DIGITAL REVENUE OPTIMIZATION USING LISTENER

1215 Hightower Trail

Bld. A, Ste. 100

Atlanta, GA 303501

AGENDA

◎LISTENER

◎APPROACH AND CASE STUDIES

◎FUTURE FOR PUBLISHING

LISTENER3

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TECHNOLOGY OVERVIEW

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AUDIENCE GOALS

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PAID SUBSCRIBER ACQUISITION EXECUTION

2017 MILESTONES

1B PV/MonthSeptember 2017

179% Growthyear-over-year

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225M events per day

22TB New Data processed each month

PRODUCT ROADMAP

✓ 2017 Q1: Launched Audience Package

✓ 2017 Q2: Development launched for the Content Module

✓ 2017 Q2: Launched Listener Tag Manager

✓ 2017 Q2: Launched metricsXchange digital benchmarking

✓ 2017 Q2: Patent pending

✓ 2017 Q3: Audience Hub and Clustering (add-on to AP)

2017 Q4: Finalize Content Module with Article Lifetime Value

2017 Q4: Productize digital user CLV and acquisition model

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2017 CASE STUDIES IN PROGRESS

• Intelligent paywall

• Predictive modeling for digital acquisition

• First party data

• Economics of content

• Cart abandonment

• Targeted newsletter signups

• Behavioral clustering 9

APPROACH &CASE STUDIES

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FLYBYS• 74% of users

• One page view/mo

• Social media

referrers

• Goal: convert to

repeat visitor

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AUDIENCE SEGMENTATION

STABLE USERS• 10% of users

• 5 page views/mo

• 2-3 article views/mo

• Repeat visitors

• 4:51 minutes on site

• Goal: collect email

via registration

FANATICS• 2% of users

• 30 page views/mo

• 5 content areas

• 20% of Fanatics are

already registered

• Multiple devices, e-

edition, apps,

• Goal: convert AND

retain subscribers

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USER TARGETING

HighMedium

Know

nA

nonym

ous

• Heavy email

marketing to engage

• Minimal subscription

offers

• Heavy ad targeting

Low

Engagement Level

• Targeted emails based on

preference

• Email subscription offers

• Segments for ad

targeting

• Target content

• Enroll in elite

membership program

• First party ad targeting

• Targeted emails

• Retain/engage

• Engage and grow

through social media,

commenting

• Newsletter signup

• Registration

• Segments for ad

targeting

• Register and convert to

grow known audience

• Forced monetization:

remove ad blocker or pay

for content

Ident

ifie

d U

ser

OVERALL CONVERSION TRENDS

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• Desktop converts better than mobile• Direct (typed) traffic converts best• Google shows the best social/search conversion• Facebook shows the worst conversion• Local converts better than non-local audience• Content depends on market, property, quality…etc.

DEVICE EXAMPLE – LARGE METRO

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0.04% of monthly users convert on Desktop vs.

0.01% on Mobile

0.34% users who hit the paywall convert on Desktop

vs. 0.15% on Mobile

REFERRER EXAMPLE – LARGE METRO

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Of the users who hit the paywall, the

conversion rate by referrer is:

0.47% Direct 0.16% Google

0.07% Facebook

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0.015%

0.029%0.065%

0.189%

0.009%

0.035%

0.143%

0.000%

0.020%

0.040%

0.060%

0.080%

0.100%

0.120%

0.140%

0.160%

0.180%

0.200%

Un

iqu

e U

sers

Conversion Rate

AUDIENCE EXAMPLE – LARGE HYPERLOCAL

ANONYMOUS USER PROPENSITY

Acceleration in page views and unique days for local users are best predictors

RECOMMENDATION: apply user targeting to high propensity users with a custom subscription offer without the traditional checkout process

0.00%

0.05%

0.10%

0.15%

0.20%

0.25%

0.30%

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

80,000

90,000

5 11 13 18 20 22 30 32 36 38 48 50 52 61 64 67 69 71 73 75 77 80 84 86 88 90 95 98

Co

nve

rsio

n P

rob

abili

ty

An

on

ymo

us

Use

rs

User Conversion Rank

Anonymous User Conversion Estimate

Users Seen an Offer Selected an Offer Reached Payment Probability

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INTELLIGENT PAYWALL FORECASTING18

$83,429$130,497

$200,657

$324,996

-$8,669 -$23,211 -$50,267 -$105,6280

500

1,000

1,500

2,000

2,500

3,000

3,500

-$300,000

-$200,000

-$100,000

$0

$100,000

$200,000

$300,000

$400,000

$500,000

$600,000

$700,000

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Incr

em

en

tal S

ub

scri

be

rs

Incr

em

en

tal R

eve

nu

e

Meter Setting (number of free articles per user)

Incremental Revenue Estimate - Conversion Impact

12-month Sub Revenue 12-month Advertising Risk 12-month Net Subscribers

Incremental

subscription

revenue at

different meter

settings

Incremental

advertising

revenue risk at

different meter

settings

Over 3X conversion for users identified as “high propensity”

• Users were targeted based on acquisition propensity via email

• Volumes are low due to small list of engaged registered non-paid users –testing confirmed and refined the model

• Now launching campaign for newsletter opt-ins who are not registered and for anonymous users through paywall

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EMAIL TARGETING TEST

List Name Emails sent Open rate Click rate Total conversions Conversion rate

Rank 3 - Mather Ranking of most likely to convert 2,368 17.91% 1.20% 8 0.34%

Rank 2 6,994 22.75% 1.83% 11 0.16%

Rank 1 612 16.23% 0.76% 0 0.00%

Rank 0 (random registration list that ST picked) 7,110 10.28% 0.51% 7 0.10%

AD SERVER TARGETING USING HOUSE ADS

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2X conversions targeting engaged users vs. control

FIRST PARTY DATA

The Columbus Dispatch 221,247

Columbus Blue

Jackets

116,402

Matched21,416

242,663

137,818

9% of entities matched from current and former Dispatch subscribers16% of entities matched from all Blue Jackets ticket buyers

2,400 entities (11% of matches) accessed content online

LOOKALIKE AUDIENCES

Statistical analysis completed on subscribers in the local DMA 210,238 subscriber entities given a ticket score

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Columbus Dispatch current and previous subscribers ranked from 0 to 100 on probability of buying Blue Jackets tickets

Columbus Dispatch anonymous web visitors ranked from 0 to 100 on probability of buying Blue Jackets tickets

Statistical analysis completed on anonymous users in the local DMA 625,986 entities given a ticket score

FIRST PARTY DATA TAKEAWAYS

• 15-20% lift in engagement vs. comparable ad sizes for advertiser

• 9:1 ROI for SEO

• 18:1 ROI for display

• Known users are key to growing value of advertising

• Improves yield for local direct advertising sales

• Can be connected to programmatic exchanges, retargeting tools, and DMPs

See the article in our new monthly newsletter!=http://www.mathereconomics.com/wp-content/uploads/2017/09/Mather-Insights_TargetingCustomAudience_SEP17.pdf 23

CONTENT MODULE

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DRILL DOWN TO ARTICLE LEVEL

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KEY METRICS BY ARTICLE AND AUTHOR

Internal, direct, fanatics, local, desktop rank high for conversion

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BREAKDOWN CONTENT/ARTICLE

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0%

10%

20%

30%

40%

50%

0%5%

10%15%20%25%30%35%

Rat

io

Shar

e

Fanatics Audience Size by Content TypeShare Ratio

EACH ARTICLE AND AUTHOR ARE SCORED

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FUTURE29

2018 REVENUE GENERATION

• Subscriber revenue growth – Digital & Print

• Nurturing users with targeted messaging

• Registration for incremental access to content

• Growing known users onsite

• Intelligent paywall + dynamic metering

• Article lifetime value

• First party data for advertising yield

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