rick ducey

TheLocalMedia&Advertising Experts

How National Brands Might Focus

On Local Search in a Mobile

Wearable, Connected WorldRick Ducey

December 11, 2014

Park City, UT

© 2014 BIA/Kelsey. All Rights Reserved.

2

BIA/Kelsey’s US Local Forecast: 2015-2019

All Paid Ad Spending Targeting Local Audiences

Mobile

Search

National vs Local marketers

What Will Search Look Like Next?

Mobile, Wearable, Connected World

Getting to the “Connected Me”

What it Means for National Brands

Topics


3

National OverviewTotal U.S. Spending in Local Markets


4

Local Ad Market Currently

Dominated by Traditional Media

Newspapers Print

11.5%

Newspapers Online

2.4%

Direct Mail

27.4%

TV O-T-A

13.9%

TV Online

0.7%

Radio O-T-A

10.3%

Radio Online*

0.8%

Print Yellow Pages

2.2%

Internet YP

1.6%

OOH

5.8%

Cable

4.9%

Magazine

1.3%

Magazine Online

0.2%

Online / Interactive

10.7%

Email

1.5%

Mobile

4.7%

2015 U.S. Local Media Revenues — $139.3 Billion

*Notes: “O-T-A” means “over the air.”

Radio online revenues include online revenue from terrestrial and online streaming services.


5

Steady Shift Toward Digital Media

$106.1 $104.2 $105.6 $103.9 $105.0 $103.5

$31.0 $35.0$39.4 $44.5

$49.7 $55.0

$0

$20

$40

$60

$80

$100

$120

$140

$160

$180

2014 2015 2016 2017 2018 2019

Traditional Online/Digital

US$ B

illio

ns

2014-2019

CAGRs:

Total Media

CAGR 3.0%

Online/Digital

Media

CAGR 12.2%

Traditional

Media

CAGR -0.5%

$139.3

Note: Numbers are rounded.

$137.0$145.0

$148.4$154.7

$158.5


6

Local Ad Market Less Dominated

by Traditional Media in 2019

Newspapers Print

8.2%Newspapers Online

2.4%

Direct Mail

24.2%

TV O-T-A

13.8%TV Online

0.9%

Radio O-T-A

9.6%

Radio Online*

1.2%

Print Yellow Pages

0.9%

Internet YP

1.7%

OOH

5.8%

Cable

4.7%

Magazine

0.9%

Magazine Online

0.3%

Online / Interactive

12.5%

Email

1.7%

Mobile

11.3%

2019 U.S. Local Media Revenues — $158.5 Billion

*Notes: “O-T-A” means “over the air.”

Radio online revenues include online revenue from terrestrial and online streaming services.


7

Total US Local Advertising

$83.0 $83.6 $84.7 $85.7 $88.1 $89.7

$50.2$54.4 $56.1

$61.4 $63.4$68.9

$0

$10

$20

$30

$40

$50

$60

$70

$80

$90

$100

2013 2014 2015 2016 2017 2018

Bill

ion

s

Total Local Advertisers Revs. Spending

Local Advertisers National Advertisers

62.3% 60.6% 60.2% 58.3% 58.1% 56.5%

37.7% 39.4% 39.8% 41.7% 41.9% 43.5%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018

Total Local Advertisers Revs. Distribution


Source: BIA/Kelsey, 2014

Note: “Local” refers to advertising that targets local audiences.

National advertisers increase share of total ad spend targeting local

audiences.


8

US Local Mobile Advertising

$0.4$0.8

$1.5$2.2

$3.4

$4.7

$2.4

$3.7

$5.6

$7.0

$9.1

$11.0

$0

$2

$4

$6

$8

$10

$12

2013 2014 2015 2016 2017 2018

Bill

ion

s

Local Mobile Advertisers Revs. Spending


15.0% 18.0% 21.0% 24.0% 27.0% 30.0%

85.0% 82.0% 79.0% 76.0% 73.0% 70.0%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2013 2014 2015 2016 2017 2018

Local Mobile Advertisers Revs. Distribution



Note: “Local” refers to advertising that targets local audiences.

Local advertisers increase share of Mobile ad spend targeting local audiences.


9


Mobile and Search

Forecast

9


10

Mobile Local Ad Spend: Five-Year Forecast

$4.3

$6.6

$9.1

$12.1

$15.1

$17.9

$0

$2

$4

$6

$8

$10

$12

$14

$16

$18

$20

2014 2015 2016 2017 2018 2019

US$ B

illio

ns


Mobile Local Ad Spend Will More than Quadruple 2014-2019


11

Local vs. National Ad Spend in Mobile

$8.98$12.16

$15.13$18.42

$21.26$23.77$4.27

$6.58

$9.09

$12.08

$15.06

$17.86

$0

$5

$10

$15

$20

$25

$30

$35

$40

$45

2014 2015 2016 2017 2018 2019

Non-location Targeted Location Targeted

US$ B

illio

ns


$13.25

$18.75

$24.22

$30.50

$36.32

$41.63

43%

32%

Location Targeted Spend Will Also More than Quadruple 2014-2019


12

Location Targeted Mobile Ad Revenues:

Key Takeaways

Defined as advertising targeted based on a user’s location.

It includes large national advertisers and SMBs.

Location specific ad copy or calls to action (i.e., call local store), will also

classify a given ad as location targeted.

National Brands and Agencies executing locally:

Adoption of mobile local advertising tactics (i.e., geo-fencing, click-to-call,

click to map).

National advertisers’ natural evolution to adopt effective, increasingly

available, and currently undervalued mobile local ad inventory.

Innovation among ad networks and ad tech providers will drive value.


13

Location Targeted Mobile Ad Revenues:

Key Takeaways (cont’d)

Ad premiums will result from higher performance for

location targeted mobile ads vs. non-location targeted

ads.

These performance deltas (such as click through rates)

are a function of:

Higher relevance, immediacy and alignment with consumer

local buying intent.

All of which are more prevalent in mobile than in other print

and digital media.

For example, half of mobile searches have intent to find local

information or products, compared to the 17 percent of desktop

searches that carry comparative local intent.


14

Location Targeted vs. Non-Location Targeted

Ad Revenues: Key Takeaways

Location targeted mobile advertising is a subset of

overall U.S. mobile advertising revenues The share of the overall mobile ad revenue pie attributed to location

based campaigns will grow from 32 percent ($4.3 billion) in 2014 to 43

percent ($17.9 billion) in 2019.

This growth is driven by Google (33 percent of paid clicks now come

from mobile devices); and Facebook (53 percent of ad revenues

attributed to mobile, up from 23 percent last March).

Google’s Enhanced Campaigns will drive much of this growth by forcing

mobile ads on search advertisers (default campaign) and a mobile

advertising learning curve and adoption cycle for all search advertisers,

including SMBs.

Enhanced Campaigns will also notably close the current gap between

mobile ad rates and desktop equivalents.

This will play out as an influx of advertisers in Google’s bid marketplace

for mobile keywords will naturally boost bid pressure and thus CPCs.

This shift is already underway.

*For a more thorough analysis of Enhanced Campaigns, see our blog analysis

http://blog.biakelsey.com/index.php/2013/03/20/lil-2013-enhanced-campaigns-google-speaks/


15

Core search volume from PCs is expected to decrease by -

2.8% in 2014, as an increasing share of search volume

shifts to mobile devices.

In January 2014, for first time Americans used smartphone and

tablet apps more than PCs to access the Internet.

Mobile devices accounted for 60% of total digital media time

spent in May, up from 50% a year ago according to comScore.

Local desktop search revenues are expected to grow at a

muted 2.6% CAGR through 2019. Major drivers include:

Increasing click-through rates, with

CPCs decreasing over the next few years.

The lower CPCs and increased volume of mobile search are

pushing down overall CPCs for the online search industry.

Local Search


16

Local Search

$7.1

$7.2

$7.4

$7.6

$7.8

$8.1

$6.6

$6.8

$7.0

$7.2

$7.4

$7.6

$7.8

$8.0

$8.2

2014 2015 2016 2017 2018 2019

CAGR +2.6%

US$ B

illio

ns


17

Mobile Search Owned by Google


18

What are smartphone users searching for?


19

Local Share of Mobile Ad Spend by Format

Display

26.1%

Search

51.1%

SMS

2.6%

Video

7.5%

Native/

Social

12.8%

2015

Display

21.9%

Search

46.5%

SMS

1.5%

Video

6.0%

Native/

Social

24.2%

2019

Native/Social Paid Ads Will Double 2015-2019, Mobile Local Search Declines


20


Majority of search has

moved from desktop to

mobile.

Is the next migration from

mobile to wearable?

What’s next in Local Search?

20


21

Let’s see, am I the only one wondering about

this?


22


What’s going on with

wearables?

22


23

Form Factors for Wearable Tech


24


25

High Awareness and Familiarity

Source: Ipsos MediaCT, October 2014


26

Wearables Rank High in Purchase Intent


Almost a fifth of US Adults Intend to Purchase Wearable Technology


27

Key Uses and Purchase Criteria for Smart

Watches – It’s About Tracking Activity

Top Three Uses

1. Activity tracking

2. Time telling

3. Basic apps

Top Three Purchase

Criteria

1. Price

2. Functionality

3. Activity tracker

Source: GfK, as cited in press release, September 8, 2014.

Note: n=1,000 US respondents


28

Among Intended Purchasers, Majority

Attracted to Fitness Monitors and Watches



29

About 40% of Internet Users Plan To or Do

Track Fitness/Health


30

It’s mostly about the “connected wrist” for

device sales


31

Wearable Use Among Internet Users Doubled


32

Tracking Fitness is the Major Use Case

Fitness


33

Wearables Have Low Use Rates at the

Moment


34

Privacy is not the main barrier to adoption of

wearables.


35


So what does all this mean

for national brands and

local search?

35


36

Google Now is just the beginning.

36


37

Connected Me

Mobile

Internet of Things

Big Data

Social

Channels

Connected Home

Connected Car

Media Analytics

Wearable Technology Creates the “Connected Me”

and Further Fuels a Data Storm of SignalsConnected Me Data Combined with Other Data Puts Targeting into HyperDrive

and Brings Us Closer to Nirvana of “Closed Loop” Marketing



38

Younger demos will be into wearables sooner and in

greater force than older demos.

Early adopters are more fitness oriented.

Wearables continue to pack in more sensors.

Location signals from GPS, Bluetooth beacons, cell towers

establish your current context and historical time and

space movement patterns.

Advertisers will know when you are sleeping, and not

sends ads.

More physically active consumers will get targeted

differently than those less physically active.

And most importantly, Santa really will know if you’ve

been good or bad!

The Connected Me


39

Implications for National Brands in the

Connected Me World of Local Search

Connected Me SEO zones

Personal

Auto

Residential

Work

Time

Activity

Biometric Signals Create

New Intent Context

Physiological search

Moods

Body temp

Heart rate

Content marketing

Just right content

New UIs and form factors

Social

New types of native

advertising

Ecommerce

Impulse purchase ideas

based on activities

Rules-based

Privacy

Off grid times and zones

For National Brands – Local SEO will morph into Connected Me SEO and

Be Rules-Based Around Location, Activity, Biometrics, Permissions


40


Getting to the Always On,

Connected Me Campaign


41

Attribution – ultimate consumer data for closed loop

marketing.

Research – already into personal, wearable devices, just a few

steps away from survey samples to large scale personal data.

Testing – Move from A/B testing to machine learning at the

individual level, Connected Me supports granular optimization.

Social – Connected Me signaling can spawn organically created

affinity groups around brands

Loyalty – Super relevant and targeted loyalty programs fine-

tuned to the individual build deeper consumer relationships

and retention

The “Always On Aware Campaign” is bathed in

new signals and constant context refreshes.The Connected Me Enables the Always On, Aware Campaign


42

Context: Location and Intent Driven Search

Where am I?

GPS

Bluetooth beacons

WiFi

Cell towers

Time

Geofencing

Track

Street level

Store level

Augmented Reality

What am I doing?

Activity recognition

Activity View

What will I do next?

Predictive view

Where will I be next and

what will I want?

Where Am I and What Do I Want Next?


43

Explicit Search vs Context Driven Search

Current Local Searches

Business hours

Business directions

Business address

Is it in stock?

Connected Me Searches

You’re getting hungry,

nearby places you like to eat.

“Your heart rate is up, try a

decaf cappuccino at these

restaurants.”

“You’ve met today’s calorie

goal, time for a treat.”

“Too much sun exposure, $5

off sun screen at these

stores.”

“Join the 1,000 Steps a Day

Club and get these offers.”


44

Explicit

Key phrase

Implicit

Context

Conversational

Filters

Reviews

Connected Me

Integrates external and

internal signals

Contextual history creates

base cases

Self-learning and predictive

Individualized user experience

Final Thoughts on Search EvolutionBig Data, Connected Me signals, machine learning, predictive algorithms

and rules-based scenarios will take Local Search to a new level.

© 2014 BIA/Kelsey. All Rights Reserved. This published material is for internal client use only. It may not be duplicated or distributed in any manner not permitted by contract. Any unauthorized distribution could

result in termination of the client relationship, fines and other civil or criminal penalties under federal law. BIA/Kelsey disclaims all warranties regarding the accuracy of the

information herein and similarly disclaims any liability for direct, indirect or consequential damages that may result from the use or interpretation of this information.

Questions & Comments:

TheLocalMedia&Advertising Experts

Rick Ducey

Managing Director

BIA/Kelsey

[email protected]

@rducey

(703) 818-2425

mailto:[email protected]

rick ducey

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