Increasing brand awareness is no longer an acceptable goal. We need to know how our digital dollars are moving our customers to action. Franchisees want to know exactly where their advertising dollars are being spent and what they stand to gain from their investment. Franchisors need to get their community’s buy-in and show results- quickly! Recently A&W Restaurants evolved its thinking about how to measure and report on digital campaigns – the cost of driving a visit to its franchisee’s reataurants.

1. A&W Tracks Cost Per Visit

2. Agenda
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• A Brief History of A&W and Digital Media
• 2017 Media Recap
• 2018 Media Plans
• Strategy
• Tactics
• Targeting
• Sell-in

3. A Brief History of A&W and Digital Media
• A&W Restaurants is the nation’s oldest franchised restaurant chain,
founded in 1919.
• A&W first developed a national digital strategy in 2014- online
advertising up to that point had been fragmented and inconsistent.
• Prior to 2017 goals were based largely on measuring impressions,
social fan growth & online video views.
• Last year was the first time our thinking shifted towards driving
measurable in-store traffic as our #1 goal.
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4. Ongoing Challenges
• Unable to read real-time sales data.
• Data lags and is almost entirely self-reported.
• Limited funds- typically our concentrated online media flights are only 4-6 weeks.
• Limited ability to apply learnings- usually have to wait 12 months before learnings
are applied.
• Fragmented asset types in our system- menu offerings and promotional
messaging varies:
• A&Ws
• A&W/ Long John Silver Co-brands
• A&W/ KFC Co-brands
• A&W Burgers Chicken Floats concept
• Geographic location of our restaurants- many are in very small towns; we still
have restaurants that are seasonal.
• Franchise Community deeply attached to traditional media outlets.
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5. 2017 Digital Media Overview
• We ran the bulk of our Digital Media during the Summer Sales Event to support our
peak season.
• For the first time we promoted HBC Tenders on a national level for our Base Brands &
LAWs!
• KAW ads focused on our new Peanut Butter Treats.
• Placement for all asset types included:
• Facebook promoted content
• Instagram promoted content
• Promoted Tweets
• Display ads (using device ID targeting)
• Hulu online TV
• The Weather Channel mobile app
• YouTube pre-roll
• Mug Club emails
• Brand Ambassador involvement
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6. 2017 Digital Tactics
• We concentrated on two main tactics this summer in our media
placement:
• Awareness tactics focused on mediums that allowed for high-impact
placements such as video and rich media, which also generated
significant reach within our target demo.
• Engagement tactics focused on driving traffic to our website and in-
store visits by conquesting audiences who frequent our competition.
• Both of these tactics worked together to bring attention to our summer
promotions while creating a desire to visit a restaurant to purchase.
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Spend by PlatformCompetitors Targeted

7. 2017 Digital Media Results vs. 2016
Results
• Traffic to the location pages on AWRestaurants.com was up 39% (221,113
vs. 158,653).
• The PB Treat ads clicked through to the user’s closest location.
• Traffic from mobile users increased by 88%.
• The Mt. Dew campaign included a one-click mobile sharing feature,
which was designed specifically with our mobile audience in mind.
• The HBC & PB Treat display ads were placed only on mobile platforms.
• On average site visitors spent 73% more time on the website (57 seconds vs.
33 seconds).
• The HBC landing page was designed to encourage users to interact
by swiping through our sauce selection & selecting their favorite
dipping sauce.
• We gained 4,540 new social fans, 26,390 new Mug Club members & added
8 new Brand Ambassadors to our roster!
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8. Summer Digital Results: Key Takeaways
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24M Impressions
14.1%↑ in
Favorability
50K Incremental Store
Visits
2.7M
Video
Views
• Receiving over 24M impressions & 2.7M
video views during the summer
promotion, we focused on hitting our
audience across multiple touchpoints
to grow awareness of our HBC & PBT
offers & drive in-store visits.
• We saw a 14.1% positive lift in users’
likelihood to favor A&W after being
exposed to our ad on The Weather
Channel.
• Using device ID targeting we were able
to attribute over 50K incremental store
visits to audiences exposed to our
mobile ads.

9. Awareness Tactics vs. Engagement
Tactics
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• We concentrated on two main tactics this summer in our media
placement:
• Awareness tactics focused on mediums that allowed for high-
impact placements such as video and rich media, which also
generated significant reach within our target demo.
• Engagement tactics focused on driving traffic to our website and
in-store visits by conquesting audiences who frequent our
competition.
Awareness Engagement

10. Three Forms of Audience Targeting
• Behavioral Targeting: based on
user’s interests & current proximity
to an A&W.
• Retargeting: users who have
previously been to an A&W & are
in current proximity to a restaurant.
• Custom Audience Targeting:
specific groups of users that
develop over a campaign cycle
based on response to A&W ads/
behavior changes.
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Behavioral
Retargeting
Custom
Audience

11. Behavioral Audience Targeting
• Behavioral Targeting:
• Casual diners within 10 mi of
restaurant
• Fast food enthusiasts within 10
mi of restaurant
• Families traveling for summer
within 10 mi of restaurant
• Ice cream/ candy enthusiasts
within 10 mi of restaurant
• Deal seekers within 10 mi of
restaurant
• Entertainment enthusiasts
within 10 mi of restaurant
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Behavioral
Retargeting
Custom
Audience

12. Audience Retargeting
• Audience Retargeting:
• Visited an A&W previously
and are within 5 mi of a
restaurant.
• Visited an A&W since 5/29,
but not in the past 3 days and
currently within 5 mi of a
restaurant.
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Behavioral
Retargeting
Custom
Audience

13. Custom Audience Targeting
• Custom Audience Targeting:
• Users within 10 mi radius of an
A&W.
• Seen at any A&W in the past 6
months but not in the past 2
months.
• Seen at any A&W in the past 12
months but not in the past 6
months.
• Seen at any A&W at most once
a month in the last 12 months.
• Seen at any Chick-Fil-A, KFC,
Church’s, Wendy’s or Dairy
Queen and within 15 mi of an
A&W.
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Behavioral
Retargeting
Custom
Audience

14. Key Insights from Audience Targeting
• The Custom Audience drove the highest incremental lift compared to the
other audiences targeted.
• DIY Enthusiasts, Fast Food Diners & Big Box Shoppers were among the top
exposed visitor profiles.
• 62% of A&W consumers targeted live within 10 mi of the location they
visited, and over 45% of them live within 5 mi of an A&W.
• KFC, Dairy Queen & Chick-Fil-A were the competitors where exposed
visitors were seen most frequently.
• By using data gathered both prior to the campaign & during the campaign
& applying predictive methodologies, we are able to attribute 50,705
incremental visits to A&W locations, resulting in a $1.91 cost per
incremental visit.
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15. Determining Incremental Lift
• Incremental Lift: percentage of visits to a location that are
attributable to advertising.
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User is exposed to
an ad
User visits an
A&W
Data is collected & run
through behavioral &
predictive
methodology to
determine incremental
lift

16. Methodology for Determining
Restaurant Visits
1. Understand the baseline A&W visit patterns.
• Measure against months of location data for devices while ad
campaign is not running.
• Account for seasonality in location visits.
2. Identify an identical control group.
• Control group is built AFTER the campaign has finished and is NOT
exposed to the ad.
• Both groups are monitored for increased A&W visits above their
natural visit frequency.
• A&W visit change is measured for both groups.
3. Accurately measure incremental lift based on actual A&W visits for both
control & exposed audience groups.
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17. Methodology for Determining
Incremental Visits
• We are also serving ads to consumers that we are not tracking within a
DMA (other mobile ads, video ads, social ads, etc.)
• Incremental restaurant visits are determined using DMA census population
data correlated against tracked A&W visitors.
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Full DMA
population
Devices
tracked in
DMA
Multiplier
(x)
Total
projected
restaurant
visits
Exposed
devices seen
in an A&W
Multiplier
(x)
Measure ratio between device
coverage & DMA population size
Apply same ratio to exposed devices seen
in an A&W to project total restaurant visits
for a DMA

18. Device ID Campaign: Overall
Delivery
• Impressions: 14,756,248
• Exposed unique users: 1,356,125
• Number of unique users used to calculate incremental lift: 186,974
• Total exposed visits: 101,592
• Incremental visits: 50,705
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19. Determining Cost per Incremental
Visit
• By using data gathered both prior to the campaign & during the
campaign & applying predictive methodologies, we are able to attribute
50,705 incremental visits to A&W locations, resulting in $1.91 cost per
incremental visit.
$𝑋𝑋, 𝑋𝑋𝑋
50,705 𝑖𝑛𝑐𝑟𝑒𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑖𝑠𝑖𝑡𝑠
= $1.91 𝑐𝑜𝑠𝑡 𝑝𝑒𝑟 𝑖𝑛𝑐𝑟𝑒𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑖𝑠𝑖𝑡
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20. Determining ROI for Incremental
Visits
$𝑋𝑋, 𝑋𝑋𝑋
50,705 𝑖𝑛𝑐𝑟𝑒𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑖𝑠𝑖𝑡𝑠
= $1.91 𝑐𝑜𝑠𝑡 𝑝𝑒𝑟 𝑖𝑛𝑐𝑟𝑒𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑖𝑠𝑖𝑡
Assumptions:
• $8.00 check average
• $1.35 F&P cost (using 3 pc HBC only)
• No labor cost factored in
$8.00 − $1.91 − $1.35 ∗ 50,705 𝑖𝑛𝑐𝑟𝑒𝑚𝑒𝑛𝑡𝑎𝑙 𝑣𝑖𝑠𝑖𝑡𝑠 = 2.5𝑥 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡
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21. Positive Correlation Between
Incremental Visits and Period Sales
• We separated restaurants by
number of device IDs tracked
in buckets of 50.
• All 29 AW restaurants with
more than 50 ID tracked had
increases in sales of period 6
vs the average YoY% sales for
Periods 3, 4, 5, 7, 8 and 9.
• With Cobrand locations we
are unable to determine
whether visitors were
purchasing A&W products or
purchasing from the
Cobrand side of the menu.
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Restaurant
Count VisitCount
YoY% P3, P4,
P5, P7, P8 &
P9
Promo
P6 YoY % Difference
No 43 1.1% -2.7% -3.8%
AW 20 2.9% -2.2% -5.1%
KA 8 -4.0% -13.8% -9.8%
LA 15 -13.6% -0.6% 13.0%
Yes 612 20908 -0.5% -0.4% 0.0%
AW 238 7754 0.4% 0.6% 0.2%
1-50 206 4839 0.5% 0.2% -0.3%
51-100 27 1849 -1.0% 1.5% 2.5%
101-150 2 238 4.5% 5.9% 1.4%
201-250 1 223 -5.3% -0.1% 5.2%
251-300 1 251 7.3% 14.2% 6.9%
351-400 1 354 6.1% 33.9% 27.8%
KA 196 7000 -1.1% -1.8% -0.7%
1-50 160 4257 -1.2% -1.4% -0.3%
51-100 31 2020 -0.8% -3.6% -2.8%
101-150 3 344 5.6% 2.2% -3.4%
151-200 1 158 -14.9% -16.5% -1.6%
201-250 1 221 -13.3% -11.2% 2.1%
LA 178 6154 -4.2% -4.8% -0.6%
1-50 138 3283 -4.5% -5.3% -0.8%
51-100 36 2392 -3.5% -4.0% -0.5%
101-150 4 479 2.1% 7.0% 4.9%

22. 2018 Digital Media Strategy
• Primary Goals:
o Utilize mix of digital placements to drive measurable foot traffic to Base
Brand A&Ws.
o Use visit data from 2017 to make ad investment more equitable
between restaurants.
o Help increase Same Store Sales!
• Secondary Goals:
o Increase A&W’s brand awareness in key zip codes (within 5 mile radius
of restaurant).
o Increase A&W’s social media following.
o Increase traffic to AWRestaurants.com.
o Increase Mug Club membership.
o Increase reach of Sales Event TV Spots.
o Outline local digital media as a “plus up” option.
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23. Changes in Strategy for 2018
• We are segmenting our restaurant list to differentiate between asset types
(urban, rural, off-highway/ commuter).
• We will use restaurant visit data from last year to determine which
restaurants had positive ROI & which restaurants did not.
• We will divide our campaign into two flights to ensure that we make the ad
coverage as fair as possible between all restaurants.
• We will use different creative messages & different CTAs to determine what
drives the most foot traffic for the lowest cost.
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24. Changes for 2018: Base Brand
Segments
• We know that our Base Brand restaurants vary widely in terms of location and
demographics, so we’ve segmented them into three “buckets”.
• This will allow more campaign customization in several areas:
• Our creative will feature specific CTAs based on segmentation, ex. “Get
one for the road!” or “Stop in for dinner!”
• The ad model will learn to optimize towards different audiences as the
campaign progresses & target more effectively in each segment.
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Base
Brands
Urban/
metro
Small
town/ rural
Transient/
commuter
Urban/ metro: towns with
populations >50,000 or on
outskirts of larger DMAs.
Small town/ rural: towns with
populations <50,000 or in remote
locations.
Transient/ commuter: restaurants
off interstate exits or on busy
state roads.

25. Changes for 2018: Using Data to
Determine “Breakeven” Point
• Using data from last year’s campaign we were able to further segment our
Base Brand restaurants into tiers within their segmented category.
• We used the cost of the campaign & the profit made on incremental visits
to determine how many visits each restaurant needed to breakeven on
their ad investment.
Assumptions:
• $8 check avg
• $1.91 CPIV
• $6.09 “profit” (does not include F&P or labor)
2017 “Breakeven” Equation:
• $𝑋𝑋, 𝑋𝑋𝑋 ÷ 630 𝑟𝑒𝑠𝑡𝑎𝑢𝑟𝑎𝑛𝑡𝑠 = $XXX/ restaurant (investment per restaurant)
• $𝑋𝑋𝑋 ÷ $6.09 = 25.3 𝑣𝑖𝑠𝑖𝑡𝑠 (26 visits needed to breakeven)
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26. 2018 Breakeven Equation
Assumptions:
• 2018 ad spend: $XXX,XXX
• Restaurants participating: 242
• Check avg: $8
• Est. CPIV: $2.25
• “Profit” per visit: $5.75 (does not include F&P or labor)
• $𝑋𝑋𝑋, 𝑋𝑋𝑋 ÷ 242 𝑟𝑒𝑠𝑡𝑎𝑢𝑟𝑎𝑛𝑡𝑠 = $𝑋𝑋𝑋 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡 𝑝𝑒𝑟 𝑟𝑒𝑠𝑡𝑎𝑢𝑟𝑎𝑛𝑡
• $𝑋𝑋𝑋 ÷ $5.75 = 115 𝑣𝑖𝑠𝑖𝑡𝑠 𝑛𝑒𝑒𝑑𝑒𝑑 𝑡𝑜 𝑏𝑟𝑒𝑎𝑘𝑒𝑣𝑒𝑛
• Campaign length: 5 weeks
• 115 𝑣𝑖𝑠𝑖𝑡𝑠 ÷ 5 𝑤𝑒𝑒𝑘𝑠 = 23 𝑣𝑖𝑠𝑖𝑡𝑠 𝑝𝑒𝑟 𝑤𝑒𝑒𝑘
Each restaurant needs to average 23 visits per week to break even.
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27. 2018 Digital Media Tactics
• Based on last year’s promising results we are putting the bulk of our online
media spend towards device ID targeting.
• While this technology allows us to track actual restaurant visits that we can
measure against sales, we know that this type of advertising will likely not
work for every one of our restaurants.
• To ensure that each Base Brand restaurant is getting ad coverage for their
investment we have developed a backup plan this year.
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May:
Platform: device ID
(smartphones)
Messaging: Diner
Burger & $1.99 Floats
Funding: 80% of media
spend
Targeting: Base Brand
restaurant segments
(242 stores)
June:
Pause! Determine which
restaurants did not get
enough visits to
breakeven. Analyze
audience data ,
messaging & CTA
learnings to launch
second campaign for
underperforming stores.
July:
Platform: TBD
Messaging: TBD
Funding: 20% of media
spend
Targeting: restaurants
that underperformed
during May campaign

28. 2018 Digital Content Strategy
• We will start with 2 messages: Extra Cheddar Diner Burger branding & $1.99
Floats.
• As the campaign progresses, the ad model will learn which message is driving
more traffic & will optimize towards the winning product.
• Once the higher-performing product has been determined we will then be
able to test different CTAs based on our restaurant segmentation to see which
ones are most effective.
• Ex. Make a pit stop, get one for the road, try it while you can
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29. 2018 Creative Examples
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30. 30
Pros & Cons of Device ID
Methodology

31. 31
Pros 2017 2018
Restaurants divided into segments √
Campaign optimized towards best results within segment √
Campaign optimized towards best results across all restaurants resulting in low CPV √
Weekly reports/ end of campaign report in timely manner √
End of campaign audience insights reported by segment √
End of campaign visitation report by restaurant √ √
Can use prior data to optimize campaign from the beginning √
Cons
Campaign optimized across all restaurants, causing a handful or restaurants to receive a bulk of the
visits
√
Could not see CPV until post-campaign report √
No weekly reports & end of campaign report was delayed √
Had to wait a year to apply any campaign learnings √
No guarantee of all restaurants receiving impressions and/ or visits √ √
Cannot receive reporting on a per restaurant level until post-campaign report √ √
Do not know ticket amount of guest visit & have to use check average for ROI √ √

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Set-Up Parameters 2017 2018
Budgets set only by targeting type (behavioral, retargeting, location-based) √
Budgets set by segment based on estimated ad inventory level available in each √
All types of creative assets can be used (video/ display/ interactive media) √ √
Targeting/ Pricing
Unique audiences built for each promotion (S&T and protein) √ √
Unique audiences build for each segment √
Interactive media included as added value √
In-flight Campaign Optimizations
Ability to optimize by message (S&T or protein) √ √
Ability to optimize by creative asset √ √
Ability to optimize by audience √ √
Ability to optimize by segment √
Ability to optimize by CPV √
Can move budgets across segments as needed √

33. The Sell-In: Make Your Team Do “Mini
Media Audits”
• Digital advertising is constantly evolving as new technologies & new
targeting capabilities emerge.
• Widespread use of smart phones, web searches, social media, smart TVs &
voice assistants has made IoT seamlessly integrate into our everyday lives.
• Smart brands are taking advantage of this connectivity & using today’s
tech to reach their audience with the right message at the right time on
the right platform.
• Questions for the room:
• How does IoT affect you in your everyday life?
• What ads do you see & how do they relate to you?
• Have your purchasing habits been influenced?
• Has your brand affinity changed?
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34. A Day in the Life of…
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35. 35

36. 36

37. 37

38. 38

39. Discussion
What ads have you seen online, on your phone or
on your smart TV?
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