A CASE FOR INVESTING IN

FULL FUNNEL DIGITAL MARKETINGAs the industry debates the merits of Upper Funnel tactics, their true

value can be found by looking at their influence across all KPIs.

July 2014

With today’s consumers having so much control over the messages delivered to

them, a greater understanding of the consumer journey is crucial for marketing

success. Brands must be able to reach their customers in ways that are relevant,

meaningful and add value to their day. Key to doing so is creating effective media

strategies that successfully engage consumers across the entire Marketing Funnel.

In the context of the Digital Media Marketing Funnel, increasing brand awareness

is the goal of Upper Funnel programs. For the context of this case study, we are

defining Upper Funnel campaigns as those with the objective of driving the right

audience to the brand’s site. Tactics that do so include Filtering and Prospecting.

Filtering uses demographic data, such as time-of-day, day-of-week, inventory

source, geography, browser type or ISP, to target audiences, whereas Prospecting

uses licensed third-party data to target a specific audience.

Lower Funnel programs seek to convert leads into opportunities. This is done

through a tactic called Remarketing. Remarketing uses first-party data to reach

consumers who have previously engaged with a brand.

Clients often judge an Upper Funnel tactic by the same Key Performance

Indicators (KPIs) as Lower Funnel tactics. At Audience On Demand® (AOD),

we believe that judgment is flawed, as each tactic along the funnel has its own

objective and should be judged accordingly. To demonstrate this, AOD proactively

researched and analyzed the effect of of Upper Funnel tactics on Lower Funnel

activity on a campaign-by-campaign basis. While this same analysis technique can

be applied more broadly than to just the display channel, in this case, AOD focused

on programmatic display.

Leveraging VivaKi’s big data solution, SkySkraper, AOD was able to access log-

level data and custom reporting from multiple DSPs for campaigns across various

verticals, as well as use external research findings.

+ As part of AOD’s regular practice, numerous campaigns across verticals and

KPIs were analyzed, and four were highlighted for this study.

+ Conversion rates, click-thru-rates (CTR) and Unique User (UU) volume were

used to compare users touched by Upper Funnel tactics and driven into

Remarketing (REM), versus those organically reached by REM.

WHAT We Wanted

to Achieve.

HOW We Did It.

The results of AOD’s research and analysis showed that Upper Funnel tactics had a

strong positive influence on Lower Funnel strategies. Campaigns that used a Full Funnel

approach yielded better results than those that used just the REM strategy alone,

regardless of KPI. In short, campaigns that used a Full Funnel approach drove more

conversions. Here’s how:

RESULTS

Users viewing Upper Funnel ads clicked through to tagged landing pages, feeding them

into the REM pool.

+ Higher click volumes on Upper Funnel ads resulted in more users being added into

the REM pool.

+ More users in the REM pool gave REM campaigns higher reach, leading to greater

opportunity for improved performance.

+ In one example, more than 10 percent of users who were shown an Upper Funnel ad

were driven to the REM pool.

Grow REM pool More clicks1

10%+ of Prospecting UU’s were driven into the REM

pool, adding over 3,500 people that can now be

targeted by Lower Funnel campaigns.

In another example, over 4% of UU’s who

were served Prospecting ads clicked and were

subsequently served REM ads as well.

3,659

35,916 UU’s in Prospecting

UU’s driven to Remarketing 19,362

479,622 UU’s in Prospecting

UU’s reached by Remarketing

Client A Client B

REM-only UU’s

Conversion rate

0.00375%

REM UU’s

Upper Funnel UU’s

Conversion rate

0.0613%

Purchase conversion rate was 64% higher when users were touched by both

Upper and Lower Funnel targeted impressions, rather than just REM alone.

Deltaof 64%

Users who clicked on Upper Funnel ads and were subsequently served REM ads were

more likely to convert.

+ Those who had previously interacted with an Upper Funnel ad comprised a more

relevant and tailored audience.

+ Remarketing to potential converters kept a product/incentive top-of-mind and may

have tipped an already susceptible user to convert.

+ Conversions by users driven through the funnel accounted for approximately 20

percent of total REM conversions.

Add more qualified users Higher conversion rate2

Client C

Running Upper and Lower Funnel tactics in tandem increased conversion volume via

incremental conversions.

+ Upper Funnel tactics captured new users, which continuously refreshed the REM pool.

+ Once these users converted, they were considered incremental, as they may not have

been remarketed to otherwise.

Garner incremental conversions Higher conversion volume3

Unique Users

UU’s reached by Remarketing

UU’s then converting in REM

3,861Total REM Conversions

3rd Party Data Filtering Private Deals

14,387,644

46,798

507(13%)

240,056,56

96,292

956 (25%)

111,495,841

148,173

1,196(31% of Total REM

Conversions)

Conversion rate was 80% to 110% higher when UU’s were touched

by Full Funnel tactics than when touch by only Remarketing.

Client D

CPC: An Alternative KPI

Sometimes, a lack of resources (log-level data, storage space, advanced analytics tools, etc.)

can limit the ability to track a user through the funnel. While Upper Funnel tactics cannot

always compete with REM tactics from a CPA perspective, they are still valuable for growing

the REM pool. In these instances, Cost Per Clicks (CPC) can serve as an alternative KPI for

Upper Funnel tactics, measuring the efficiency of driving users to the REM pool. Here’s how it works:

CLICKS

A click on an Upper

Funnel ad will drive to a

REM tagged page.

COOKIED USER

A user will be cookied when

they arrive on the landing page,

bucketing them into the REM pool.

RATIOS

Lower CPC’s mean that

users are being driven to

the remarketing pool more

efficiently.

CPC

Looking at CPC in the Upper

Funnel portion of the campaign

acts as a proxy for the cost of

adding users to the REM pool.

About AOD

Analytics

Priyanka Naik came to AOD with a background in management consulting. In her role as

analyst, she consistently applies her creative strategic and analytical insight to all of her

clients, which fall across a wide range of industry verticals. Priyanka has contributed to the

AOD Analytics Team by pioneering programs such as “Analyst of the Month” and a training

on “How to Present Data.” Outside of AOD, Priyanka’s passion is cooking, and she shares

recipes and reviews on her personal blog, chefpriyanka.com. Priyanka graduated with a

Bachelor of Arts in Economics from Boston University.

Priyanka Naik

Tim Slater

Nina Van Brunt

Tim Slater joined AOD as an Ad Ops Coordinator after graduating from Grand

Valley State University with a BBA in Marketing. After working on the Mediavest

business, he segued into working as an analyst on Starcom and other assorted

AOD business. During 2013, Tim assumed the role of Mobile Subject Matter Expert

for the Analytics team. Outside of the office, Tim pretends to know how to golf

and is a self-declared nerd.

Nina Van Brunt stepped into her Analyst role with full force, learning the digital space,

training pod members and leading her pod in client communication. She is the Video Channel

Subject Matter Expert, serving as the liaison between the AOD Video Team and the Analytics

Team, facilitating communication, education and optimal workflow between the two. She

also spearheaded the effort to integrate specific video DSP data into AOD’s proprietary

SkySkraper database. Nina graduated from Boston University with a BS in Film.

VivaKi’s AOD Analytics Team exists to not only evaluate

what they find in programmatic campaign data, but why. This dedicated team of expertly

trained analysts mines the wealth of data that’s been collected by VivaKi’s SkySkraper data

solution for all VivaKi clients across all digital channels to discover actionable insights about

audiences and inform optimization strategies. Their efforts result in the development of best

practices that advance the intelligence of AOD and, in turn, agencies and their clients.

About the Authors