This document argues that investing in a full digital marketing funnel, including upper and lower funnel tactics, yields better results than using just lower funnel tactics alone. It summarizes an analysis of campaign data from multiple DSPs that showed upper funnel tactics like prospecting positively influenced lower funnel strategies like remarketing by driving more users and clicks into the remarketing pool, increasing reach and conversion rates. Specifically, campaigns using a full funnel approach saw 64-110% higher conversion rates than remarketing alone. The document concludes that combining upper and lower funnel tactics increases conversion volumes through incremental conversions.

1. A CASE FOR INVESTING IN
FULL FUNNEL
DIGITAL MARKETING
As 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

2. 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.

3. 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

4. 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.
Delta
of 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

5. 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
3,861
Total 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

6. 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.

7. 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