Audible Presentation

RESPONSE

TO AUDIBLE

ASSIGNMENT

APRIL 27, 2015

CONTENTS

Section 1 The Challenge Section 2 Defining the Audience Section 3 Media Approach Section 4 Channel Planning Section 5 Modeling Section 6 Innovation Roadmap Section 7 Test & Learn Section 8 Reporting Section 9 Technology Solutions Section 10 Measurement and Forecasting //

AUDIBLE

417K Active Listeners

$50m Budget

//

THE CHALLENGE

2012 BRAND STUDY SHOWED ROOM TO GROW 2012 112.8 MILLION

Currently listening to audiobooks

PROSPECT POPULATION

Not currently listening but will consider Not currently listening and won’t consider

AUDIBLE UNAWARE

AUDIBLE AWARE

100%!

LISTENING-TO-CONSIDERATION SPECTRUM

90%!

18.23% 14.2 MM

22.63% 7.9 MM

80%!

70%!

60%!

14.37% 11.2 MM 23.21% 8.1 MM

50%!

40%!

30%!

20%!

10%!

54.15% 18.9 MM

67.39% 52.5 MM

0%!

0%!

10%!

20%!

30%!

Source: Audible Custom Study Findings, Jan 2012, Brand Asset Consulting

40%!

50%!

60%!

70%!

80%!

90%!

100%!

//

POSITIVE GROWTH SEEN ACROSS THE BOARD 2015 182 million

Would advocate audiobooks

PROSPECT POPULATION

Would maybe advocate audiobooks Would not advocate audiobooks

AUDIBLE UNAWARE

AUDIBLE AWARE

100%!

14.75% 16.7 MM

WILLINGNESS TO ADVOCATE AUDIOBOOKS

90%!

80%!

33.59% 37.9 MM

70%!

60%!

50%!

40%!

30%!

55.77% 38.6 MM

22.36% 15.4 MM

20%!

10%!

21.85% 15.1 MM

51.84% 58.6 MM

0%!

0%!

10%!

20%!

Source: Primary Research, M&C Saatchi Mobile - Web Survey 2015

30%!

40%!

50%!

60%!

70%!

80%!

90%!

100%!

//

POSITIVE GROWTH SEEN ACROSS THE BOARD 2015 182 million

Would advocate audiobooks

PROSPECT POPULATION

Would maybe advocate audiobooks Would not advocate audiobooks

AUDIBLE IMPROVEMENT IN AWARENESS

7%

100%!

WILLINGNESS TO ADVOCATE AUDIOBOOKS

90%!

80%!

2012

70%!

19.22%

Improvement in consideration

60%!

50%!

40%!

30%!

20%!

32.30%

10%!

15.55%

Improvement

Improvement in value sentiment

0%!

0%!

10%!

20%!

Source: Primary Research, M&C Saatchi Mobile - Web Survey 2015

30%!

40%!

50%!

60%!

70%!

80%!

90%!

100%!

//

MEDIA NEEDS TO CONTRIBUTE ON TWO FRONTS Would advocate audiobooks Would maybe advocate audiobooks Would not advocate audiobooks AWARENESS

100%!

Make them aware of Audible, push to trial

80%!

70%!

Push to trial if not currently a customer

Make them aware of Audible, convince them of the value of audiobooks, push to trial

60%!

CONSIDERATION

WILLINGNESS TO ADVOCATE AUDIOBOOKS

90%!

50%!

40%!

30%!

Convince them of the value of audiobooks, push to trial

20%!

10%!

Not a focus

Not a focus

0%!

0%!

10%!

20%!

Source: Primary Research, M&C Saatchi Mobile - Web Survey 2015

30%!

40%!

50%!

60%!

70%!

80%!

90%!

100%!

//

DEFINING OUR AUDIENCE

OUR TARGET MARKET (Category involved and open) are defined by curiosity

Smartphone owners (182m) Music consumers (155m) Readers (103m)

Audiobooks user (34m)

Podcast listeners (46m)

TV Streamers (63m)

Source: GWI, MRI & ComScore, Pew, 2014-5

//

THE SWEET SPOT A combination of behavior and access

Curious

Digital

//

FINDING THE RIGHT AUDIENCE Suggest focusing on audiences with right behaviors and scale

Curious

Commuters (71m)

Business Travelers (30m)

At home parents (36m)

Fitness Enthusiasts (70m)

Digital Cord Cutters (20m)

Empty nesters (20m)

Source: MRI 2014

//

KEY SURVEY & RESEARCH FINDINGS 57% of podcast listeners advocate listening to audiobooks.

87% of podcast listeners are between the ages 18-45.

71% of 18-45 year olds subscribe to digital content services.

People who enjoy reading books are 16x more likely to advocate audiobooks than people who don’t enjoy reading.

Curious people are 34x more likely to advocate audiobooks than people who are not curious.

62% of audiobook buyers choose audio over other book formats because they can listen to the book in the car (Source: Audio Publishers Association ID 249827)

These three audiences exhibit traits of curiosity and digital savvy and all share in behaviors that provide opportunity to achieve flow often.

TOTAL ADDRESSABLE SIZE - 171M People BUSINESS TRAVELERS (30M)

FITNESS ENTUSIASTS (70M)

40% of podcast listeners listen to podcasts when they travel 87% of podcast listeners that listen to podcasts during travel subscribe to paid digital content services.

71% of podcast listeners listen to podcasts when they exercise.

51% of podcast listeners listen to podcasts while they commute.

80% of podcast listeners that listen to podcast during to exercise subscribe to paid digital content services.

88% of podcast listeners that listen to podcasts while commuting subscribe to paid digital content services.

50% of podcast listeners that listen to podcasts during exercise identify as curious people.

50% of podcast listeners that listen to podcasts while commuting identify as curious people.

55% of podcast listeners that listen to podcasts during travel identify as curious people

(SOURCE: AUDIO PUBLISHERS ASSOCIATION ID 249827)

COMMUTERS (71M)

//

MEDIA APPROACH

MEDIA APPROACH

CU R I O U S PE O PLE WA NT TO B E I N A S TATE O F F LOW: M A K I N G TH E M O S T O F E V E RY M OM E NT

//

MEDIA APPROACH 2012 BRAND SURVEY REVEALED THAT AUDIBLE IS UNLIKELY TO BE A SUBSTITUTE FOR OTHER ENTERTAINMENT

Not perceived as value for money Perceived ‘skill’ at listening to audiobook Audiobooks not a substitute for books or entertainment Not perceived as value for money Source: Audible Custom Study Findings, Jan 2012, Brand Asset Consulting

} }

Perception highly likely to change when using the service

Give people a reason to listen, not a context

//

MEDIA APPROACH

Universal Truth Curious people want to be in the state of flow

Brand Truth

+

Audible complements your passion, putting you in a state of flow

//

MEDIA APPROACH

COMPLEMENT YOUR FLOW //

MEDIA APPROACH

‘COMPLEMENT YOUR FLOW’ IMPERATIVES MEDIA

CREATIVE

Target curious people

Identify their passion & align with it

Be in moments of flow or when people are considering flow

Be a complement to their passion not a substitute

Be alongside their passions

Push to free content such as a trial

//

MULTI-CHANNEL MARKETING MULTI-CHANNEL MARKETING IMPROVES EFFICIENCY AND VOLUME We recommend a multi-channel approach

Efficiency

Better Efficiency

Direct Response, one channel

Direct Response & brand, multiple channels Larger Volume

Spend

//

RESEARCH

TV

DIGITAL RADIO

OUTDOOR & EXPERIENTIAL

PODCAST SPONSORSHIP

DIGITAL VIDEO (MOBILE & DESKTOP)

DR: MOBILE, PAID SOCIAL & DESKTOP

INSIGHT

Audible is competing in the entertainment category not just audiobooks

Our audience’s radio consumption is mostly digital: 80% of their audio consumption

Our audience’s can be identified within certain locations in seeking flow

Podcasting usage is growing: it’s the nearest proxy to audiobooks.

Currently at 46m listeners in US alone

Audiobooks considers are more likely to be digital content subscribers

Mobile, Paid Social & Desktop are a proven acquisition channels and an excellent catch all

APPROACH

Align with TV properties through targeting & sponsorship to gain cultural relevancy

Concentrate on online digital radio only

Be in moments of flow with outdoor and experiential

Concentrate on online digital radio only

Align with their interests through targeted digital video

Continue investment with joined up approach with other media

Sources: Edison Research, 2015

//

GENERATE & HARVEST DEMAND WITH MULTI-CHANNEL APPROACH

TV & DIGITAL RADIO Culturally relevant positioning Outdoor & Experiential Be in moments of flow

Podcast Sponsorship Drive consideration in moments of flow Digital Video (Desktop & Mobile) Drive consideration & conversion

DR: Mobile, Paid Social & Desktop Efficient conversion

DEMAND GENERATION 32%

HYBRID 14%

DEMAND HARVEST 54% //

SUGGESTED BUDGET SPLIT

8

2 6

27

2 5

TV Podcast Sponsorship

Digital Radio

Outdoor & Experiential

Digital Video (Desktop & Mobile)

DR: Mobile, Desktop & Paid Social //

EXAMPLE EXECUTION

TV

Podcast Sponsorship

Digital Radio

Digital Video (Desktop & Mobile)

Outdoor & Experiential

DR : Mobile, Paid Social & Desktop

//

DEMAND GENERATION

CHANNEL PLANNING

TV TEST

TV & DIGITAL RADIO

OUTDOOR & EXPERIMENTAL

DEMAND HARVEST

PODCAST SPONSORSHIP

DIGITAL VIDEO

DR: 80% MOBILE & PAID SOCIAL, 20% DESKTOP

JULY

AUGUST

SEPTEMBER

OCTOBER

NOVEMBER

DECEMBER

//

CHANNEL PLANNING

Prioritize budget for ATL based on commute times (30 mins+)

//

CITY PRIORITIZATION

Seattle San Francisco

Chicago

Atlanta

Los Angeles Washington New York

//

CHANNEL PLANNING

Split Budget by Population for ATL Activity

POPULATION Popula.on

WEIGHTING Weigh.ng

TV TV

DIGITAL RADIO Digital Radio

OUTDOOR & Outdoor & EXPERIENTIAL Experien.al

New York

8,405,837 8,405,837

0.48 0.28

3.82 TBC

0.96 0.56

3.36 TBC

Washington

646,449 646,449

0.04 0.02

0.29 TBC

0.07 0.04

X TBC

Chicago

2,718,782 2,718,782

0.15 0.09

1.24 TBC

0.31 0.18

1.09 TBC

Atlanta

447,841 447,841

0.03 0.01

0.20 TBC

0.05 0.03

X TBC

Los Angeles

16,370,000 3,884,307

0.54 0.22

TBC 1.77

1.09 0.44

TBC 1.55

San Francisco

837,442 837,442

0.03 0.05

TBC 0.38

0.06 0.10

TBC X

SeaFle

652,405 652,405

0.02 0.04

TBC 0.30

0.04 0.07

TBC X

Total

30,078,756 17,593,063

11

816

2 2

65

TERRITORY Territory

Digital Video Mobile)

MOBILE, Mobile & DESKTOP, Desktop & Paid & PAIDSocial SOCIAL

2.00

5.00

20.00

22

55

20 27

PODCAST DIGITAL VIDEO Podcast (Desktop & SPONSORSHIP (Desktop & Mobile) Sponsorship

2

5

27

//

MODELING

HOW ECONOMETRICS MODELING FITS

BEHAVIORAL ANALYSIS

AUDIENCE INSIGHT/SIZING 0%

Mobile

20%

Desktop

40%

TV

Radio

60%

OOH

80%

Print

PS

100%

Testing

MODELING

//

ECONOMETRICS MODELING

DATA

• Ensure data is validated • Identify noise from signals

MODELS

• Apply data to models that will provide actionable insight • Validate models through constant refinement through test & learns

DATA COLLECTING/ SOURCING INFRASTRUCTURE

• Confirm data needs • Validate data sources • Ensure ongoing data collection process

MARKETING/ INSIGHTS TEAM

• Build models to address key business questions • Provide actionable insights to guide channel planning

//

WHICH CHANNELS DRIVE THE BEST RESULTS? Marketing mix models are mathematical frameworks leveraging big data to identify which channels drive the best outcome/results in context of the business environment.

Models allow marketing teams and senior leaders to leverage data to guide planning:

It also quantifiably demonstrates how marketing works together with other business factors to produce the outcome.

• Run simulations based on different marketing budgets and channel allocation strategies.

Owned Media/PR

Earned Media/WoM

Audible App/ Website Performance Brand/ Consideration Metrics

Business Divisions

Marketing

• Assess true attribution across channels for historical and planned campaigns.

OUTCOME: Audible Listeners

Seasonality/ Environment

//

ANALYTICS TO PARSE THROUGH BIG DATA

Intuition is not enough.

With a plethora of data available, we need a quantifiable methodology to assess combination of controlled and noncontrolled factors on upper/ lower funnel acquisition streams.

Marketing mix modeling leverages big data to attribute outcome to marketing by accounting for all combinations of factors impacting the business.

That insight enables us to plan effectively across channels as well as forecasting results based on key future assumptions on controlled and noncontrolled factors using historical data.

Brand Metrics!

WoM!

Facebook / Twitter!

PR!

Paid/Organic Search!

Media!

Promotion!

Economy!

App/Web TrafďŹ c!

Trade!

Price!

Seasonality!

In-App Acquisition!

Web Acquisition!

//

ANALYTICAL ROADMAP Start small: Ensure data collection and analytics plan is a pragmatic solution that starts small and builds out sophistication as results are proven through test & learns.

Since it takes time to source all the data sources, provide files with proper dimensions, an effective approach would be to address specific marketing strategy and business questions in a tiered approach.

ATTRIBUTE ACQUISITIONS ACROSS MARKETING CHANNELS AND BASE

Management Consultants

• McKinsey • Accenture

OPTIMIZE PORTFOLIO OF AUDIENCE SEGMENTS AND THEIR CHANNELS

Agent-Based Modeling

• Marketing Revolution • Nielsen

• ThinkVine

OPTIMIZE CREATIVE MESSAGING

Regression-Based Modeling IDENTIFY IMPACT OF LONG-TERM BRAND EQUITY

• Adometry • VisuallQ

• MMA

//

MODELING PROCESS Depending on the analytics team, there are different approaches to modeling.

Core to all models is leveraging historical data to create response curves representing the impact of each marketing variables/factors in context to external factors.

Should there be limited data, modelers apply Bayesian techniques that takes human intuition/expertise and other qualitative information to guide parameter estimates to fill in data gaps.

DATA

MODELS

CHANNEL INSIGHTS

OUTPUT

10-16 WKS

4-6 WKS

2 WKS

4 WKS

Paid Media Business Operations/Core

Direct

Owned Media App Download Web Visits Search Volume Brand Sentiment

Indirect OUTCOME - AL’s

WoM/Earned Media Social Media Competitive Activity Economy Seasonality

MARKETING/ BUSINESS Marketing and business factors that directly drive acquisitions BASE Level of organic demand for the product without marketing

Historical Attribution Analysis by Channel Optimized Channel Allocation Recommendation to guide planning

Finalize channel allocation strategy and Execute

External

Holidays, ‘Acts of God & relevant events

//

MODELING VARIABLES Identify data needs/sources and collect, validate, and aggregate all data files ranging from controlled and uncontrolled factors into ONE STACK for dashboard and modeling purposes.

1st Party

CONTROLLED FACTORS

PAID MEDIA

UNCONTROLLED FACTORS

NON-MEDIA CONTROLLED FACTORS

OWNED/ EARNED MEDIA

National & Local TV National & Local Radio Print Outdoor Sponsorships

Brand Awareness, consideration, attributes, etc.

Social Sentiment on FB, YT, Instagram and other social networks

Affiliate Online Display Mobile Direct Mail Email Paid Search

3rd Party

Price & Discounting Promotions

Number of likes, followers, shares, etc.

APP/WEBSITE PERFORMANCE App Downloads/ Engagement Audible Website Traffic Organic Search Volume [GQV]

ENVIRONMENT Competitive Activity Macro Indicators GDP, SP500 Index, Unemployment, Weather

Trials

Audience segment geolocation data

Take Rate

Seasonality

Trial to Member Conversion Rate Customer Type

Cultural/ significant events – Olympics, Elections, etc.

//

DATA DETAILS: EXAMPLE Models leverage a data stack based on quantitative metrics expressed in a flat file [csv/xls/SAS] Data is usually expressed as weekly or monthly metrics.

DATA DIMENSION CREATIVE AND/OR CAMPAIGN

WEEK/MONTH

GRP, IMPRESSION

MARKET/DMA/ ZIP CODE

IMPRESSION

IMPRESSION, CLICK, CLICK-THRU, CONVERSION

Print

Online Display

SPEND

# SENT

# SENT, CLICK, CLICK-THRU, CONVERSION

Direct Mail

Email

National & Local TV Outdoor Mobile Sponsorships National & Local Radio Affiliate

Paid Search

1st Party

3rd Party

//

SAMPLE DATA After data collection, we process the data and validate the results to ensure accuracy as the quality of the models are dependent on good data.

We create visual charts to trend out the time-series data to ensure all outliers, missing data, and other anomalies are intentional before leveraging the set for the models.

TRIALS 60

50

40

30

20

10

0 D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A

WEB STORE VISITS 3,500

3,000

2,500

2,000

1,500

1,000

500

0 D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J J A

//

BUILDING MODELS Models take historical data into account and create response curves representing the impact of each marketing variables/factors.

Should there be limited data, modelers apply Bayesian techniques that takes human intuition/expertise and other qualitative information to guide parameter estimates to fill in those gaps.

During data analysis, we separate the noise from signals to identify correlations and ad stock/lag effects to develop statistical models for prediction of responses at desired levels of granularity for multiple metrics.

Models combine stimulation-response regression models with time series models that describe influence of macro variables (seasonality, trends, external factors) as well as short term market dynamics.

MODEL PREDICTIONS AT DESIRED LEVEL OF GRANULARITY

MODEL OVERALL PREDICTIONS

//

ENSURING BEST FIT Validating model accuracy ensures high confidence when working with insights.

Visualizing the mean absolute percent error (MAPE) between modeling outcome and actual data provides transparency on “fit� regarding how well outcome represents actual figures.

In Sample MAPE = 5.3% Out of Sample MAPE = 7.1%

In general, <5% is an excellent fit; 5% to 10 is a strong fit; 10 to 15% is a moderate fit

out of sample (holdout) period

In sample period

2,500,000 !

2,000,000 !

Actual!

Fitted!

Forecast

Forecast!

1,500,000 !

1,000,000 !

500,000 !

- !

2008!

2009!

2010!

2011!

2012!

2013!

2014!

//

TIME SERIES BASE VS MARKETING ATTRIBUTION Marketing Mix Models attribute outcome between overall marketing/business factors from base.

This visualization illustrates the contribution of marketing to the bottom line.

Marketing/Business • Marketing and business factors that directly drive acquisitions • Contribution is also attributed by specific channels and other shortterm factors Base • Factors that do not change very much [brand perceptions/awareness, etc.] – Long-term factors • Level of organic demand for the product without marketing

//

ACTIONABLE INSIGHTS TO GUIDE PLANNING Visualize the % attribution of revenue across channel against % spend and overlay the ROI Index to identify which channels we should invest more, optimize, and re-evaluate or potentially drop from plan.

This is used to guide planning so we know which channels are most effective in driving revenue.

ROI Index = %Attribution / % Spend x 100

Invest More

30%

4.0

Re-evaluate / Drop

Optimize

3.5

25%

3.0

20%

2.5 2.0

15%

1.5

10%

1.0

5%

0.5 0.0

% Spend

U E C

AT AL O

G

O TD O U O

SP EW N

R

R

ED M ER O TH

% Attribution

AP E

IA

TV

BI L O M

IN

SE

RT

E

S

0%

ROI Index

//

RESULTS Digital/print publisher suspected that last click attribution was misrepresenting the effectiveness of their ATL campaigns by not attributing enough credit for driving subscriptions.

Leveraging the primary and third-party data on marketing, business, and exogenous factors, we built a marketing mix model to first identify the contribution of total marketing and its channels to total subscribers so that we can inform the optimal mix for planning.

Models forecasted that shifting the media mix could potentially increase total subscribers by between 6-10%.

Upon presenting this insight, client adjusted their media plan and was able to accrue a 8% increase in total subscribers.

HISTORICAL MIX

Other Media

Mobile

OPTICAL MIX

Other Media

Inserts

National Press

Mobile

Outdoor

Inserts

National Press

Brand TV

Outdoor

Catalogs Catalogs

Brand TV

//

INNOVATION ROADMAP

WHY DO WE NEED IT? The “70/20/10 Approach” maps media tactics into a structured approach that drives KPIs. “The next new thing” is tested in a control environment, and only strong performers move into on-going usage.

70% DRIVE EFFICIENCY

Evergreen media: proven media tactics that positively improve AL-generation efficiency.

On-going optimizations within this 70% continue to improve the overall cost per AL.

20% LEARN MORE

Test and learn media: tactics that show signs of positive contribution to AL generation but need further iteration to improve or prove out efficiency and scalability. These tactics can also be efforts to further scale evergreen media.

10% BREAK NEW GROUND

The very edge of media: tactics that are entirely untested within Audible or even in the market.

These tactics are kept on a very short leash and carefully monitored to avoid waste; they are either moved to the test-and-learn phase or eliminated until it makes sense to re-test.

//

70 / 20 / 10 APPROACH TO INNOVATION

SCALE & EFFICIENCY

INNOVATION

70%

20% LEARN MORE

BREAK NEW GROUND

Evergreen

What we know works

Test & Learn Innovating off of what works

Innovation Brand new ideas

Drive Acquisition

Increase Scale

Break New Ground

Drive Brand Awareness & Consideration

Test New Partners & Audiences

Test New Strategies

Generate Test & Learn Scenarios

Test New Tactics

First-to-Market Opportunities

DRIVE EFFICIENCY

10%

//

70% EXAMPLES

70%

DRIVE EFFICIENCY

Evergreen

What we know works

DRIVE ACQUISITION • Generate the bulk of ALs through consistent partner performance that has been well-measured • Grow scale with ongoing optimizations of the best performing targets and partners while allocating budget away from poor performers

DRIVE BRAND AWARENESS & CONSIDERATION

GENERATE TEST & LEARN SCENARIOS

• Accelerate target audiences through the funnel with above-theline tactics that educate audiences on Audible’s product and value proposition

• Identify the strongest tactics that deserve to scale via test-and-learn campaigns in the 20% bucket

• Ex. Tent-pole TV

• Ex. Finding new partners, similar programming, etc

//

20% EXAMPLES

20% LEARN MORE

Test & Learn

Innovating off of what works

TEST NEW PARTNERS

TEST NEW AUDIENCES

• Test new partners within tactics that have proven to be effective

• Finding new, untapped audiences through analysis of currently performing targets and demographics

• Ex. A/B testing partners, similar to current performers, for a set period of time in order to determine viability

• Ex. Testing look-alike audiences, new targets through cohort analysis, new behavioral types, TV demo targets, etc.

TEST NEW TACTICS • Testing new tactics within existing strategies that have proven to be efficient • Ex. Podcast media/sponsorships, content creation, digital & traditional program sponsorships, audience retargeting, sequential messaging, etc.

//

10% EXAMPLES

10%

BREAK NEW GROUND

Innovation

Brand New Ideas

BREAK NEW GROUND

NEW STRATEGIES

• Investing in opportunities which have not been tested or tried by Audible, or other advertisers in the category

• Testing entirely new strategies which are not derived from existing campaigns that can generate new insights

• Ex. Develop an interactive OOH ad which allows users to experience Audible within key markets

• Ex. Sponsor one or more episodes of a TV series

FIRST-TO-MARKET OPPORTUNITIES • Trialing new technologies, products, and opportunities (some with beta exclusivity) • Ex. Craft a campaign to participate in beta of the new Facebook DSP messaging, etc.

//

2H 2015 INNOVATION THOUGHT STARTERS

DIGITAL OOH & EXPERIENTIAL

PODCAST CONTENT CREATION

SOCIAL MEDIA CONTENT STRATEGY

• Simulate Audible moments for commuters in transit terminals.

• Sponsor marathons and other events where Audible can promote

• Bring the Audible experience to another platform that complements curiosity.

• Launch a podcast series that extends the reach of your content.

• Continue to feed the curiosity of the digitally native Audible listener.

• Provide bite-sized content across existing and emerging social media platforms to keep them hungry.

“flow.”

//

TEST & LEARN

TESTING PROCESS

Select a hypothesis for testing

Choose the right metrics

Establish media buying rules

Analyze data / results

//

TEST & LEARN TEST & LEARN APPROACH GUIDES ON-GOING CAMPAIGN

TEST & LEARN + INNOVATION

EVERGREEN

30%

70%

Online

Mobile

Traditional

Partners, Tactics & Targeting (planned) Trial Volume Cost-per-Trial AL Volume Cost-per-AL Click-to-AL % Trial-to-AL % Engagement

contextual insights

demographic insights

behavioral insights

Mobile

Traditional

Partners, Tactics & Targeting (applied)

Organic Lift in Trials & ALs Lift in DR metrics (CVR / CTR) Lift in Trial-to-AL take rate Lift in site visitation and/or GQV

day-part insights

Online

location insights, etc.

Trial Volume Cost-per-Trial AL Volume Cost-per-AL Click-to-AL % Trial-to-AL % Engagement

Organic Lift in Trials & ALs Lift in DR metrics (CVR / CTR) Lift in Trial-to-AL take rate Lift in site visitation and/or GQV

evaluation, iteration

//

DIGITAL EXAMPLE PARAMETERS

MEASUREMENTS

• targeting : run of network

• Inventory quality : Cost-per-trial & click-to-trial % as primary indicators

• pacing : even, week-to-week • flighting : 30-days • purchase model : eCPC or eCPM, static bid cap across all partners

• scale : trial volume as primary indicator • efficiency : comparative CPT (per category of partner) • misc. to note : capabilities, specializations

• budget : $6,250 per partner, per week

• evaluation : week-over-week

• creative : generic, cross-segment, cross-partner

• approach : partners categorized by potential scale & efficiency

July 2015

(COMPARATIVE)

EVEN PACE, EVEN SPEND ACROSS ALL PARTNERS

PARTNER 1

click-to-trial % & trial volume

EX : CATEGORY 3

PARTNER 2

click-to-trial % & trial volume

EX : CATEGORY 4

PARTNER 3

click-to-trial % & trial volume

EX : CATEGORY 2

PARTNER 4

click-to-trial % & trial volume

EX : CATEGORY 2

PARTNER 5

click-to-trial % & trial volume

EX : CATEGORY 1

PARTNER 6

click-to-trial % & trial volume

EX : CATEGORY 3

//

+SCALABILITY

PARTNER TEST – COMPARATIVE CATEGORIZATION

PARTNER 1 Q2 – SCALABLE, INEFFICIENT

PARTNER 4 Q1 – SCALABLE, EFFICIENT PARTNER 6

PARTNER 2 +EFFICIENCY

PARTNER 5 Q3 – NOT SCALABLE, INEFFICIENT

PARTNER 3 Q4 – NOT SCALABLE, EFFICIENT

//

TESTING TRADITIONAL CRITERIA & SELECTION

3 TEST CITIES NE

SW

3 CONTROL CITIES 3 TEST CITIES 3 CONTROL CITIES 3 TEST CITIES

MW

SE

3 CONTROL CITIES

3 TEST CITIES 3 CONTROL CITIES

NW

REGIONALLY REPRESENTATIVE CITIES COMPARABLE IN: POPULATION DEMOGRAPHICS COST OF MEDIA BRAND PERCEPTION

3 TEST CITIES 3 CONTROL CITIES

//

TESTING TRADITIONAL ABOVE THE LINE MEASUREMENT APPROACH

3 TEST CITIES NE

SW

SE

ABOVE THE LINE ACTIVITY

POST-CAMPAIGN BENCHMARKS

3 CONTROL CITIES 3 TEST CITIES 3 CONTROL CITIES 3 TEST CITIES

MW

PRE-CAMPAIGN BENCHMARKS

3 CONTROL CITIES

3 TEST CITIES

BRAND SURVEY

BRAND SURVEY

AVERAGE CLICK THROUGH RATE

AVERAGE CLICK THROUGH RATE

AVERAGE CLICK-TO-TRIAL RATE

LOCAL TV, E.G.

AVERAGE CLICK-TO-TRIAL RATE

AVERAGE TRIAL VOLUME

AVERAGE TRIAL VOLUME

SITE TRAFFIC

SITE TRAFFIC

3 CONTROL CITIES

NW

3 TEST CITIES 3 CONTROL CITIES

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WHAT WE NEED FROM AUDIBLE PRE-TEST CAMPAIGN BENCHMARKS

BENCHMARK AVERAGE CLICK-THROUGH RATES BY CITY (PAID SOCIAL & PAID SEARCH) BENCHMARK AVERAGE CLICK-TO-TRIAL RATES BY CITY (PAID SOCIAL & PAID SEARCH) BENCHMARK AVERAGE TRIAL VOLUMES BY CITY BENCHMARK AVERAGE ORGANIC SITE TRAFFIC BY CITY BENCHMARK AVERAGE ORGANIC SEARCH VOLUME BY CITY

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CORRELATION MEASUREMENT INDIRECT MEASUREMENT OF TRADITIONAL & DIGITAL MEDIA IMPACT (ILLUSTRATION PURPOSES ONLY)

• Ongoing analysis of trends and correlations with media spend to further measure media impact beyond direct attribution

• Measuring the effectiveness of media spend which cannot be directly attributed to conversions

• Leveraging output to craft test & learn scenarios to prove/disprove correlation hypotheses

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REPORTING

REPORTING Dashboard which combines easy-to-use pivot tables with visual representations of performance from both topline and granular perspectives. Each view can be easily adjusted to provide the right level of detail with the correct visual representation based on what is required for any given individual or situation.

Detailed write-ups delivered on a weekly, monthly, and quarterly basis which detail in plain English why media is performing as it is, optimizations made, the impact those optimizations have had, and comprehensive rationale behind future planning based on those factors.

EXECUTIVE SUMMARY Topline view of spend and performance by channel When you need a simple, quick view into the overall health of each channel

PACING SUMMARY Spend pacing by channel and partner When you need to see where budget reallocations are necessary across channels

DAILY/WEEKLY NETWORK PERFORMANCE Detailed spend and performance metrics by channel & partner When you need a detailed view into all media & performance metrics available

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EXECUTIVE SUMMARY

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PACING SUMMARY

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DAILY/WEEKLY/MONTHLY SUMMARY

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CROSS-CHANNEL DASHBOARD

Regional Breakouts

Offer/Creative Breakouts

Flight Breakouts (Quarter, Month, Year, etc)

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CROSS-CHANNEL REPORTING

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TECH SOLUTIONS ECOSYSTEM By selecting the technology partners that fit Audible best, M&C will create a technology ecosystem that improves ALgeneration efficiency by enhancing campaign management and increasing visibility.

Data flow Campaign Management

Analysis and Understanding

Ad Servers

Visualization Tools

Social Listening Multi-touch Platforms

PMDs In-app Attribution SDKs

Analytics Platforms

DMPs

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TECHNOLOGY PHILOSOPHY There is no single technology ecosystem that fits all businesses. Every business is unique and deserves an ecosystem that consists of platforms individually selected to address its specific challenges and needs.

Marketplace Evaluation

Customized RFP

Final Selection

Who are the major players? What are their main strengths, weaknesses, and differentiators?

Work with Audible to create a set of evaluation criteria that is tailored to the needs and limitations of all relevant teams (BI, Marketing, CRM, etcâ&#x20AC;Ś)

With a shortlist of possible candidates, evaluation meetings are conducted before selecting the platform that best meets Audibleâ&#x20AC;&#x2122;s specific criteria

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AD SERVERS Ad servers store creative units and systematically deliver them to sites and apps; they also enable delivery reporting and conversion tracking. Many ad servers now have both desktop and mobile capabilities.

KEY BENEFITS

CHALLENGES

CRITERIA

Increased creative rotation control

Pricing can be prohibitive for high impression plans

Number of partner integrations

Unified digital reporting

Conversion attribution for (m)web events

Pixel implementation required for conversion attribution

Often limited in-app conversion tracking

Mobile capability

Server uptime

Possible Partners

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PMDS Preferred Marketing Developers (PMDs) use API integrations with paid-social platforms (Facebook, Twitter, etc.) to create a unified interface for managing paid-social campaigns. Many PMDs also add capabilities not available on the native platforms.

KEY BENEFITS

CHALLENGES

CRITERIA

Automated optimization and bid rules

Rapidly changing marketplace requires frequent evaluations

Number of paid-social API integrations

Comprehensive paid-social reporting

Reliance on one platform for all paid social

Number of third-party data partnerships

Added targeting options

Non-Facebook integrations often still nascent

Quality of support

Possible Partners

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DMPS Data Management Platforms (DMPs) act as a centralized repository for an advertiserâ&#x20AC;&#x2122;s data. After ingesting data, DMPs are able to create audience segments that can be sent to integrated media partners for targeting with digital ads. DMPs also house all 1st and 3rd party data for ad hoc analysis and modeling. Access to this first-party DMP data can be restricted.

KEY BENEFITS

CHALLENGES

CRITERIA

Allows for leveraging of first-party data

Access to extensive Audible data required to be impactful

Quality of user interface

Marries first-party and third-party data

Requires frequent refreshing of data

Number of integrated partners

Enables highly targeted messaging

Needs strict privacy controls

Stability of platform

Possible Partners

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IN-APP ATTRIBUTION SDKS In-app attribution SDKs are designed to track in-app conversion events and attribute them back to a mobile-media partner. Post-backs are sent to partners when they drive a conversion. These real-time data points allow media partners to maximize their optimization algorithms.

KEY BENEFITS

CHALLENGES

CRITERIA

Provides lastclick attribution of conversions

Requires implementation of the SDK into the app

Number of integrated media partners

Helps media partners optimize

No reliable impressionbased tracking

Reporting interface

Allows for budget allocation based on cost per action

Routine QA is required to ensure proper postbacks to partners

Ability to track multiple conversions

Possible Partners

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MULTI-TOUCH PLATFORMS Multi-touch attribution platforms go beyond last-touch and last-click attribution. Instead, they track the consumer journey across all digital ad impressions that lead to a conversion. Models can then be built that assign percentages of a conversion to each touch point. Often these companies can give insights beyond digital as well.

KEY BENEFITS

CHALLENGES

CRITERIA

Allows for fuller understanding of the path to conversion

Attribution weighting depends on a subjective model

Ability to track crossdevice

Optimizations no longer reliant on last click

Cross-device attribution is often probabilistic

Deterministic attribution capability

Visibility into crossdevice attribution

Impression tracking not always available

Flexibility of model

Possible Partners

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ANALYTICS PLATFORMS Analytics platforms can be deployed either in-app and/or on-site to provide a fuller picture of what consumers are doing on the site or in the app. These go beyond the conversion events tracked by attribution SDKs and/or ad servers, tracking user behaviors and metrics such as time spent.

KEY BENEFITS

CHALLENGES

CRITERIA

In-depth user activity visibility

Requires implementation of site code or SDK

Ease of implementation

Does not send data back to media partners

Reporting interface

Often requires separate tools for inapp vs. on-site

Ability to report in real time

Can be used for site / app optimizations

Assist with identifying issues that cause app crashes

Possible Partners

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VISUALIZATION TOOLS Visualization tools create customizable graphical representations of data for both at-a-glance performance evaluations via dashboards and in-depth analysis via quickly generated graphs and charts. These tools would cover data from offline and online media.

KEY BENEFITS

CHALLENGES

CRITERIA

Simplifies complex data

Data privacy needs to be ensured

Flexibility for customization

Dashboards allow for quick views of performance

Needs to plug into many data sources

Ability to ingest volumes of data

Can easily generate graphics for presentations

Has to adapt to many different KPIs

Collaboration capabilities

Possible Partners

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SOCIAL LISTENING TOOLS Social listening tools user “spider” technologies to crawl social platforms, such as Facebook and Twitter, to measure references to a brand. Many of these tools also have algorithms that gauge the sentiment of the social posts to report back on how audiences feel about the brand.

KEY BENEFITS

CHALLENGES

CRITERIA

Understand impact on social media

Doesn’t tie back to conversion events like an AL

Quality of sentiment analysis

Receive real-time feedback on brand perception

Requires socialmanagement expertise to parse data

Ability to archive posts

Increases social intelligence for better interaction with audiences

Need to routinely evaluate tools to account for new social platforms

Functionality to flag complaints

Possible Partners

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MEASUREMENT

MEASUREMENT & OPTIMIZATION Every dollar spent on paid media should have a positive impact on the main business objective of driving efficient ALs. As such, the overall cost per AL will be constantly monitored to help determine the impact of ATL activity on the performance of BTL channels.

However, not all media can be or should be judged against direct contributions to AL volume. Media should be evaluated in three cohorts:

Non Digital ATL

Digital ATL

$120 Cost Per AL

Digital BTL

Budget between each cohort is allocated based on correlations between spend within that cohort and lifts in overall ALs. Ex: if increased investment against Digital ATL drives brand lift but no movement in AL volume, that spend will decrease.

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ATL NON-DIGITAL KPIS Channels: TV, OOH, experiential Every dollar spent on paid media should have a positive impact on the main business objective of driving efficient ALs. As such, the overall cost per AL will be constantly monitored to help determine the impact of ATL activity on the performance of BTL channels.

RANKED KPIs

IMPACT ON Brand Social Media Business Objectives

Awareness: consideration: GQV Mentions: sentiment: shares Overall AL and trial volume / cost per: Overall average member conversion rate

Site / App metrics

Take rate: visits: installs

Digital Campaigns

CTR: attributable CPAL, CPT, CPI

MEASURED BY Surveys / studies: Google Social listening tools 1st-party Audible data Analytics platforms / SDKs Ad servers / SDKs

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ATL DIGITAL KPIS Channels: Desktop, mobile, podcast sponsorships, digital radio Budgets will be prioritized towards the ATL digital partners whose spend correlates best with lifts in brand social metrics.

Being digital platforms, we can also see directly attributable impacts upon business objectives, such as ALs and trials, so those will act as a significant secondary metric.

RANKED KPIs BRAND (Awareness: consideration) SOCIAL (Mentions: sentiment: shares) TRIAL (Volume / Cost per)

MEASURED BY Surveys / studies; Google Social listening tools Server / SDK

AL (Volume / Cost per)

REF tag (source code)

Member conversion rate

Server / SDK & REF tag

Site / app metrics (Take rate: visits: installs)

Analytics platforms / SDKs

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BTL DIGITAL KPIS Channels: Desktop and mobile As trial data can be passed in real-time to partners, it is the primary BTL digital KPI. ALs and member conversion rate are strong secondary KPIs, so partners who generate non-converting trialists are removed.

BTL media is expected to have some minimal level of impact on brand and social, but those will not be viewed as key differences

RANKED KPIs TRIAL (Volume / Cost per) AL (Volume / Cost per) Member conversion rate

MEASURED BY Surveys / studies; Google Social listening tools Server / SDK

Site / app metrics (Take rate: visits: installs)

REF tag (source code)

SOCIAL (Mentions: sentiment: shares)

Server / SDK & REF tag

BRAND (Awareness: consideration)

Analytics platforms / SDKs

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FIRST-PARTY DATA INFORMS MEDIA BUYING

DATA

MEDIA INSIGHT

ACTION EXAMPLE

AdvertiserID, DeviceID, CampaignID, Location/Geo

AdvertiserID, CampaignID, DeviceID, Cookie Data (Path-to-CVR), 3rd Party Data

AdvertiserID, CampaignID, DeviceID, CreativeID, Cookie Data, Source Code

AdvertiserID, CampaignID, DeviceID, Location Data, Third party Data

AdvertiserID, CampaignID, Timestamp, Location Data

DEMOGRAPHIC

BEHAVIORAL

CONTEXTUAL

GEO / LOCATION

DAYPART

Identify best performing combinations of age, gender, HHI, lifestyle, education, etc.

Identify typical user behaviors / paths between ad engagement and conversion.

Identify the types of media, partners, verticals to scale, and where to scale back.

Identify best converting and scalable markets

Identify the best performing times of day / days of week based on CVR & volume.

ACTIONABLE INSIGHT

ACTIONABLE INSIGHT

ACTIONABLE INSIGHT

ACTIONABLE INSIGHT

ACTIONABLE INSIGHT

Females between the ages 25-34 with a college education and $75k+ HHI have a higher propensity to convert to trial on blog and long-tail video inventory.

Users who have been exposed to above-theline tactics, such as videos and high-level sponsorships, have a higher propensity to engage with a direct response ad and ultimately convert to trial.

Audiences exposed to ads for sci-fi audiobooks within science, education, or gaming content verticals are more likely to convert to trial.

Audiences in major commuter cities (such as Los Angeles, New York, and Chicago), convert best off of ads for self-improvement and finance books within podcast content.

Audiences in major commuter cities (such as Los Angeles, New York, and Chicago), convert best off of ads for self-improvement and finance books within podcast content.

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FORECASTING

IMMEDIATE

Build a media mix and plan based on the $120 cost per AL goal, using assumptions grounded in Audible 1st-party data and 3rd-party research.

Key inputs

Overall ALs, average click-to-trial rates, trial volume by month, site visitation volume, current measured digital cost-pers, field research results, audience sizing data.

SHORT-TERM

Design tightly restricted exposed / unexposed tests of ATL spend. Correlations between that spend and lifts in overall cost-per AL will be used to forecast changes in efficiency based on re-distribution of budget.

Key inputs

Results from media tests, overall ALs, trial volume by week, and site visitation volume, BTL media results (e.g. CPT).

LONG-TERM

Cross-channel econometric model.

Key inputs

Two yearsâ&#x20AC;&#x2122; of the following historical data points - spend, activity level, creative, markets and campaign names across all channels, results from all campaigns, overall AL, trial, and site visitation volume.

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