Tirendo - eCommerce Platform


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Tirendo - eCommerce Platform

  1. 1. Strictly private and confidential 2014 - All Rights Reserved E-Commerce 3.0 Challenges for a future prove e-commerce platform 02.06.2014, Christian Zacharias
  2. 2. Strictly private and confidential 1 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
  3. 3. Strictly private and confidential 2 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
  4. 4. Strictly private and confidential 3 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
  5. 5. Strictly private and confidential 4 Agenda
  6. 6. Strictly private and confidential 5 Agenda
  7. 7. Strictly private and confidential 6  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
  8. 8. Strictly private and confidential 7  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
  9. 9. Strictly private and confidential 8 Logging Architecture Get to know your Customers
  10. 10. Strictly private and confidential 9 Agenda
  11. 11. Strictly private and confidential 10 Reports and direct access Get Insights from you Data DW H HDFS Data Stores Reports, KPI´s, Mails Adhoc Queries, Direct Data Access  Predefined Reports for quick insights  Summary-Mailings  Dashboards for specific Business Areas  ! Report Analytics  Direct access to prepared Data  Only Read Access  Dedicated Instance  Promote often used queries to Reports  ! Add Metrics about Data Usage
  12. 12. Strictly private and confidential 11 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
  13. 13. Strictly private and confidential 12 Agenda
  14. 14. Strictly private and confidential 13 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
  15. 15. Strictly private and confidential 14 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
  16. 16. Strictly private and confidential 15 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
  17. 17. Strictly private and confidential 16 Agenda Get to know your Customers Get Insights from you Data Data takes over your shop Get ready for Scale
  18. 18. Strictly private and confidential 17 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
  19. 19. Strictly private and confidential 18  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
  20. 20. Strictly private and confidential 19 E.g. Tirendo Platform Architecture
  21. 21. Strictly private and confidential Questions 20