Fallon Worldwide “Brainfood” POV

“17 Things You May Not Know About Online Advertising (And 1 Thing You Probably Do)”

January 25, 2011

I’m here today to talk about analytics in the context of creative digital advertising

•   Creative agencies (like mine) are founded on the concept of “creative leverage”—that big ideas can work harder than big budgets.

•   Analytics as a discipline has been driven by the explosion of data available online.

•   To succeed in digital, good ideas are not good enough – they need to be supported, informed and changed by numbers.

Today I’m going to present 17 surprising facts about online advertising culled from recent studies and client work – starting with one thing you probably know . . .

Online advertising (OLA) (n.) – “a thing that seems to be getting less effective and more expensive”

$25B

$20

$15

$10

$5

US Online Ad Spend

($)

0 2000 2002 2004 2006 2008 2010

0.50%

0.40

0.30

0.20

0.10

Avg. OLA CTR (%)

0

Source: Fallon analysis; Google Benchmarks; Forrester

#1. Digital spend is still too low.

•   This is the first of the “17 Things You May Not Know About Online Advertising” . . .

Internet media budgets do not reflect how consumers actually spend their time.

Source: Dynamic Logic MarketNorms, 2008, Fixed frequency level of 1. Campaigns using online display advertising of any format.

Display ads really do impact brand metrics.

Brand Impact of Online Display (Control v. Exposed)

#2. 80% of clicks are done by 20% of people.

CLICKERS

Online clickers follow the 80/20 (Pareto) rule.

“Despite only accounting for 6% of the total Internet population, heavy clickers accounted for 50% of clicks in the month.” ComScore

Source: comScore Inc., custom analysis, total US online population, XPC Persons Panel, July 2007 data period Note: “Heavy” clickers defined as 4+ clicks on online advertising per month; “Moderate” = 2-3 clicks; “Light” = <1 click per month

#3. Clickers are probably NOT your best customers.

“Natural Born Clickers”

•   Age: 25-44

•   Lower income: $20-40K

•   2x more spend online

•   Heavy Internet use:

  5X higher time on site

  8X more pages per visitor vs. online pop

•   Non-clickers visit: portals, search, news, finance

•   Heavy clickers visit: gambling, job searching, games … and porn*

* Just a guess

Source: comScore Inc., custom analysis, total US online population, XPC Persons Panel, July 2007 data period Note: “Heavy” clickers defined as 4+ clicks on online advertising per month; “Moderate” = 2-3 clicks; “Light” = <1 click per month

Clickers Are Generally Less Credit Worthy.

•   Financial services client case study

•   Users who were exposed but did NOT click were approved 180% more often than users who clicked

•   “Casino” mentality

•   More leisure time = More time to click

Source: Publicis financial services client case study (2007-2008)

Clicked Control

Approval Rates

179% Lift

Exposed

Financial Services Client View-Through Study

#4. Your best customers may be invisible.

The Cookie Deletion Dilemma: Overstated Reach but Understated Frequency.

Based on a comScore study of Yahoo and DoubleClick cookies:

•   30% of Internet users delete their cookies in a month

•   These deleters do so an average of 4x per month

•   True for 1st party (e.g., NYT sign-in) and 3rd party (e.g., ad server) cookies

  Up to 2.5x overstatement of “unique visitors”

  Understatement of campaign ROI

 Worse for higher-end and technology brands

#5. 80% of OLA’s effectiveness has nothing to do with the CLICK.

It’s been conclusively shown across many industries that banners impact people who don’t click—like TV.

0.0000% 0.0020% 0.0040% 0.0060% 0.0080% 0.0100% 0.0120% 0.0140% 0.0160% 0.0180% 0.0200%

5 10 15 20 25 30 35 40 45 50 55 60 Length in Days of Advertising Effect

Con

vers

ion

Prob

abili

ty (H

azar

d)

Red Baseline = conversion probability for days 15 - 60

Days 0 - 5: 341% lift over baseline

Days 5 - 10: 124% lift over baseline Days 10 - 15: 94% lift over baseline

0.0000% 0.0020% 0.0040% 0.0060% 0.0080% 0.0100% 0.0120% 0.0140% 0.0160% 0.0180% 0.0200%

5 10 15 20 25 30 35 40 45 50 55 60 Length in Days of Advertising Effect

Con

vers

ion

Prob

abili

ty (H

azar

d)

Red Baseline = conversion probability for days 15 - 60

Days 0 - 5: 341% lift over baseline

Days 5 - 10: 124% lift over baseline Days 10 - 15: 94% lift over baseline

Length in Days of Advertising Effect

Con

vers

ion

Prob

abili

ty (H

azar

d)

Red Baseline = conversion probability for days 15 - 60

Days 0 - 5: 341% lift over baseline

Days 5 - 10: 124% lift over baseline Days 10 - 15: 94% lift over baseline

Client Example: Latency Window

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

Ad Exposed Control

VT Non - Incremental

VT Incremental 15.7% Lift*

Click - Based

Net

Yie

ld b

y U

niqu

e U

ser

Conversions Acquired

0.00%

0.02%

0.04%

0.06%

0.08%

0.10%

0.12%

0.14%

VT Non - Incremental

VT Incremental 15.7% Lift*

Click - Based

Net

Yie

ld b

y U

niqu

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ser

Conversions Acquired Client Example: VT* Incrementality

* VT = View-through, defined as post-impression activity observed among users who were exposed to a display ad but did not click

#6. Most of a banner’s effect is probably on search.

Effect of Display Ads on Search by Industry.

Source: comScore, “How Online Advertising Works: Whither the Click?” Jan. 2009, presentation for ARF [meta-study of 200]; Specific Media study of 12 months. * Publicis client case study (2008-09)

Observed Lift for Seachers Exposed to Banner Ads vs. Control

+206%

+144%

+125%

+69%

#7. Same with TV.

Source: Omniture Inc (The Omniture Summit 2009, p8); case study client name suppressed

Search Reacts to Television Advertising.

TV GRPs vs. Search Clicks for National Brand

#8. Never do display without search.

Paid Search + Display Works Better Than Either Channel Alone.

Incremental Impact on Offline Sales per (’000) Exposed

Source: comScore, “How Online Advertising Works: Whither the Click?” Jan. 2009, presentation for ARF

Search & Display

Search Only

Display Only

#9. Impact is largely determined by your industry.

Display Ads’ Impact on Site Visitation by Industry.

Advertiser Site Reach

(Weeks 1-4 After First Exposure)

Source: comScore, “How Online Advertising Works: Whither the Click?” Jan. 2009, presentation for ARF

#10. Rich media may not work the way you think it does.

Rich Media can work for aided awareness, but it may be distracting/confusing the brand’s message.

Rich Media with Video has the MOST Impact on Aided Brand Awareness…

…But is significantly LESS Effective at Impacting Message Association

Source: Dynamic Logic MarketNorms Study (2008)

#11. Banners are often less important than LANDING PAGES.

Most people who click don’t make it to the landing page.

Drivers of Drop-off:

•   Cookie rejection •   Long load times •   Natural defection

(user clicks stop, back, or close window)

•   Connectivity issues •   Improper tagging

Source: DFA reporting Jan. 2009; Fallon analysis

Banner Click-to-Quote Start Traffic for Insurance Advertiser

(Click to Quote Start Traffic) 376,426

(263,882)

(111,886)

658

-70.1%

-29.7%

(-99.4% of LP traffic)

Landing Pages Matter: One of these options drove a 20-25% better response rate than the others.

• Driven to the application

• Result: Performed the worst among all variations

Landing Pages Tested

• Driven to a product-specific detail page

• Result: Performed the best

• Significantly higher (double-digit) response rate

• Driven to less detail around more card products

• Result: Depressed responses more than 20% vs. single-product page

Source: Confidential client analysis

#12. Landing pages need to MIRROR your creative.

Landing Pages must register as “not a mistake” <1 second after loading, or the user will bounce.

Visual Consistency

Contextual Consistency

Keyword: iPod

Keyword: MP3 Player

• Further down the funnel

• Transactional key word • Driven to the iPod mall

• Higher up in the funnel – less transactional

• Key words are made visual

• Messaging expands & adds brand and info elements

•  Identical visual element is the link

#13. If you want good response, customize your landing page.

Different Targets = Different Landing Pages.

Florida drivers

Interactive Cross-sell Tabs (Car, Home, Boat)

Texas drivers

“Welcome to your new life” – Movers

Savings Message – Students

Discount for Military

Alumni “could save even more” Find an Agent

OR get a quote online

“Early Bird Special” – Seniors

“Review Your Quote” – Banner for

quote abandoners

  Examples of Landing Pages with images and content tied to a customer group

#14. Load times trump everything.

Longer load times may be the single biggest driver of online response rates

* Total responses (#) / Total impressions from online media (paid search and display). Does not include conversion rate or quality.

Total Waiting-to-Load Time (Click to Quote Start – Paid Search Only, seconds)

Response Rate Index*

10

15

20

30

15 10 5 0 20

0

Response Rates vs. Load Times

#15. The only way to measure true impact is to set up a test in advance.

Use cookie-level log files (from ad server) to differentiate between conversions that would have occurred naturally, versus those influenced by the online media.

Appropriate latency window and attribution percentage is decided.

Web Audience

Test Group- Views Ad

Control Group- Views PSA (not Ad) - Runs on same sites/placements

View (no click)

Click

View (no click)

Responses and

Conversions

Brand Banner

Post-View tests can be set up relatively easily through an ad server like DoubleClick.

#16. If you fail to plan campaign measurement—plan to fail.

Best in class digital players start their measurement process well before assets are built.

#17. Creative can be less important than other factors in digital.

OLA and Paid Search often function more like Direct Mail than above-the-line advertising (e.g., TV).

Value of Offer 40%

Targeting 40%

Creative 20% Targeting & List Selection

Carefully select and cultivate customer and prospect lists

Value of Offer The ideal DM offer: -   Fulfills a perceived need -   Conveys strong perceived value (compared to competitors) -   Is unique -   Is practical -   Has a clear connection with brand

Creative Elements -   Hooks to provoke immediate response (sample, etc.) -   Bullets, lists, dashes to catch skimmers -   Headline / “Johnson Box” above letter salutation outlining key benefit -   Clear call-to-action to drive response

Source: CRM Trends; confidential DM client study (2008)

Impact of Different Elements on Prospect Response to DM

Bonus #18. But great creative + great product always wins . . .

Thanks.

martin.kihn@fallon.com office: 612.758.2748