Tirendo eCommerce Platform 3.0
Transcript of Tirendo eCommerce Platform 3.0
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2014 - All Rights Reserved
E-Commerce 3.0 Challenges for a future prove e-commerce platform
02.06.2014, Christian Zacharias
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� Customers starts discovering the web and the shopping possibilities � Pull behavior – Customer looks for a specific product in the shop � Easy to sell Products � Agencies building the fist ecommerce systems � Rise of Intershop and big integrated player (Broadvision, Art Technology Group) � XTcommerce and osCommerce as free alternatives
The Gold Rush
E-Commerce 1.0
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� Customer gets more importance � More Content and Multimedia to engage Users � Customers Voice – Reviews � Pull approach – try to get the customer on the page � Stimulated impulse shopping – Deal-shopping � Integrated Platforms (Hybris, Magento, Oxid) § Monolithic approach § Hard to scale § Caching helps (Varnish)
� Switch to own solution after hitting the performance wall
OpenSource and Hard to Scale
E-Commerce 2.0
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� Cross-device ecommerce experience § Start buying process mobile finish on desktop § Increase reach through API´s and Apps
� Know everything about you customer § Better recommendations and prediction systems § Act data-driven and deal with BigData
� Service oriented Approach § Decouple you platform § Single responsibility principle § Easier to scale
What is this about
E-Commerce 3.0
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Agenda
Get to know your Customers
Get Insights from you Data
Data takes over your shop
Get ready for Scale
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Agenda
Get to know your Customers
Get Insights from you Data
Data takes over your shop
Get ready for Scale
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� Each Customer Contact is important � Onsite
§ Visited Pages § Products watched § Baskets § Checkout § Orders § Logins
� Offsite § Adwords, Affiliates, Newsletters and Mails § Marketplaces (Daparto, Idealo, …) § Banners placed through Marketing-Services § Retargeting
� Mobile
What should I log
Get to know your Customers
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� Create a Logging System § Integrate Logging system
� Track and Mark every Visitor § Create VisitorId for each new visitor and mark him trough a Cookie § Identify existing Visitor through this Cookie
� Correlate all action from the visitor to this VisitorId � Integrate your logging system into your Application Platform
§ Controller Logic § Database connector § Background Processing § CronJobs
� Add Analytics Solutions used to track OnPage Actions and additional Information about the Visitor/Customer
� Track inbound URL´s to track marketing efforts and campaigns
Track everything!
Get to know your Customers
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Logging Architecture
Get to know your Customers
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Agenda
Get to know your Customers
Get Insights from you Data
Data takes over your shop
Get ready for Scale
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Reports and direct access
Get Insights from you Data
DWH
HDFS
Data Stores Reports, KPI´s, Mails
Adhoc Queries, Direct Data Access
ü Predefined Reports for quick insights
ü Summary-Mailings ü Dashboards for specific
Business Areas
ü ! Report Analytics
ü Direct access to prepared Data ü Only Read Access ü Dedicated Instance ü Promote often used queries to
Reports
ü ! Add Metrics about Data Usage
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Business Inteligence
Get Insights from you Data
DWH
HFS
Data Stores
Business Intelligence
ETL Processes Aggregate
Data
Calculate statistical Datasets
Data Driven Shop
Recommendations & Bundles
Intelligent CRM
Marketing Control
� Aggregate and implement statistical functions to calculate co-occurrence matrices of Products2Products and Products2Visititors
� Collect Marketing- and Campaign-Performance Data � Analyze Customer Behavior and correlate with Product and Order Data to improve CRM � Use existing OpenSource Solutions like Apache Mahout to do the heavy mathematics
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Agenda
Get to know your Customers
Get Insights from you Data
Data takes over your shop
Get ready for Scale
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� Co-occurrence Matrix for Product2Products Recommendation § Upselling Potential § Boosts by Margin-, Sales- or Stock-Business Rules
� Recommend Cross-Selling Products � Provide Products-Scores to improve Product Listings
§ Scores based on Stock, Margin, Revenue, Sales .. § Calculate final Sorting-Score based on specific formulars
� Generate statistical Bundles � Personalize the full shop experience
Recommendations & Bundles
Data takes over your shop
Data Driven Shop
Recommendations & Bundles
Intelligent CRM
Marketing Control
How to measure your success: TEST TEST TEST
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� Improve Customer Mailings and Transaction-Mails � Newsletter Optimizations and Personalization � BI generates Recommendation of Products for the
Recipients � Recommend Products based on historic customer
behavior and insights
Intelligent CRM
Data takes over your shop
Data Driven Shop
Recommendations & Bundles
Intelligent CRM
Marketing Control
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� Marketing tracking provides insights into marketing performance § Marketing Dashboards and Reports from DWH
� Control your marketing spending's based on campaign-performance
� Recommend Marketing Material Placement based on Customer intends and behavior § Banner generation
� Automate Bidding and Campaign Management
Marketing Control
Data takes over your shop
Data Driven Shop
Recommendations & Bundles
Intelligent CRM
Marketing Control
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Agenda
Get to know your Customers
Get Insights from you Data
Data takes over your shop
Get ready for Scale
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Low information content Not enough significant data for statistical analysis
Deal with the data
Get ready for Scale
A
B
Data Usage f(P,T)
Product-range
Exponential increase of data usage within the increase of the product-range and traffic Significant also increase exponential Scale Processing and Storage in the same way
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� Scale horizontal through virtualization of you platform and Service Oriented Architecture � Collect messages non-blocking and asynchronous
§ Receiver is a central service accessible by all components � Flexible message-distribution and -processing
§ Different message consumers with different purposes • Direct log analysis (e.g. Kibana, ElasticSearch) • Permanent store all Log-Messages for long-term analysis (e.g. Hadoop & Hive)
� Data Storage needs the scale as well § HDFS, self hosted or cloud § S3 § Base for further Data aggregation and processing
Prepare your System
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E.g. Tirendo Platform Architecture
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Questions
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