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 Do you know that feeling when an app
knows exactly what you want?
@renan_oliveira
Principal Data Scientist
AN UNIQUE MOMENT - YOU CAN'T FAST-FORWARD OR SKIP
Time and Quality
Decision process
Special occasion
We are not a streaming service.
Ordering food has an additional
difficulty being assertive because
fixing a mistake is not like skipping
a song: placing an order involves
more money and logistical operation.
IFOOD IN NUMBERS
20 million orders
270k drivers
100k restaurants
660 cities
https://www.uol.com.br/tilt/noticias/redacao/2019/08/29/haja-fome-ifood-recebe-mais-de-7-pedidos-a-cada-segundo-no-brasil.htm
FOOD IS A VERY PERSONAL CHOICE
Taste Profile
Speed
Brand
Price Affinity
Offer Affinity
etc…
Taste Profile
Dish
Cuisine
Offers
Rating
etc…
Match
CHALLENGES
Locality geographical constraint for model training
Speed if you are hungry you will want to eat soon
Serviceability production capacity and restaurant quality
Feedback implicit (engagement) vs explicit (ratings)
Growth cold start problem
DEPLOY MODEL PIPELINE
COLLABORATIVE FILTERING - IMPLICIT FEEDBACK
5 2 2
? 3 4
5 3 ?
ASH
GOKU
SEIYA
Orders
User Journey
Built engagement
ALS is very good to reinforce
tastes but fails to identify new
tastes. Since our problem has
geographical constraints, our
data is more sparse than usual.
USER HISTORY + CONTENT BASED
BOUGHT
TOMATO PIZZA - 3
FREE DELIVERY - 2
TOMATO PIZZA - 2
FAST DELIVERY - 1
TRENDING - 2
HAMBURGUER - 4
COKE - 2
FAST DELIVERY - 1
TERMS AND
RELEVANCE
TOMATO PIZZA - 5
HAMBURGUER - 4
FAST DELIVERY - 4
COKE - 2
FREE DELIVERY - 2
FAST DELIVERY - 3
TRENDING - 2
HISTORY
TOMATO PIZZA
FREE DELIVERY
COKE
SALAD
JUICE
FAST DELIVERY
TOMATO PIZZA
HAMBURGUER
FAST DELIVERY
TERMS STORESRECSYS
“AKINATOR” - EXPLICIT FEEDBACK
1. Select cuisines
2. Select the expected price
3. Select time range
Kmeans is great for a cold start
scenario in which we don't know
much about the customer but we
have information about other
costumers and restaurants nearby.
renanoliveira.net
THANK YOU!
if you want to revolutionize the food delivery market
we are hiring!
www.ifood.com.br/carreiras

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iFood Recommendations

  • 1.  Do you know that feeling when an app knows exactly what you want? @renan_oliveira Principal Data Scientist
  • 2. AN UNIQUE MOMENT - YOU CAN'T FAST-FORWARD OR SKIP Time and Quality Decision process Special occasion We are not a streaming service. Ordering food has an additional difficulty being assertive because fixing a mistake is not like skipping a song: placing an order involves more money and logistical operation.
  • 3. IFOOD IN NUMBERS 20 million orders 270k drivers 100k restaurants 660 cities https://www.uol.com.br/tilt/noticias/redacao/2019/08/29/haja-fome-ifood-recebe-mais-de-7-pedidos-a-cada-segundo-no-brasil.htm
  • 4. FOOD IS A VERY PERSONAL CHOICE Taste Profile Speed Brand Price Affinity Offer Affinity etc… Taste Profile Dish Cuisine Offers Rating etc… Match
  • 5. CHALLENGES Locality geographical constraint for model training Speed if you are hungry you will want to eat soon Serviceability production capacity and restaurant quality Feedback implicit (engagement) vs explicit (ratings) Growth cold start problem
  • 7. COLLABORATIVE FILTERING - IMPLICIT FEEDBACK 5 2 2 ? 3 4 5 3 ? ASH GOKU SEIYA Orders User Journey Built engagement ALS is very good to reinforce tastes but fails to identify new tastes. Since our problem has geographical constraints, our data is more sparse than usual.
  • 8. USER HISTORY + CONTENT BASED BOUGHT TOMATO PIZZA - 3 FREE DELIVERY - 2 TOMATO PIZZA - 2 FAST DELIVERY - 1 TRENDING - 2 HAMBURGUER - 4 COKE - 2 FAST DELIVERY - 1 TERMS AND RELEVANCE TOMATO PIZZA - 5 HAMBURGUER - 4 FAST DELIVERY - 4 COKE - 2 FREE DELIVERY - 2 FAST DELIVERY - 3 TRENDING - 2 HISTORY TOMATO PIZZA FREE DELIVERY COKE SALAD JUICE FAST DELIVERY TOMATO PIZZA HAMBURGUER FAST DELIVERY TERMS STORESRECSYS
  • 9. “AKINATOR” - EXPLICIT FEEDBACK 1. Select cuisines 2. Select the expected price 3. Select time range Kmeans is great for a cold start scenario in which we don't know much about the customer but we have information about other costumers and restaurants nearby.
  • 10. renanoliveira.net THANK YOU! if you want to revolutionize the food delivery market we are hiring! www.ifood.com.br/carreiras