washington DC and Sacramento.
 Direct, referral and search provide a steady stream of
new daily website traffic.
DV Default Channels Sessions (Geo Attribution) v2

Channel Traffic Attribution Ranking
 #1 Display (discovery and first site visit) reveals digital
media is achieving its purpose for creating site traffic
through initial awareness. Further reinforces multiple
HPO journey paths beyond the assisted path.
 #2 Direct (successive site visit) represents visitors are
showing intent for revisiting the website in large
numbers after initial awareness. Could be influenced
via an assisted journey path.
 #3 Social media (first or successive visit) shows a
high number of people are being exposed to social
content and messaging.
 #4 Referral (first or successive site visit) is a steady
source of partner website backlink traffic from initial or
secondary program digital impressions.
 #5 Email (successive site visit) represents retargeting
click traffic from email publishing campaigns.
 #6 Organic Search (successive site visit) reveals
levels of consideration intent after initial awareness.
HPO Default Channels Sessions (Geo Attribution) v1
Intent
.
First Click
Discovery, Awareness &
Interest
Consideration.
Intent
Direct Display
Email Referral
Social
Search

Default Channel Traffic Trends
 Overall, fewer peaks and valleys across channels
compared to DV metros.
 (7) metros including Houston, New York, Los
Angeles, Chicago, Boston, Pittsburgh and Atlanta
regional campaigns stimulating majority of site traffic
attribution.
 Display, social and email peaks correlate to
heightened campaign activity.
 Direct, referral and search provide a steady stream
of new daily website traffic.
HPO Default Channels Sessions (Geo Attribution) v2

Channels Sessions Traffic Comparison (Geo Attribution)
Default Channels Comparison
 DV vs. HPO partner level channel attribution
percentages for traffic acquisition mirror each other
with one primary distinct difference.
 Direct is more influential for site traffic for HPO
geographies over DV geographies.
The nuance may be in alignment with unique
assisted HPO journey path considerations and
patterns.
Relying more heavily on the assisted path, HPO
Partners are leveraging personal face-to-face
contact to create initial awareness, and reinforce
interest, consideration and enrollment.
In many cases, the HPO Direct traffic attribution
differential when compared with DV metro
geographies is likely a direct result of
organizations providing in-person oversight for
patient enrollments.
.
First Click
Consideration.
Intent
Consideration.
Intent
Direct Display
Email Referral
Social
Search

CONVERSION ATTRIBUTION
Q. (Attribution) What conversions can we track by attribution?

Conversion Counts (Aggregate Baseline)
DV vs. HPO Comparison (Adjusted)
Adjusted counts are aligned to GA under / over-reporting
averages and are within acceptable thresholds.
GA Goal Tracking Representation
Accounts Created Consent Completions Quality Ratio
Google Analytics Counts 56,113 35,100 62%
Adjusted Google Analytics Counts 49,705 40,757 82%
Actual DRC Counts 49,847 41,885 84%
Adjusted
GA Counts
Accounts
Created
Consent
Completes
Quality
Ratio
Population
Percent
Accounts
Share
DV
Partners
9,817 7,893 80% 19% 20%
HPO
Partners
45,305 38,413 85% 81% 90%
Program
Totals
49,847 41,885 84% 100% 100%
Overlap
Delta
+5,275 +4,421 -- -- +10%
GA vs DRC anomalies: Accounts +12.5% over-reporting . Consents -16.2% under-reporting . Adjusted counts margin of error + 1 percent
 Conversion counts and quality ratios reveal a positive
flatline and are reasonably constant across each
month within the quarterly review.
 Would prefer to see an upward trendline month over
month for conversion counts.

Conversion Count Ranking (Aggregate Baseline)
National Metro Conversions (Adjusted)
 Top (10) metros for conversion represent 60% of all
quarterly national program conversions:
1. New York
2. Phoenix
3. Pittsburgh
4. Los Angeles
5. Boston
6. Chicago
7. Birmingham
8. San Diego
9. Tucson
10. Detroit
 Return visits convert at a higher overall percentage
rate compared to new visitors. Represents more
people are converting on their second or subsequent
visit.
[ Conversion Rates: All Visits (10.4%) - New Visits (7.9%) - Return Visits (17.5%) ]

Conversions x States (Aggregate Baseline) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Aggregate Leading Regional Impact
 As expected, state conversion counts represent a
direct correlation and alignment with DV and HPO
presence.
 California and Arizona outpace all 50 states.
 Arizona remains an anomaly. (Needs deeper review.)
Region Adjusted Conversion Rate Adjusted Accounts Adjusted Consents
GRAND TOTAL 10% 49,705 40,756
California 12% 7,612 6,350
Arizona 26% 5,897 6,070
Pennsylvania 18% 4,660 3,912
New York 13% 4,466 3,890
Illinois 14% 3,527 3,060
Massachusetts 17% 3,416 3,136
Texas 4% 3,309 2,064
Alabama 17% 2,970 2,425
Michigan 11% 2,258 1,519
Wisconsin 13% 2,154 1,760
Florida 7% 2,043 1,968
Georgia 5% 1,253 1,020
Tennessee 10% 572 257
Virginia 6% 505 242
Mississippi 11% 483 471
Minnesota 15% 428 323
North Carolina 8% 388 167
Nevada 20% 280 135
Rhode Island 15% 267 35
Washington 6% 261 121

Channel Conversions (Aggregate Baseline)
National Channel Conversions (Adjusted)
NOTE: CONVERSION ATTRIBUTION IS BASED ON A
LAST CLICK ATTRIBUTION MODEL.
Channel conversion counts do not take into consideration
any value on a touchpoint in the journey path prior to the
last click which leads to the conversion.
 Channels do align to expected touchpoint journey
with later stage touchpoint channels realizing the
highest conversion rates.
Display
discovery, awareness & interest
(first click)
Social
awareness & consideration
(second or successive click)
Email
retargeting & consideration
(successive click)
Referral
awareness & consideration
(first or successive click)
Search
Specific intent & purpose
(first or successive click)
Direct
Specific intent & purpose
(successive or last click)
First Click Second or Subsequent Click Last Click
Channel Conversion Attribution Follows Touchpoint Linear Flow Journey Path

DV Conversion Counts (Geo Attribution)
Conversion Attribution
❑ DV metros are converting in good numbers.
❑ Adjusted Quality ratio is a bit off from national running
average of 84%.
❑ Conversion counts do have HPO overlap and are
double counted in the (4) common metro markets.
Houston, Phoenix, San Diego and Sacramento are
common partner overlap areas which do impact
represented attribution counts.

DV Metro Conversions (Adjusted)
quarterly DV conversions:
1. Phoenix
2. San Diego
3. Sacramento
Of note: Top metros are common overlap metros with
HPO presence. Conclusive attribution impact based on
using geo filtering is unobtainable without campaign
attribution filtering.
 Baseline return visit trending pattern reinforced as
return visits convert at a higher percentage rate over
new visits representing more people are converting on
their second or successive site visit.
GA View: 176339261 (unfiltered view) GA Goal Tracking Representation
DV Conversion Count Metro Ranking (Geo Attribution)

DV Conversion Rate Metro Ranking (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
DV Metro Conversion Rates (Adjusted)
Conversion rates by DV metro do not correlate to
conversion counts being created.
But of distinction some markets do perform better than
others, e.g., Phoenix and San Diego, when reviewed by
conversion counts.
 Phoenix is an anomaly on the high end which is
currently the leading DV metro for conversion rate.
(Needs deeper review.)
Phoenix is also a common overlap market with HPOs.
Attribution counts may differ when analyzed by
campaign attribution.
 The San Diego and Sacramento areas are making a
large impact. (common overlap metros)
 Washington DC represents a good DV conversion
location.
 Houston is also an anomaly where it’s the leading
metro for traffic sessions, yet underperforms for
conversions. (Needs deeper review.)

DV Conversions x State Region View (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
DV Regional Conversion Impact
 State conversions loosely align with DV clinic
presence.
 Arizona-Banner and California and are top
performers (overlap states).
 Texas, Virginia, Tennessee, North Carolina,
Washington, Maryland and the District of Columbia
are high performance regions.
GRAND TOTAL 8% 9,817 7,893
Arizona 25% 4,298 4,459
California 12% 2,918 2,281
Texas 1% 549 224
Virginia 7% 439 207
North Carolina 9% 357 143
Washington 6% 236 108
Maryland 5% 219 114
District of Columbia 4% 196 100
New Mexico 9% 85 57
Louisiana 5% 35 10
Nevada 10% 14 13
South Carolina 4% 6 1
West Virginia 8% 5 3
Wyoming 15% 3 3
Arkansas 3% 2 2
Colorado 8% 2 0
Kentucky 5% 1 1

DV Channel Conversions (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Channel Conversion Attribution
 Channel conversion counts and conversion rates
align with touchpoints within the user touchpoint
journey.
 Display and Social, as awareness channels, are
serving their intended purpose for creating levels of site
traffic with the added benefit of occasional first click
conversion attribution.
 Email and Referral as channels where users arrive at
the site via active click backlinking perform as expected
within the user journey model.
 Search and Direct as channels for arriving at the site
with specific intent are accredited for conversion in high
numbers within the last touch attribution model.
Insights align overall with the multi-touch user touchpoint
journey. The journey continues to evolve.

HPO Conversion Counts (Geo Attribution)
Conversion Attribution
 HPO metros are significantly converting in high
numbers.
 Quality ratio is better than National average.
 Conversion counts do have HPO overlap and are
double counted in the (4) common metro markets.

HPO Metro Conversions (Adjusted)
quarterly HPO conversions:
1. New York
2. Phoenix
3. Pittsburgh
4. Los Angeles
5. Boston
6. Chicago
7. Birmingham
8. San Diego
9. Tucson
10. Detroit
 Trending pattern reinforced with return visits
converting at a higher percentage rate over new
visits representing more people are converting on their
second or subsequent visit.
GA View: 176339261 (unfiltered view) GA Goal Tracking Representation
HPO Conversion Count Metro Ranking (Geo Attribution)

HPO Conversion Rate Metro Ranking (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
HPO Metro Conversion Rates (Adjusted)
Conversion rates by HPO metro loosely correlate to
conversion counts being created.
But of distinction Top 5 markets do perform better than
others.
 Phoenix is an anomaly on the high end which is
currently the leading HPO and DV metro for
conversion rate. (Needs deeper review.)
 Phoenix is a common overlap market with DVs.
Attribution counts may differ when analyzed by
campaign.
 The Pittsburgh and Birmingham markets are
making a large impact. (common overlap metros)
 Detroit, Dallas and Waco represents strong HPO
conversion markets.
 Houston remains an anomaly where it’s the leading
metro by sessions, yet Houston (#20) isn’t represented
within the Top 15 metros for conversion. (Needs
deeper review.)

HPO Conversions x State Region View (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
HPO Regional Conversion Impact
 State conversions do align with HPO presence.
 California and Arizona-Banner are top consortium
performers.
 Pennsylvania, New York, Illinois are high
performance precision medicine consortiums.
 Texas as part of the TACH consortium and Alabama
as part of the Southern consortium performs well.
GRAND TOTAL 11% 45,306 38,413
California 12% 7,439 6,226
Arizona 26% 5,894 6,069
Pennsylvania 18% 4,542 3,831
New York 13% 4,426 3,873
Illinois 14% 3,514 3,050
Massachusetts 17% 3,414 3,135
Texas 4% 3,067 1,928
Alabama 18% 2,956 2,411
Michigan 11% 2,209 1,492
Wisconsin 14% 2,148 1,755
Florida 7% 2,024 1,957
Georgia 5% 1,235 1,004
Minnesota 16% 407 311
Rhode Island 15% 267 35
Connecticut 7% 236 199
Louisiana 5% 230 40
South Carolina 16% 195 209
New Jersey 3% 189 114

HPO Channel Conversions (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Channel Conversion Attribution
 Channel conversion counts and conversion rates
align with touchpoints within the user touchpoint
journey.
 Display and Social are lower on the CVR scale as
expected and as awareness channels with fewer last
click conversions.
 Email and Referral as channels where users arrive at
the site via active click backlinking perform as expected
within the user journey model.
 Search and Direct as channels for arriving at the site
with specific intent are accredited for conversion in high
numbers within the last touch attribution model.
Overall trending pattern is common across the program
in aggregate and across partners further representing
channels influence within the touchpoint journey path.

USER BEHAVIORS
Q. (Baseline) What are user behaviors upon arriving at the site?

User Site Traffic Behaviors (Aggregate Baseline) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Accounts
Created
Consent
Completions
Quality
Ratio
GA Counts 56,113 35,100 62%
Adjusted 49,705 40,756 82%
GA vs DRC anomalies:
Accounts +12.5% over-reporting . Consents -16.2% under-reporting .
Adjusted counts margin of error + 1 percent
Site Visits Representation
Conversion Rate: Accounts Created / User Visits

User Type Behaviors Comparison (Aggregate Baseline)
New Visits New Users Sessions
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Pageviews Pages / Session
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 350,042 350,042 1.0 4.15 73% 1,955,116 6.2 27,663 18,819 68% 8%
Return Visits Return Users Sessions
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 126,206 150,476 1.2 11.92 61% 2,163,948 9.0 22,042 21,937 100% 18%
Delta Change
Return vs. New
223,836 199,566 -15.97% -65.18% 19.67% -9.65% -31.15% 5,621 -3,118 -32.00% -54.19%

State Behaviors x Accounts Created (Aggregate Baseline)
Region Users New Users Return Users Sessions Session per User
Avg Session
Duration
Avg Bounce Rate Pageviews Pages / Session
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
GRAND TOTAL 476,248 350,042 126,206 500,518 1.05 6.49 70% 4,119,064 7.25 49,705 40,756 82% 10%
California 65,524 46,459 19,065 69,750 1.06 7.42 66% 651,256 8.69 7,612 6,350 83% 12%
Arizona 22,964 12,764 10,200 25,201 1.10 15.73 55% 490,149 14.54 5,897 6,070 103% 26%
Pennsylvania 25,499 17,595 7,904 26,661 1.05 10.43 53% 334,435 9.62 4,660 3,912 84% 18%
New York 35,173 25,743 9,430 37,546 1.07 7.41 69% 368,249 6.11 4,466 3,890 87% 13%
Illinois 26,030 17,598 8,432 27,790 1.07 9.68 62% 300,461 10.01 3,527 3,060 87% 14%
Massachusetts 20,050 12,628 7,422 21,616 1.08 10.78 53% 308,832 9.65 3,416 3,136 92% 17%
Texas 83,153 66,503 16,650 85,621 1.03 2.37 85% 293,025 4.64 3,309 2,064 62% 4%
Alabama 17,020 12,363 4,657 18,065 1.06 9.68 60% 233,933 10.25 2,970 2,425 82% 17%
Michigan 19,783 14,000 5,783 20,833 1.05 6.29 69% 163,694 10.03 2,258 1,519 67% 11%
Wisconsin 15,963 10,768 5,195 16,707 1.05 8.46 57% 173,346 10.44 2,154 1,760 82% 13%
Florida 27,858 21,521 6,337 29,197 1.05 5.25 77% 195,388 6.44 2,043 1,968 96% 7%
Georgia 23,638 18,176 5,462 24,575 1.04 4.01 79% 119,895 4.67 1,253 1,020 81% 5%
Tennessee 5,677 4,314 1,363 5,862 1.03 4.86 67% 40,698 6.22 572 257 45% 10%
Virginia 7,771 6,596 1,175 8,016 1.03 2.80 72% 31,856 4.86 505 242 48% 6%
Mississippi 4,431 3,350 1,081 4,653 1.05 7.61 73% 42,399 7.49 483 471 98% 11%
Sort: Top 15 x Accounts Created

Region Users New Users Return Users
% Return
Users
Sessions Session per User Avg Session Duration Avg Bounce Rate Pageviews Pages / Session Adjusted Accounts Adjusted Consents Adjusted Quality Ratio Adjusted Conversion Rate
GRAND TOTAL 476,248 350,042 126,206 27% 500,518 1.05 6.49 70% 4,119,064 7.25 49,705 40,756 82% 10%
Texas 83,153 66,503 16,650 20% 85,621 1.03 2.37 85% 293,025 4.64 3,309 2,064 62% 4%
California 65,524 46,459 19,065 29% 69,750 1.06 7.42 66% 651,256 8.69 7,612 6,350 83% 12%
New York 35,173 25,743 9,430 27% 37,546 1.07 7.41 69% 368,249 6.11 4,466 3,890 87% 13%
Florida 27,858 21,521 6,337 23% 29,197 1.05 5.25 77% 195,388 6.44 2,043 1,968 96% 7%
Illinois 26,030 17,598 8,432 32% 27,790 1.07 9.68 62% 300,461 10.01 3,527 3,060 87% 14%
Pennsylvania 25,499 17,595 7,904 31% 26,661 1.05 10.43 53% 334,435 9.62 4,660 3,912 84% 18%
Georgia 23,638 18,176 5,462 23% 24,575 1.04 4.01 79% 119,895 4.67 1,253 1,020 81% 5%
Arizona 22,964 12,764 10,200 44% 25,201 1.10 15.73 55% 490,149 14.54 5,897 6,070 103% 26%
Massachusetts 20,050 12,628 7,422 37% 21,616 1.08 10.78 53% 308,832 9.65 3,416 3,136 92% 17%
Michigan 19,783 14,000 5,783 29% 20,833 1.05 6.29 69% 163,694 10.03 2,258 1,519 67% 11%
Alabama 17,020 12,363 4,657 27% 18,065 1.06 9.68 60% 233,933 10.25 2,970 2,425 82% 17%
Wisconsin 15,963 10,768 5,195 33% 16,707 1.05 8.46 57% 173,346 10.44 2,154 1,760 82% 13%
Kansas 15,359 14,127 1,232 8% 15,372 1.00 0.35 97% 25,560 2.45 124 79 64% 1%
Virginia 7,771 6,596 1,175 15% 8,016 1.03 2.80 72% 31,856 4.86 505 242 48% 6%
New Jersey 7,534 6,029 1,505 20% 7,760 1.03 2.14 83% 21,165 4.64 192 116 61% 3%
Tennessee 5,677 4,314 1,363 24% 5,862 1.03 4.86 67% 40,698 6.22 572 257 45% 10%
District of Columbia 4,941 4,089 852 17% 5,074 1.03 2.46 70% 17,131 3.70 196 100 51% 4%
Washington 4,711 3,495 1,216 26% 4,913 1.04 4.03 66% 23,882 6.18 261 121 46% 6%
Louisiana 4,705 3,806 899 19% 4,815 1.02 2.00 81% 12,096 3.13 252 56 22% 5%
North Carolina 4,670 3,764 906 19% 4,807 1.03 3.73 70% 26,732 5.91 388 167 43% 8%
Maryland 4,631 2,949 1,682 36% 5,038 1.09 4.46 60% 24,424 4.89 220 114 52% 5%
Mississippi 4,431 3,350 1,081 24% 4,653 1.05 7.61 73% 42,399 7.49 483 471 98% 11%
Connecticut 3,453 2,462 991 29% 3,611 1.05 5.09 75% 25,462 6.15 236 199 84% 7%
Minnesota 2,836 1,838 998 35% 2,978 1.05 9.23 47% 32,275 10.46 428 323 76% 15%
Ohio 2,617 1,999 618 24% 2,700 1.03 4.19 67% 14,863 6.13 188 125 67% 7%
State Behaviors x User Visits (Aggregate Baseline)

Region Users New Users Return Users
% Return
Users
Sessions Session per User Avg Session Duration Avg Bounce Rate Pageviews Pages / Session Adjusted Accounts Adjusted Consents Adjusted Quality Ratio Adjusted Conversion Rate
South Carolina 1,870 1,346 524 28% 1,992 1.07 9.14 69% 27,321 11.16 244 220 90% 13%
Colorado 1,807 1,264 543 30% 1,899 1.05 6.73 58% 21,376 9.83 222 168 76% 12%
Rhode Island 1,726 974 752 44% 2,151 1.25 7.53 67% 8,861 5.61 267 35 13% 15%
Oregon 1,689 1,452 237 14% 1,719 1.02 3.17 74% 7,979 6.52 91 62 68% 5%
Missouri 1,411 1,051 360 26% 1,460 1.03 3.94 67% 7,750 5.78 71 52 74% 5%
Nevada 1,387 1,067 320 23% 1,432 1.03 8.38 56% 8,562 6.09 280 135 48% 20%
Indiana 1,265 957 308 24% 1,304 1.03 4.29 67% 8,005 6.65 93 49 52% 7%
Arkansas 1,116 875 241 22% 1,165 1.04 6.36 53% 11,214 7.76 177 80 45% 16%
New Mexico 1,053 811 242 23% 1,086 1.03 5.69 65% 5,809 6.55 89 59 67% 8%
Oklahoma 878 702 176 20% 895 1.02 5.37 59% 4,175 4.53 146 76 52% 17%
New Hampshire 862 637 225 26% 889 1.03 4.69 67% 4,821 5.96 44 34 77% 5%
Kentucky 768 621 147 19% 785 1.02 4.07 58% 5,166 5.99 71 34 47% 9%
Iowa 748 592 156 21% 782 1.05 2.61 72% 3,048 4.46 31 20 63% 4%
Utah 625 402 223 36% 665 1.06 4.77 59% 3,418 5.49 47 24 52% 8%
West Virginia 469 343 126 27% 480 1.02 4.87 71% 2,618 6.02 36 21 57% 8%
Wyoming 457 431 26 6% 458 1.00 2.02 71% 1,617 5.41 17 5 28% 4%
Maine 357 267 90 25% 370 1.04 6.51 53% 3,319 8.64 25 27 107% 7%
Nebraska 313 226 87 28% 318 1.02 3.39 59% 1,724 5.71 20 16 80% 7%
Hawaii 306 216 90 29% 321 1.05 5.94 61% 2,464 7.18 27 17 65% 9%
Idaho 241 180 61 25% 251 1.04 5.68 48% 1,521 6.03 14 12 82% 6%
Delaware 225 169 56 25% 231 1.03 6.51 55% 1,816 6.42 20 17 85% 9%
Vermont 196 144 52 27% 203 1.04 6.27 49% 1,924 9.16 16 13 80% 8%
Montana 185 146 39 21% 189 1.02 5.68 64% 1,008 5.20 12 10 84% 7%
North Dakota 116 86 30 26% 120 1.03 13.67 48% 917 7.93 20 19 95% 17%
South Dakota 101 85 16 16% 102 1.01 3.02 71% 499 4.86 4 3 78% 4%
Alaska 86 62 24 28% 90 1.05 9.62 53% 926 11.14 12 3 30% 13%
State Behaviors x User Visits (Aggregate Baseline)

DV User Site Traffic Behaviors (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Accounts
Created
Consent
Completions
Quality
Ratio
GA Counts 11,044 6,793 62%
Adjusted 9,817 7,893 80%
Accounts +12.5% over-reporting . Consents -16.2% under-reporting .
Adjusted counts margin of error + 1 percent

DV User Type Behaviors Comparison (Geo Attribution)
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 94,693 94,693 1.00 2.69 78% 374,093 5.43 4,870 2,943 60% 5%
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 31,498 36,774 1.17 10.39 64% 469,917 7.61 4,947 4,950 100% 16%
Delta Change
Return vs. New
-63,195 -57,919 17.00% 286.25% -17.95% 25.62% 40.15% 77 2,007 66.67% 214.12%
Houston, Phoenix, San Diego and Sacramento are common partner overlap markets and may impact final attribution counts.

DV User Type Comparison x Accounts Created (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Houston, Phoenix, San Diego and Sacramento are common partner overlap markets.
NEW VISITS
Top 10 Metros
Region New Users Sessions Session per User
Avg Session
Duration
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
ALL METROS AVERAGES 94,693 94,693 1.00 2.69 78% 374,093 5.43 4,870 2,943 60% 5%
San Diego CA California 9,551 9,551 1.00 7.06 61% 91,321 9.63 1,316 1,004 76% 14%
Phoenix AZ Arizona 9,749 9,749 1.00 5.52 69% 73,515 10.48 871 643 74% 9%
Sacramento-Stockton-Modesto CA California 7,694 7,694 1.00 4.69 69% 47,302 7.57 647 450 69% 8%
Houston TX Texas 43,950 43,950 1.00 0.72 89% 62,909 2.57 416 145 35% 1%
Washington DC (Hagerstown MD) Virginia 5,209 5,209 1.00 1.56 75% 15,184 3.58 333 141 42% 6%
Memphis TN Tennessee 1,307 1,307 1.00 4.54 64% 11,602 8.17 273 78 29% 21%
Seattle-Tacoma WA Washington 2,973 2,973 1.00 3.48 68% 12,115 6.22 187 79 42% 6%
Washington DC (Hagerstown MD) District of Columbia 4,089 4,089 1.00 1.69 72% 12,870 3.77 157 83 52% 4%
Charlotte NC North Carolina 1,576 1,576 1.00 2.93 75% 6,811 4.84 146 43 29% 9%
Raleigh-Durham (Fayetteville) NC North Carolina 1,593 1,593 1.00 3.25 69% 8,064 5.86 139 53 39% 9%
RETURN VISITS
Top 10 Metros
Region Return Users Sessions Session per User
Avg Session
Duration
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
ALL METROS AVERAGES 31,498 36,774 1.17 10.39 64% 469,917 7.61 4,947 4,950 100% 16%
Phoenix AZ Arizona 7,507 9,183 1.22 24.85 42% 290,055 20.24 3,427 3,816 111% 46%
San Diego CA California 4,795 5,676 1.18 8.38 53% 60,504 8.83 552 419 76% 12%
Sacramento-Stockton-Modesto CA California 2,802 3,336 1.19 10.31 59% 45,007 12.40 403 408 101% 14%
Houston TX Texas 9,511 10,439 1.10 1.99 92% 23,003 2.64 133 79 59% 1%
Washington DC (Hagerstown MD) Virginia 953 1,177 1.24 8.87 56% 10,264 8.11 106 66 63% 11%
Washington DC (Hagerstown MD) Maryland 1,421 1,788 1.26 6.39 55% 8,087 4.48 80 27 33% 6%
Seattle-Tacoma WA Washington 1,126 1,319 1.17 6.06 59% 9,684 7.76 49 29 59% 4%
Raleigh-Durham (Fayetteville) NC North Carolina 442 503 1.14 6.66 60% 5,342 10.47 45 28 62% 10%
Washington DC (Hagerstown MD) District of Columbia 852 985 1.16 5.66 62% 4,261 3.55 38 17 46% 4%
Nashville TN Tennessee 748 831 1.11 5.65 56% 4,671 5.43 29 15 51% 4%

DV Metro Behaviors x Accounts Created (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Metro Users New Users Return Users
% Return
Users
Sessions
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
GRAND TOTAL 126,191 94,693 31,498 25% 131,467 1.04 4.84 74% 844,010 6.31 9,817 7,893 80% 8%
Phoenix AZ 17,256 9,749 7,507 44% 18,932 1.10 14.89 57% 363,570 15.05 4,298 4,459 104% 25%
San Diego CA 14,346 9,551 4,795 33% 15,227 1.06 7.55 58% 151,825 9.23 1,868 1,423 76% 13%
Sacramento-Stockton-
Modesto CA
10,496 7,694 2,802 27% 11,030 1.05 6.39 66% 92,309 9.65 1,050 858 82% 10%
Washington DC (Hagerstown
MD)
14,912 11,657 3,255 22% 15,640 1.05 3.20 68% 62,722 4.64 812 400 49% 5%
Houston TX 53,461 43,950 9,511 18% 54,389 1.02 0.97 90% 85,912 2.60 549 224 41% 1%
Memphis TN 1,796 1,566 230 13% 1,832 1.02 4.89 67% 15,462 7.94 317 107 34% 18%
Seattle-Tacoma WA 4,099 2,973 1,126 27% 4,292 1.05 4.27 65% 21,799 6.88 236 108 46% 6%
Raleigh-Durham (Fayetteville)
NC
2,047 1,603 444 22% 2,108 1.03 4.06 67% 13,423 7.39 184 81 44% 9%
Charlotte NC 2,024 1,689 335 17% 2,067 1.02 3.09 75% 9,446 5.14 164 56 34% 8%
Nashville TN 2,716 1,966 750 28% 2,799 1.03 3.61 68% 12,090 4.63 138 63 46% 5%
Albuquerque-Santa Fe NM 1,013 784 229 23% 1,045 1.03 5.59 66% 5,517 6.43 87 57 65% 9%
Baltimore MD 857 599 258 30% 897 1.05 4.15 56% 4,723 5.11 47 24 52% 5%
Baton Rouge LA 718 569 149 21% 739 1.03 2.42 80% 1,638 2.57 35 10 30% 5%
Greensboro-High Point-Winston
Salem NC
289 228 61 21% 299 1.03 4.23 62% 1,719 5.49 15 7 46% 5%
Las Vegas NV 143 103 40 28% 152 1.06 6.13 50% 1,229 7.73 14 13 90% 10%
Casper-Riverton WY 18 12 6 33% 19 1.06 21.21 33% 626 34.44 3 3 131% 15%

HPO User Site Traffic Behaviors (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
Accounts
Created
Consent
Completions
Quality
Ratio
GA Counts 50,969 33,058 65%
Adjusted 45,306 38,413 85%
Accounts +12.5% over-reporting . Consents -16.2% under-reporting

HPO User Type Behaviors Comparison (Geo Attribution)
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 291,758 291,758 1.00 4.44 72% 1,718,596 6.76 24,037 16,950 71% 8%
Session per
User
Avg Session
Duration
Avg Bounce
Rate
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
Aggregate 112,617 134,899 1.20 12.66 60% 2,064,432 9.74 21,268 21,463 101% 19%
Delta Change
Return vs. New
-179,141 -156,859 20.00% 185.14% -16.67% 20.12% 44.08% -2,769 4,513 42.25% 136.07%
Houston, Phoenix, San Diego and Sacramento are common partner overlap markets and may impact final attribution counts.

HPO User Type Comparison x Accounts Created (Geo Attribution) Time Period: Q1 2019 (Jan. 1 thru Mar. 31, 2019)
NEW VISITS
Top 10 Metros
Region New Users Sessions Session per User
Avg Session
Duration
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
ALL METROS AVERAGES 350,042 350,042 1.00 4.15 73% 1,955,116 6.21 27,663 18,819 68% 8%
Pittsburgh PA Pennsylvania 13,323 13,323 1.00 11.22 54% 180,268 11.21 2,880 2,375 82% 22%
New York NY New York 24,199 24,199 1.00 3.76 72% 129,541 4.70 1,847 1,140 62% 8%
Los Angeles CA California 20,972 20,972 1.00 4.67 72% 127,843 7.50 1,819 1,282 70% 9%
Chicago IL Illinois 16,999 16,999 1.00 5.63 65% 118,840 8.23 1,723 1,134 66% 10%
Birmingham (Ann and Tusc) AL Alabama 8,471 8,471 1.00 8.47 57% 92,138 9.14 1,511 1,056 70% 18%
Boston MA-Manchester NH Massachusetts 11,896 11,896 1.00 7.04 56% 107,791 9.25 1,375 1,034 75% 12%
San Diego CA California 9,551 9,551 1.00 7.06 61% 91,321 9.63 1,316 1,004 76% 14%
Dallas-Ft. Worth TX Texas 13,536 13,536 1.00 3.05 78% 63,121 6.67 915 480 52% 7%
Detroit MI Michigan 9,193 9,193 1.00 3.85 73% 46,227 8.51 897 433 48% 10%
Phoenix AZ Arizona 9,749 9,749 1.00 5.52 69% 73,515 10.48 871 643 74% 9%
RETURN VISITS
Top 10 Metros
Region Return Users Sessions Session per User
Avg Session
Duration
Adjusted
Accounts
Adjusted
Consents
Adjusted Quality
Ratio
Adjusted
Conversion Rate
ALL METROS AVERAGES 126,206 150,476 1.19 11.92 61% 2,163,948 9.02 22,042 21,937 100% 17%
Phoenix AZ Arizona 7,507 9,183 1.22 24.85 42% 290,055 20.24 3,427 3,816 111% 46%
New York NY New York 9,167 11,513 1.26 15.82 60% 231,650 8.99 2,546 2,706 106% 28%
Boston MA-Manchester NH Massachusetts 7,154 8,686 1.21 16.76 46% 196,149 11.63 2,003 2,070 103% 28%
Los Angeles CA California 8,903 11,229 1.26 14.76 62% 186,667 9.08 1,813 1,950 108% 20%
Chicago IL Illinois 8,194 9,928 1.21 16.29 56% 168,640 11.19 1,625 1,744 107% 20%
Tucson (Sierra Vista) AZ Arizona 2,607 3,156 1.21 26.89 34% 90,013 20.26 1,130 1,200 106% 43%
Pittsburgh PA Pennsylvania 6,222 7,157 1.15 11.33 44% 99,519 10.24 972 926 95% 16%
Birmingham (Ann and Tusc) AL Alabama 3,300 4,129 1.25 16.95 49% 95,458 11.28 954 884 93% 29%
Miami-Ft. Lauderdale FL Florida 2,290 2,953 1.29 21.16 59% 74,494 14.21 812 894 110% 35%
San Diego CA California 4,795 5,676 1.18 8.38 53% 60,504 8.83 552 419 76% 12%

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