DataScienceLab2017_Как знать всё о покупателях (или почти всё)?_Дарина Перемот

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DataScienceLab, 13 мая 2017 Как знать всё о покупателях (или почти всё)? Дарина Перемот (ML Engineer at SynergyOne) Раскроем собственный ответ на вопрос "Чего же хочет покупатель?". Поделимся результатами исследований транзакций и расскажем, есть ли у вас домашний питомец. А так же, продемонстрируем, как машинное обучение уже сейчас помогает узнавать вас ближе. Все материалы: http://datascience.in.ua/report2017

Technologie

How to know (almost) everything
about customers?

Tricky questions time
Who would want to read your minds?

What would the merchant want?
Tricky questions time

Tricky questions time

What to sell?

What is its price?

When to sell it?

Whom to sell?

Customer expert wanted

Experienced

Qualified

Impartial

Honest

Experts
Ukrainian dataset
2,5 years
210 K rows
7 K customers
22 K POS
American dataset
1 year
180 K rows
12 K customers
40 K POS
What they have in common?


Cash

Food stores

Cafe & restaurants

Gas stations

...

Tricky questions time
Is there any “similarity” in client's behaviour?

Key points

Uses less or equal than 4 MCC codes.
Ukrainian dataset: 64%
American dataset: 61%

Uses less or equal than 6 MCC codes.
Ukrainian dataset: 73%
American dataset: 76%

Tricky questions time
Why do we interested in the “similarity” of
customers?

Benefit
Targeted advertising in real time

Behavior pattern
Behavior pattern = customer’s tag

Behavior pattern
Customer’s feature connected with distribution of
expenditures via budgeting categories, locations,
time.

Tricky questions time
Why would merchant need all this stuff?

Tricky answer time

Discover unexpected target audience

Get to know the competitors

Find out the locals

Links
YaCM 2016 (about hyperlocation adds):

https://events.yandex.ru/lib/talks/3469/
Sberbank Data Science Journey (MCC2Vec for
Sberbank):

https://www.sdsj.ru/slides/MCC2VEC.pdf

https://youtu.be/0q5p7xP4cdA?t=23702

Links
DBSCAN vs others:

http://scikit-learn.org/stable/auto_examples/clu
ster/plot_cluster_comparison.html
OneKarma beta-test UI:

https://onekarma.synergyone.pro
Comics:

https://marketoonist.com/

Thank You
Darina Peremot
ML engineer in SynergyOne
email: dp@synergyone.pro
facebook: @darina.peremot
telegram: @peremot

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