14th International Joint Conference on Computer Science and Software Engineering Keynote: With over 50 million active customers, Groupon is one of the largest e-commerce sites in the world. Now offering over 500,000 deals daily, it has grown into a large marketplace aiming to connect customers to local deals through a variety of marketing channels. In order to achieve this, Groupon has had to develop sophisticated web based marketing processes.This talk will discuss the concept of Computational Marketing. Computational marketing is an emerging scientific discipline. It's central challenge is to find the best match between a given user in a given context and a suitable advertisement in order to provide advertisements that are contextually relevant and likely to lead to a purchase. With hundreds of thousands of events being generated per second, in the form of clicks, purchases, page impressions, etc. on all Groupon properties worldwide, being able to process these in real time in order to develop some instantaneous insights can provide a significant leg up over the competition.

1. Computational Marketing at Groupon
Clovis Chapman, PhD
email: cchapman@groupon.com
Research opportunities and challenges

2. About Me
University College London, London, UK:
Grid Computing
Dell Cloud Research & Development Center,
Dublin, IE:
Cloud Computing
Groupon, Seattle, USA:
Big Data and Computational Marketing

3. About Groupon
Founded November 2008. One deal per day in
Chicago.
Every day, a special deal for a business near you
is sent by email as a coupon.
Collective buying: If enough coupons were
bought, the deal would become active, hence:
“GROUPon”

4. Explosive Growth
2009 2013
40 K Active
customers
41.7 M Active
customers
Spread to over 40 countries, over 200 million
customers, and 40 million active customers.

5. Today
“eCommerce Marketplace”: 200,000+ businesses, connecting tens of millions of customers on multiple sites across the world.
Top 5 eCommerce brand in 2016 and top 25 mobile app by unique users in the US.
Businesses include restaurants, health and beauty services, activity parks, etc. Groupon also provides goods (electronics, groceries, etc.)
and travel deals.

6. How it works (local)
Deal Centric: Groupon will promote “deals” that
are typically near you.
E.g. “20 minute Seattle Plane Ride” at a discount
Bring voucher to merchant (using mobile phone)
Groupon specific considerations:
• Location Targeting: our deals are mostly
location specific
• Time Bound: New deals are up every day, only
for a limited time
• Variety: wide range of different type of
experiences, and merchants (beauty, things to
do, etc.)

7. PUSHPULL
Over 200 Million customers internationally.
Emails sent once or multiple time daily.
Personalised and geolocated emails.
Email
Take deals to the customer
Search Engine Optimization
Search Engine Marketing ($)
Display Advertising ($)
Affiliate Marketing ($)
Invite the customer to you.
Present deals where she is looking.
Marketing Channels

8. Talk Overview
Computational Marketing at Groupon
● What is Computational Marketing?
● Campaign Management
● Marketing Channel Attribution
● Bidding
● In Summary

9. Find the “best match” between a given user in a given context and a
suitable advertisement
Broder, A. Z.

10. AdvertiserAdvertising platform
Advertising Creative Landing Page
Advertising context Advertiser domain
Redirected
Campaign setup:
Creative, match criteria, bids
Clicks
1
2 3
User

11. Advertising
Creative
Keywords
Search Engine marketing
Bid
dependent
placement

12. Facebook Advertising

13. Display Advertising

14. Display Advertising: context is everything!
/

15. Marketing Optimization loop
Publish / Update
Campaigns (on Google,
Bing, Facebook).
• Several advertising platforms (Google,
Facebook, Bing, etc.)
• Hundreds of thousands of deals
worldwide changing frequently
• Fully automated optimization loop
Analysis
Monitor
Performance
(attribution)
Select Deals
/ Content
/ Assets
Define Match criteria
(Keywords / Audience /
location / time etc.)
Compute Bids
(Max cost per click)

16. Talk Overview
Computational Marketing at Groupon
● What is Computational Marketing?
● Campaign Management
● Marketing Channel Attribution
● Bidding
● In Summary

17. Campaign Management
4 Core elements of an SEM ad campaign:
● Keywords to target
● Creative
● Landing Page
● Bid
Other matching criteria important for Groupon:
● Location targeting
Campaigns are created / refreshed multiple times daily
for every deal.
Automatic Keyword & Creative Generation.
Use of Adwords API to push updates.
Keywords
Advertising
Creative
Search Engine Marketing
Landing Page
Click

18. Campaign Management
Keyword Examples
"massage groupon"
"massage & wellness spa"
"massage acupuncture"
"massage addiction"
"massage advertisement"
"massage albuquerque"
"massage and bodywork"
"massage and facial"
"massage and pedicure"
"massage and manicure"
"massage and spa"
…
“message spa"
"message spas”
“masge”
“massahe”
We advertise ~14 000 + massage related keywords alone in the
U.S.
200 Million+ Keywords worldwide to manage
Keywords advertised across multiple locations / Campaigns
Billions of bid & performance records to manage:
• How much did we bid
• How many impressions per day
• How many clicks per day
• How many purchases per day
• Etc.
Keywords can be obtained from a variety of sources including deal
and page meta-data:
• Category
• Merchant details
• Template based generation

19. Campaign Management
Keyword generation challenges
Must be selective in our use of keywords
Example:
• “Pizza”
• Unclear intent (Delivery? Recipe? …)
• Minimum bid: $4.90
• 1 million daily searches
Can quickly drain our budget!
Lower price for lower search terms “market inefficiency” (Bartz K et al.)
Cost per Click increases with Search volume
(Bartz K et al.)

20. Campaign Management
Research opportunities, examples
Semantic Keyword Extraction algorithms & natural
language processing:
• Can use deal, merchant page, and related pages as
corpus
• Shallow NLP, N-Gram, TFIDF
Cyclic keyword graph (Joshi P. et al. 2014)
Graph theory (Joshi P. et al.)
Use directed graph to compute relevance between terms

21. Talk Overview
Computational Marketing at Groupon
● What is Computational Marketing?
● Campaign Management
● Marketing Channel Attribution
● Bidding
● In Summary

22. 2 days later
$
t
12:00 Groupon Email
12:10 Google Search
(Google Ad)
17:10 Mobile App
13:00 Facebook
My devices

23. Rule based attribution models
Multi-channel Attribution: Algorithms and Modeling
Given a series of landings on the site from a variety
of external sources, which should be associated
with the purchase?
These models differ greatly in terms of results and
don’t take into account:
• Complex interplay between channels (eg.
Display > SEM > SEO may be a frequent path to
conversion)
• Differences between channels and product types
(e.g. Travel deals convert better on desktops and
will involve longer time periods allocated to
research)
• Static models that do not evolve over time
Last click
First click
Linear
Time Decay
U-Shape

24. Multi-channel Attribution
Multi-channel Attribution: Algorithms and Modeling
Display Adv.
Direct
Organic Search
(Google / Bing)
Search Engine
Marketing
Berman, R . Beyond the last touch
Traffic sources of conversion

25. Game theory / Shapley Value (Source: Shapley, L.):
Markov Chains (Source: Bryl’, S.):
Journey 1: C1 – C2 – C3 - $
Journey 2: C1 – END
Journey 3: C2 – C3 - END
Other Algorithms
Multi-channel Attribution: research opportunities, examples
Facebook
Clicks
Adwords
Clicks
Sales
5 0 $10
0 5 $5
5 5 $20
Facebook value:
Adwords value:
Cooperative effect:
2
1
20 – (2x5 + 1x5) = 5

26. Analytics Pipeline
N-Tier architecture
Homepage Deal page Shopping cart
Frontend services
Click Stream
Tracking parameters /
Cookies / Javascript / etc.
Significant volumes of data must
be analyzed :
• Hundreds of thousands of user
events per minute (views,
purchases, cart, etc.).
(Clickstream)
• Service oriented architecture
likely involves numerous loosely
coupled independent services,
powered by hundreds of servers
• Service interfaces and event
likely differ significantly
Data Storage
Clicks, views, purchases, etc.
Service instance / server

27. Clickstream Analytics
Deal Click
groupon.com/deal?
utm=UK_RTC_X
Deal Purchase
groupon.com/checkout?...
Click Stream
Logged in? No
Cookie X
IP address Y
Browser thumbprint Z
Logged in? Yes
Cookie X
IP address Y
Browser thumbprint Z
• Compute individual user journeys in order determine channel attribution based on selected model
• Individual campaigns can be identified via tracking parameters set on the advertising platform
• Cross device tracking: 67% of customers start shopping on one device and continue on another (Google)
…
User A User A

28. Supporting Architecture
Lambda Architecture (Source: Marz, N. et al.)
Data Stream
Archive
Job2Job1All events
Recent
events
Batch Layer
Speed Layer
Worker nodes
Results

29. Open Source Implementation
Lambda Architecture (Source: Marz, N. et al.)
HDFS
All events
Recent
events
Batch Layer
Speed Layer
Results

30. Talk Overview
Computational Marketing at Groupon
● What is Computational Marketing?
● Campaign Management
● Marketing Channel Attribution
● Bidding
● In Summary

31. Bidding basics (SEM)
Second price auctions (sealed)
Keyword:
“Food in Seattle”
Other match criteria:
User location
Time of day
Known user
Etc.
Max Cost per Click
$5
$4
$3
$2
Pays second highest bid:
$4.01

32. Bidding basics (SEM)
At it’s simplest – bid can be calculated as:
Avg(Revenue Per Click) / (Target Return on spend)
How much should be willing to pay per click?
For example – for “Food in Seattle”:
- 100 people clicked the campaign
- $500 was generated as per attribution method
- Our target is: %200 – make $2 for every $1 spent on marketing
- Avg(Revenue Per Click) / (Target Return on spend) = $5 / 2 = $2.5 Source: Ortec Mktg

33. Bidding Context (SEM)
Many contextual modifiers can be applied – resulting in millions of combinations possible. Some examples:
• Location targeting
• Device
• Time of day
• Remarketing: Should we pay more for known users?
Other challenges: do we have enough history for a given campaign? Can we exploit?
• Historical performance of merchant / deal / category / etc ?
• Performance across channels
Challenges and Opportunities

34. Bidding Opportunities
Research opportunities & examples
Decision tree style approach:
- Non linear supervised learning method
- Can be used for conversion estimation (Wang
J. et al)
- Simple but suffers from high variance
- Other approaches: collaborative filtering, etc.
Source: Wang J. et al
Keyword Clustering: (Source: Regelson et al.)
- Compensate for sparse data and lack of history
- Group campaigns with similar expected
performance

35. In summary
Computational marketing is a complex science involving a wide range of disciplines, provides numerous opportunities for research.
• Information retrieval, Big data, Machine learning, Natural Language Processing, etc.
• Financial scale is huge
Many other topics not touched upon but equally challenging:
• Landing page and customer journey optimization. Is the whole journey consistent?
• A/B testing of creatives and landing pages
• Re-targeting of known users

36. Thank you!