ZALANDO Personalisation At Zalando @Melissa_Weston_ @Zalando - - PowerPoint PPT Presentation

ZALANDO

Personalisation At Zalando

@Melissa_Weston_ @Zalando

MELISSA WESTON

17/09/2019

OUR STORY – NOW AND THEN

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WE WENT FROM START-UP…

@Melissa_Weston_ @Zalando

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…TO GROWN-UP

@Melissa_Weston_ @Zalando @Melissa_Weston_ @Zalando

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HOW OUR ASSORTMENT GREW

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ASSORTMENT 2008 2010 2011 2018

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WE BRING FASHION TO PEOPLE IN 17 COUNTRIES

2008-2009 2010 2012-2013 2011 2018

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FROM SCREAMING FOR ATTENTION…

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…TO INSPIRING PEOPLE AND CREATING FASHION EXPERIENCES

@Melissa_Weston_ @Zalando

OUR VISION: THE STARTING POINT FOR FASHION

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PLATFORM STRATEGY

FASHION, TECH, OPERATIONS = the three core competencies are the basis of our platform strategy

BRANDS CONSUMERS ENABLER

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SUSTAINABLY STRONG GROWTH

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ZALANDO AT A GLANCE

~ 5.4billion EUR

revenue 2018

> 300 million

visits per month

~ 14,000

employees in Europe

> 80%

• f visits via

mobile devices

> 28

million

active customers

> 400,000

product choices

> 2,000

brands

17

countries

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WE LOVE FASHION

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WE OFFER A SUCCESSFUL AND CURATED ASSORTMENT

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> 400,000

articles from

> 2,000

international brands

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private labels

HIGHLY EXPERIENCED

category management

LOCALIZATION

• f the assortment

CURATED SHOPPING

with Zalon

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WE DRESS CODE

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WE ARE CONSTANTLY INNOVATING TECHNOLOGY

@Melissa_Weston_ @Zalando

HOME-BREWED, CUTTING-EDGE & SCALABLE

technology solutions

> 2,000

employees at international tech locations

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HQs

in Berlin

help our brand to

WIN ONLINE

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A new employee called Toru is starting in Zalando's warehouse in Erfurt,

• Germany. You might consider this

nothing special, but Toru is an autonomous picking robot that can not

• nly move whole boxes, but even

individual objects.

TORU

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We use Big Data to better describe and identify different components of fashion across different brands so that they can be properly indexed and a more accurate recommendation made to the consumer

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PERSONALIZATION AND BIG DATA

• Algorithmic Fashion Companion (AFC)
• Sizing (Based on size-related returns

and machine learning)

• Homepage (Compositional relevance

and recommendations)

• Big Data & Personalization (Dublin Tech

Hub)

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• AFC: is a digital, scalable outfit recommendation tool,

providing customers with unlimited outfit suggestions. Customers browsing Zalando are shown recommended outfits based on anchor items in their wishlist and anchor items which they have at home (previously bought on Zalando and not returned).

• Anchor items can be any article of clothing around

which an outfit is then built. The AFC is an algorithm which makes use of machine learning.

• The algorithm was taught how to put together outfits

by studying 200k manually-created outfits from Zalon and Shop the Look.

@Melissa_Weston_ @Zalando

ALGORITHMIC FASHION COMPANION (AFC)

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• Sizing: The sizing team is one of our best examples when

it comes to personalization. Customers are shown recommendations on sizing in one of two ways, either by suggesting a specific size for them, or by suggestion that the brand often produces, say, shoes one size bigger or smaller than the customer might be used to.

• These size recommendations are based on two different

data sets: firstly, size-related returns, in which we record whether a customer found an item of clothing to be too large or two small.

• The second data set is generated by a team of fitting

models, who try on different items and compare them to their ‘regular’ size. Machine learning algorithms are then able to predict which items from certain brands are likely to have sizing issues.

@Melissa_Weston_ @Zalando

SIZING

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• Homepage: On the homepage, we follow two types of

personalization.

• The first is what we call compositional relevance: it sorts

the content entities on the home page according to your browsing behaviour, preferences and purchase history. For example if you buy a lot of items on sale, a content entity displaying sale items will be shown first.

• The second form of personalization is in the form of

recommendations: what gets shown in these content entities is further personalized according to your tastes.

@Melissa_Weston_ @Zalando

HOMEPAGE PERSONALIZATION

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• Personalization & Mobile: Effective personalization must

be a seamless experience across all devices:

• “That’s one of the reasons w

e do invest in making it clear that, if they [our customers] login, it w ill help to make the experience better for them and, if they start liking brands, then w e can save that and capture

• data. Ultimately w

e need a 360 degree channel alignment” - Daniel Schneider.

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PERSONALIZATION & MOBILE

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• Big Data & Personalization: In order to analyze the big

data needed for personalization, a Tech hub was opened in Dublin in April 2015.

• One aim is to develop fashion insights and secure an

advanced level of personalization. The reasoning behind this was that when we receive data on different fashion products from our suppliers, more often than not it is highly inconsistent across brands. We need to be able to better describe and identify different components of fashion so that they can be properly indexed.

• Another key purpose which the Dublin office fulfils is

creating a machine learning platform to allow more teams within Zalando to make use of advanced artificial intelligence applications.

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BIG DATA & PERSONALIZATION

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WE FOSTER THE INNOVATIVE POWER OF OUR EMPLOYEES

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HACK WEEK INNOVATION LAB TECH ACADEMY USER LAB SELF- ORGANIZED GUILDS

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WE LIVE OPERATIONAL EXCELLENCE

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WE OPERATE FASHION

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fulfillment centers

> 20

payment methods adapted to each market

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markets customer care in

13

languages

INNOVATIVE

content creation

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ZALANDO.CO.UK

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THE STARTING POINT FOR FASHION

THANK YOU

MELISSA WESTON MELISSA.WESTON@ZALANDO.DE @Melissa_Weston_ @Zalando

17.09.219

NORTHERN EUROPE MARKETING LEAD UK & IE

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• r completeness of the presentation and the information contained herein

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