This document discusses approaches to measuring the effectiveness of offline marketing campaigns. It summarizes different attribution methods like market lift analysis, brand awareness surveys, and promocode redemption rates, noting the strengths and weaknesses of each. It then describes a New York City subway advertising campaign by SeatGeek that demonstrated the utility of post-transaction surveys for attributing offline sales. By surveying new NYC customers on how they heard of SeatGeek and projecting the results, SeatGeek was able to estimate a higher return on ad spend from the subway campaign than implied by other metrics like promocode redemption.

1. Cracking The Code:
An Approach To Offline Marketing Attribution
Will Flaherty
VP, Growth Marketing | @flahertyiv

2. Discover events Pick a perfect seat Buy with two taps Enter with the app
SeatGeek is a mobile-centric ticket marketplace

3. Offline marketing offers immense promise…..
Tremendous scale combined with unique media
arbitrage opportunities
1
2
Offline provides an opportunity to reach
consumers who can’t be reached via digital
3
Offline mediums offer a broader canvas to
communicate USPs or tell a brand story

4. Channel Example: Direct Mail

5. …yet also presents numerous challenges, all tied
back to measurability
Offline media is difficult to track — and nearly impossible
to do so at the granularity offered on digital platforms
1
2
Additionally, offline media buys generally require larger
time and monetary commitments than online campaigns
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Poor campaign insights + long feedback loop + $$$ =
elevated risk of failure

6. There’s no “Silver Bullet” for offline attribution
We utilize many methods in concert with one another to measure and
gauge offline performance, as each have distinct strengths and weaknesses
We look at lift from offline advertising in markets we
advertise. However, this rarely provides a clean view
because of seasonality, team performance, and company
growth. This method is also ill-suited to measure the long-
term effects of offline marketing.
Market lift analysis2
We run brand awareness surveys (i.e. which of the
following ticketing companies are you familiar with?).
Results help us understand awareness driven by
geographically targeted offline campaigns, but they can
be expensive and can struggle to provide great
granularity into return on ad spend.
Brand awareness1
Unique promocodes can be used by customers at account
creation and checkout in order to convey an offer and also
collect highly granular data on campaign response.
However, many users neglect to enter their promo codes
or forget them, meaning that they frequently underreport
actual performance.
Promocodes3
Users are asked after making a purchase how they heard
about SeatGeek either via e-mail or modal on site or in
app, with follow up questions designed to collect more
granular attribution data. Not as granular as promocodes,
and ROAS calculations rely on user behavior assumptions
that may be hard to validate.
Post-transactional survey4

7. Promo code redemption
• A few of our creative units contained promocodes, but
redemption rates of the associated code were low,
implying only modest Return on Ad Spend (ROAS)
Our NYC subway campaigns illustrated the
limitations of many of these methods…
Overview
• The NYC subway has become an advertising
destination for many startups. The scale is enormous;
over six million people ride the subway daily.
• NYC Subway offers a unique opportunity to run
multiple creatives in a takeover of a single car
Brand awareness
• We saw an uptick in New York City aided brand awareness,
but our survey sample size was too small and our questions
too generic to attribute performance to the subway campaign
Market lift
• With many other marketing activities ongoing in New
York, It was difficult to identify any conclusive lift that
we could attribute to the Subway campaign

8. …but also underscored the immense utility of
a post-transaction survey
Post-transactional survey
• We launched a post-transaction survey in preparation
for the New York City subway campaign
• Every first-time NYC buyer received an email asking
where they heard about SeatGeek
• We began the test a week before the subway
campaign launched to measure how many users
incorrectly attributed the subway to their purchase.
Only 1% of people chose an invalid source
Subway results
• 24% of all new users responded to our post-
transactional email, with 20% crediting the subway
ads for how they heard about SeatGeek
• We then projected ROAS based on survey results,
with the resulting estimated return much higher than
implied by promocode redemptions
Pre-Subway
Post-Subway
25% 50% 75% 100%
TV Online Radio / Podcast Friend Mail Subway
20%
1%
Survey Results Before and After Campaign Launch

9. ROAS Calculation Methodology
Deep Dive: How we use post-transactional
surveys to calculate subway return
3 Calculate ROAS using scaled sales
After calculating the scaled up revenue, we divided that figure by the cost of subway media
to yield our final ROAS estimate
Determine scale-up factor
Just under 25% of all new NYC purchasers responded to the emailed survey. So we applied
a scale up factor of 4.21 to survey-attributable subway sales to estimate those numbers for all
new NYC purchasers.
2
ID survey-attributable subway sales
We first identified the user IDs of all new users who attributed Subway as how they heard
about SeatGeek, and then pulled all purchases made by those users during the period
1

10. Best practices for post-transactional surveys
Administer survey soon after a “key event” occurs in
your service’s user experience1
Design survey to make data input of the key channel-
level questions as seamless as possible2
Ensure that you can tie survey results to trackable
actions or other metadata (e.g., location) to allow for
deeper analysis later down the line
3
Attribution survey in
DoorDash Mobile App
Be aware of scale-up assumptions — unlikely that all your
users behave exactly as the pool of surveyed users do4
Optimize for high response rates to minimize margin of
error in analysis when scaling up results5

11. Thanks!
will@seatgeek.com
@flahertyiv