Advanced attribution model
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Transcript of Advanced attribution model
Advanced Attribution Model,Analytics Summit, November 13th , 2014
Aspa Lekka [email protected]
Foodpanda is a global online food delivery marketplace
Company:
www.foodpanda.com
Founded in 2012
Present in more than 45 countries
Business Intelligence & Analytics:
Google Analytics and Google Analytics Premium
Team of 8 people
TVMobile App Ad
SEM Conversion
Customer Journey
Multiple channels:
•SEM•Display•CRM•Affiliate•Radio•Price Comparison•…..
Marketing budget allocation
Get new visitors
AWARENESS
Maximize orders
ACTION
0 50 100 150 200 250
Search
Price comparison
Affiliate
Display
Direct
Social
Last click- orders TOTAL: 503
0 20 40 60 80 100 120 140 160 180
Search
Price comparison
Affiliate
Display
Direct
Social
Last click - orders TOTAL: 438
Awareness
Interest
Desire
Action
Why attribution model?
Every channel gets attributed the correct orders
Calculating the CAC for Marketing Campaigns
NEW CUSTOMERS ACQUIRED
Campaign 1 BUDGET Monday Tuesday Wednesday Thursday Friday Saturday Sunday TOTAL
Monday 1,000 € 13 13
Tuesday 1,100 € 21 21
Wednesday 900 € 22 22
Thuerday 1,000 € 25 25
Friday 850 € 23 23
Saturday 1,200 € 24 24
Sunday 1,000 € 26 26
CAC
77 €
52 €
41 €
40 €
37 €
50 €
38 €
How efficient was the Marketing Budget?
NEW CUSTOMERS ACQUIRED
Campaign 1 BUDGET Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday TOTAL
Monday 1,000 € 10.5 2.9 14.5 10.8 12.3 19.0 9.0 79.0
Tuesday 1,100 € 10.5 6.6 3.9 13.3 3.1 6.2 13.9 57.4
Wednesday 900 € 5.2 4.1 8.0 9.4 8.1 18.1 17.8 70.6
Thuerday 1,000 € 12.7 20.2 17.3 5.8 3.9 4.0 9.7 73.6
Friday 850 € 4.7 7.8 12.0 6.6 6.0 20.5 2.6 60.2
Saturday 1,200 € 19.4 16.7 7.6 17.6 19.0 6.1 16.1 102.4
Sunday 1,000 € 7.4 2.2 5.9 15.2 13.4 16.4 11.7 72.1
CAC*
13 €
17 €
14 €
14 €
17 €
10 €
14 €
Data Driven Models for Attribution
SHAPLEY VALUE 1.
SURVIVAL ANALYSIS2.
PATH ANALYSIS NETWORKSSTRUCTURAL EQUATION MODELING
3.
The Shapley Value
SHAPLEY VALUE
The Shapley value is a way to assign credit among a group of “players” who cooperate for a certain end
An example:
• 3 players(2 with right glove and 1 with left glove)
• Goal: Form a pair• Assign credit to each player after forming a pair
There are two possible pairs that we can form and in both of them, Player 1 needs to be involved. Therefore, Player 1, is of more importance compared to Player 2 or Player 3. Consequently, when sharing the profits, he should get a bigger part compared to Player 2 (if we case 1 is true) or Player 3 (if case 2 is true)
The Shapley Value
• 3 channels
• A click chain that consists of these 3 channels and led to 500 transactions
• Evaluate the contribution of each channel to these 500 transactions
100
125
50
270
375
350
500
The Shapley Value
SEM100
DISPLAY270-100=170
SEO
500-270=230100
125
50
270
375
350
500
SEM100
SEO375-100=275
DISPLAY
500-375=125
DISPLAY125
SEM270-125=145
SEO
500-270=230
DISPLAY125
SEO350-125=225
SEM
500-350=150
SEO50
SEM375-50=325
DISPLAY
500-375=125
SEO50
DISPLAY350-50=300
SEM
500-350=150
Calculating the Shapley Value
Calculating the Shapley Value
SEM100
DISPLAY270-100=170
SEO
500-270=230
SEM100
SEO375-100=275
DISPLAY
500-375=125
DISPLAY125
SEM270-125=145
SEO
500-270=230
DISPLAY125
SEO350-125=225
SEM
500-350=150
SEO50
SEM375-50=325
DISPLAY
500-375=125
SEO50
DISPLAY350-50=300
SEM
500-350=150
SEM’s expected marginal contribution is:
DISPLAY’s expected marginal contribution is:
SEO’s expected marginal contribution is:
SEM162
(0.32)
DISPLAY162
(0.32)
SEO176
(0.36)
500 orders attributed to the three channels :
Survival Analysis
SURVIVAL ANALYSIS
Target population
Treatment 1
Dead
Alive
Treatment 2
Dead
Alive
Event
Event
TIME
What is the patient’s probability to be still alive after 20 years?
Survival Analysis
Visitors
Channel 1
Conversion
NO Conversion
Channel 2
Conversion
NO Conversion
Event
Event
TIME
What is the visitors’ probability to convert after 30 days or 5 visits?
Survival Analysis
Day1Day2 Day5 Day2
Day3 Day7 Day8
DAY 1 / VISIT 1
0 1 0 1
DAY 3 / VISIT 3
0 1
DAY 6 / VISIT 6
0 1
DAY 9 / VISIT 9
Survival Analysis
VIS
ITO
RS
TIMESTART END
: censored observation
: event (conversion)
Censored observation:
There is not “time to event” recorded because:
•Loss of follow up Drop out Conversion due to a
cause that is out of our interest
•End of the study
Survival Analysis
Estimate time-to-event for a group of individuals, such as time until a visitor purchases
To compare time-to-event between two or more groups, such as visitors that have clicked on a Display ad compared to visitors that have not clicked on a Display ad.
To assess the relationship of co-variables to time-to-event, such as: does number of clicks, pages viewed, or time on site effect the decision to purchase?
Survival Analysis
DATA DRIVEN MODELS
ADJUSTED TO EACH CASE
LIMITED TUTORIALS
ADJUST FORMULAS TO YOUR DATA
EASY TO SET UP(QUITE)
LINK ADS WITH ONSITE BEHAVOR
FIND COST EFFICIENT CLICK CHAINS
MERGE OFFLINE AND ONLINE DATA
Evaluation & Suggestions
Thank you!Aspa Lekka