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


� 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


� 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


Agenda

Get to know your Customers

Get Insights from you Data

Data takes over your shop

Get ready for Scale


Agenda




Get ready for Scale


� 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



� 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!



Logging Architecture



Agenda




Get ready for Scale


Reports and direct access


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


Business Inteligence


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


Agenda




Get ready for Scale


� 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



Data Driven Shop


Intelligent CRM

Marketing Control

How to measure your success: TEST TEST TEST


� 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 Driven Shop


Intelligent CRM

Marketing Control


� 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 Driven Shop


Intelligent CRM

Marketing Control


Agenda




Get ready for Scale


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


� 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


E.g. Tirendo Platform Architecture

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Questions

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Date post:	20-Jun-2015
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