[Webinar]

The Perfect Blend of Surveys and Behavioral Tracking

Saran GaneshDirector of Product

January 26, 2017

• Introduction to Verto• Surveys + Behavioral = Smart Poll• Use cases• Q&A

Agenda

Quantify Media Consumption Across All Channels Hour-by-Hour

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. !

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 timethat 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

Some of Our Customers

SMART POLL A Holistic View of the Consumer:

Surveys + Behavioral Data

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

Data Collection: Behavioral TrackingHow the Data is Captured

1Panelists are recruitedthrough a registration questionnaire.

2Participants download and install the app on their multiple devices.

3App ‘passively’ measures panelists’ behavior 24/7—single-source methodology.

4Integrated analysis of the passive behavioral data, demographics, and declared preferences.

5Actionable insights

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.

!

AppsApps installed/uninstalled/used, duration of use, etc.

!

SMART POLLSurveys + 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.

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

USE CASESCommercial Applications

of Smart Poll

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.

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

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

75.668.2

0

20

40

60

80

100

120

Ave

rage

Hou

rs p

er U

ser p

er M

onth

Time Spent on Sites and Apps That Sell Pet Products

Any PC Mobile

Pet Owners Online Population

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

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)

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

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

SH

AR

E O

F R

ES

PO

ND

EN

TS

Think about the 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

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

157156

145

159

Android Smartphone iOS Smartphone Android Tablet iOS Tablet

Satis

fact

ion

Scor

e

Device Satisfaction by Device Type

Source: Verto Device Watch Data, 18+ U.S. Internet users, October 2015

Case StudiesCustomer Projects

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?

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?

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 THE CONSUMER: How do mothers with babies differ from typical online users?

Saran GaneshDirector of Product--347-223-1856saran.ganesh@vertoanalytics.com--http://www.vertoanalytics.com/smart-poll/

@vertoanalytics