4. The Digital World Is Cross-Device and Mobile-First
• Nearly 40% of U.S. consumers use smartphones, tablets, and
PCs during any month.
• The average U.S. consumer owns more than 5 digital devices.
• Consumers use around 25 different apps per month and have
75 different apps installed on their devices at any particular
point in time.
• Only 5-15% of downloads lead to active 30-day users, and, out
of those, just 10-20% can be monetized over time via in-app
purchasing.
As consumers move fluidly between devices and
services, you should know when, how, and why.!
5. We measure consumers
on every device, app, site, service, and platform they use
throughout the day, both online and offline.
We operate a single-source panel
in which we passively collect cross-device user behavioral
data and panelist demographics and other background
data.
We validate and quantify the time
that consumers spend on screens, providing the “why”
behind rankings, ratings, and benchmarks.
We provide insights so you can take action
to optimize for cross-media consumption, retention, and
path-to-purchase behaviors.
Consumer-Centric
Measurement
8. Verto Smart Panel
• Panelists install metering apps on all their digital
devices.
• Panelists must register their devices to enroll in
the Smart Panel.
• Multi-screen behavior is captured through our
single-source methodology.
• Provides for true multi-screen behavioral
session-level analysis and day-in-the-life studies.
• Taxonomy ties all platforms, apps, and sites
together in eight layers.
Passively Metered Opt-in Panel Provides
Behavioral and Contextual Data from
the Point of Interaction
9. Data Collection: Behavioral Tracking
How the Data is Captured
1
Panelists are recruited
through a registration
questionnaire.
2
Participants download
and install the app on
their multiple devices.
3
App ‘passively’ measures
panelists’ behavior
24/7—single-source
methodology.
4
Integrated analysis of the
passive behavioral data,
demographics, and
declared preferences.
5
Actionable insights
10. Verto Smart Panel: What Do We Measure on Each Device?
Phone features*
Voice, SMS/MMS, camera…
Cross-device behavior
is captured through
our single-source
methodology.
Provides for true
multi-screen
behavioral session-
level analysis and
day-in-the-life studies.
OS covered OS covered OS covered
Meter runs on PCs, smartphones, and tablets.
On every device we track apps, sites, services, and platforms panelists use throughout
the day, both online and offline, including web sites visited, visit duration, search terms,
advertising, e-commerce and more.
!
Apps
Apps installed/uninstalled/used, duration of use, etc.
!
11. SMART POLL
Surveys + Behavioral Data
A HOLISTIC VIEW OF THE CONSUMER
• A single-source approach designed around the
consumer
• All data is collected from the same individuals to
enable longitudinal analysis:
• Profile information
• Cross-device digital usage (passive metering
data)—smartphone, tablet, ebook, laptops,
desktop PCs, etc.
• Offline usage (TV) & attitudes (declarative)
• Ad-hoc questions (client segmentation, etc.)
• No data fusion or statistical methods to fill in
the gaps or “bridge samples”
• Address the “why” behind behavioral actions
• Use behavioral data to screen panelists for
specific attributes or behaviors prior to survey.
• Append attitudinal survey data to specific
attributes or behaviors on a respondent level.
12. A continuous stream of data:
• App downloads & usage
• Web site visitation
• Exposure to content categories
• Device usage/telemetric data
• Media exposure
• E-commerce activity
• Search activity
• Social media use
The who, what, where, when, and WHY:
• Satisfaction with devices, apps, and sites
• User experience models
• Reasons for churn/registration
• Ad recall and brand awareness
• Loyalty to brands/services
• Purchase intent and actual purchase history
• Claimed usage
• Psycho-graphic segmentation
! Get a precise view of consumer behavior and
their drivers.
Smart Poll: A Holistic View of the Consumer
14. Verto Smart Poll: Commercial Applications
1. Cross-Device Measurement—Combine cross-device behaviors and day-in-the-life patterns
with demographics, lifestyle characteristics, and attitudes to help improve products.
2. Enhanced Segmentation—Field your own custom segmentation model to learn which
consumers are most likely to buy in the future.
3. Behavior-Triggered Surveys—Survey to capture reactions to an app or site, identify certain
types of users, or compare usage to competitive services.
4. Ad Effectiveness—Enrich your understanding of the key target segments and the devices,
services, and content used to guide campaign planning.
5. Mobile Path to Purchase—Uncover behaviors that lead to a purchase, determine interest in
innovative m-commerce approaches, and identify where brands can influence consumers on
the path to purchase.
15. Use Case:
Cross-Device Measurement: OEM (Original Equipment Manufacturer) Device Behaviors
Outcome:
• OEMs use this research to evaluate the
strengths/weaknesses of devices and installed services
• Insights can be used for product development, competitive
intelligence, uncovering white spaces, improving features.
Background:
Data is at the heart of creating better user experiences.
Understanding what consumers do on mobile devices and
why is the key to building a winning product strategy.
Implementation:
• Track the usage patterns of smartphone and
tablet users
• Identify key usage metrics: time spent, time of
day, apps used, etc.
• Isolate the type of users (demographics, usage) to
target
• Survey those users to understand why they made
certain device choices and how they use them
A B C
16. Use Case:
Enhanced Segmentation: Pet Owners’ Activity and Choices
Outcome:
• Link owner behavior to ad exposure
• Understand habitual behavior vs. triggers that cause a
change in typical patterns
• Get insights on the impact of a vet visit on product or
food choices
Background:
A pet food company wants to deepen its understanding
of two types of buyers—Informed Health Managers and
Pet-Centric Parents. The research project tracks pet
owners’ digital behavior and habits using both active and
passive components.
Implementation:
• Passively track pet owners’ clickstreams,
search activity, and mobile-app engagement
on pet-related websites
• Survey pet owners about feeding habits,
shopping, and food choices
• Survey pet owners about their pets’
activities, vet visits, food preferences
A B
104.8
89.3
112.3
88.9
75.6
68.2
0
20
40
60
80
100
120
AverageHoursperUserperMonth
Time Spent on Sites and Apps That Sell Pet Products
Any PC Mobile
Pet Owners Online Population
17. Use Case:
Behavior-Triggered Surveys: Travel Planning
Outcome:
• Learn which are travelers’ favorite apps and sites used
for research and which are used for booking
• Get a clear picture of the most used travel apps and
sites—including local guides or subway maps
• Understand why a consumer uses multiple apps and
sites. For example: Why do they use Orbitz versus
Kayak to buy a plane ticket?
Background:
Travel planning and booking has moved to 3+ screens. To
win, the travel industry needs a deeper understanding of
how travelers are using their smartphones and tablets.
The study focuses on travelers who are planning to travel
in the next 6 months.
Implementation:
• Passively track for any travel site visits or travel app usage
• Tag ads from the various travel-related sites and apps
• Based on the travel visits and app usage, trigger a survey
to canvass for usage preferences, e.g., reasons for
switching away from app
A B C
18. Use Case:
Ad Effectiveness Tracking
Outcome:
• Measure the overall success of the ad campaign to
optimize for future campaigns
• Behavioral measurement reveals target consumers’ cross-
device engagement down to the hour or day of the week—
target ad distribution and timing
• Get concrete feedback about ads—including creative,
messages, formats, etc.
Background:
As the balance of media spending shifts to digital and
mobile, brands need richer data about cross-device media
habits. With these insights, brands and agencies can build
a more effective media buying strategy across multiple
channels, including TV, social media, PC, and mobile.
Implementation:
• Isolate target segments based on gender, age,
device ownership, location, household income
etc.
• Track pre-campaign behavior and post-campaign
exposure to ads on mobile web sites and mobile
apps
• Collect clickstream data and measure exposure
to the online campaign for the same group of
panelists
• Assess both brand and sales lift by surveying
viewers on ad recall and messages
A B C
81%Mobile Brand
Awareness
26%Lift in Brand
Consideration
(vs. 77% Online Only) (Multi-screen vs. +4%
Online Only)
19. Use Case:
Path to Purchase for a Cosmetics Purchase
Outcome:
• Learn how each touch point influences brand choices
and final product decision
• Identify triggers that impact a conversion on the path to
purchase
• Evaluate whether certain brands have better mobile
strategies that then result in more m-commerce
Background:
Purchase decisions are influenced by daily experiences.
These experiences happen in both the offline and online
worlds and affect consumers at different stages in their
path to purchase. Mobile touch points play an important
role in how consumers decide which cosmetics brands to
purchase.
Implementation:
• Identify a representative sample of cosmetics
purchasers among Smart Panel members
• Observe their clickstream, app usage, cross-device
browsing/buying patterns, and keyword search
terms
• Surveys are triggered at different touch points
during their journey to assess why they used a
certain device or service to make a purchase and if
they decided to buy in-store.
A B
20. Exemplary Data:
Ad Recall on PCs and Smartphones Is Significantly Higher Than on Tablets and Game Consoles
65%
59%
49%
41%
25%
24%
0%
20%
40%
60%
80%
Computer Smartphone Streaming Media Player Smart TV Tablet Game Console
SHAREOFRESPONDENTS
Think aboutthe Past 30 Days. Do You Recall Seeing Any Ads When Using the Internet?
Source: Verto Device Watch Data, 18+ U.S. Internet users, October 2015
Passive Data Measurement: Device Used
21. Exemplary Data:
On Smartphones, Apple Is on the Same Level with Android Devices, But Takes the Lead on
Tablets
• Device satisfaction by operating system and device type
157
156
145
159
Android Smartphone iOS Smartphone Android Tablet iOS Tablet
SatisfactionScore
Device Satisfaction by Device Type
Source: Verto Device Watch Data, 18+ U.S. Internet users, October 2015
23. Case Study:
Attracting Advertisers to Streaming Video
Outcome:
• Identified four distinct segments of cross-device video users and
mapped out a day-in-the-life and mobile device habits of these
online video audiences to differentiate their interests.
• Used Verto Analytics’ single-source data to study the habits of the
online users who stream video across multiple devices and
developed the industry’s first comprehensive report on the
findings.
• Produced data-backed proof for advertisers to quantify how many
existing users versus incremental users can be reached by video
advertising on mobile devices and PCs (versus just PCs).
• Our client has seen a shorter sales cycle and significant revenue
uptake based on the insights.
Background:
A leading video advertising network wanted to provide its sales team
with better data to help convince their customers to invest in multi-
screen video advertising.
Key Question:
How can we identify the best platforms and contexts to engage with
loyal users, and how do we quantify their value to advertisers and
brands?
24. Case Study:
Optimizing Ad Spending
Outcome:
• We provided the customer with an analysis of target groups,
device ownership and usage, and digital usage patterns. We
generated day-in-the-life profiles for these target groups,
identifying the devices and services their targets were using
during specific times of day.
• This customer was able to build more actionable media mix
models based on Verto Analytics’ single-source data and
activate ad campaigns based on that.
• The customer identified the top three digital touch points
(search engines and two social platforms) that influenced their
target consumers. They launched a new advertising campaign
that reached 45% more consumers during the same time
frame as previous campaigns, with an overall 25% reduction
in respective media spend.
Background:
A Fortune 500 consumer goods company wanted to understand its
target audience and improve its media buying strategy across
multiple channels, including TV, social media, PC, and mobile.
Key Question:
How do I better understand the behaviors and demographics of my
consumer target groups and the sites, apps, and services they tend
to use more frequently vs. the typical online user base?
25. Case Study:
Understanding the Digital Behavior of Mothers with Babies
Background:
A research company working with a baby food manufacturer
wanted to to understand the digital behaviors of mothers with
babies in the UK.
A B
Key Question:
What are the digital behaviors of mothers with babies
over the course of a single day—and how, when, and
where do they shop?
Outcome:
• We provided the customer with an analysis of target
groups, device ownership and usage, and digital usage
patterns.
• We generated a day-in-the-life profile for this target group,
identifying the devices and services their targets were
using during specific times of day.
• Using the insights Verto provided, the customer knows
how to reach consumers at the right moment when it is
most likely to influence their purchase decisions.
• Finally, the customer was able to map the consumer
journey online and in-store.
UNDERSTANDING THECONSUMER: Howdo mothers withbabies differ fromtypical online users?
26. Saran Ganesh
Director of Product
--
347-223-1856
saran.ganesh@vertoanalytics.com
--
http://www.vertoanalytics.com/smart-poll/
@vertoanalytics
![[Webinar]
The Perfect Blend of Surveys and
Behavioral Tracking
Saran Ganesh
Director of Product
January 26, 2017](https://image.slidesharecdn.com/4ae45dd7-e980-41ff-a60c-65a1abd32708-170127152809/85/Verto-Analytics_Smart-Poll_WebinarPres-1-26-17-FINAL-002-1-320.jpg)
