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Big Data Analytics in B2B Ecommerce - Making Big Decisions
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Big Data Analytics in B2B Ecommerce - Making Big Decisions


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Understand what Big Data Analytics can do for your B2B Ecommerce business.

Understand what Big Data Analytics can do for your B2B Ecommerce business.

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  • 1. • Industry Context • Data in Ecommerce • Why should B2B Ecommerce firms embrace Big Data Analytics? • Areas in which Big Data Analytics can Impact B2B Ecommerce Business
  • 2. • Forrester • Frost & Sullivan B2B ecommerce transactions in the US will reach $560 billion by the end of 2013 B2B online retailing – one of the leading global trends that will shape 2014 • Amazon entered with Amazon Supply (in beta) • Google entered with Google Shopping for Suppliers (in beta) β
  • 3. Large Volume and Variety of Data Structured Real Value lies here! Unstructured They need to Capture and Decipher concealed patterns and unidentified associations
  • 4. Firms are now seeking suitable tools to help them: Fix optimal pricing Identify niche customer segments Pinpoint customer touch points Uncover obscure insights
  • 5. Organizations are looking for faster and more effective ways to: Collect Manage Dispense Control structured and unstructured product information Customers are looking for: Adequate Consistent Easy-to-find product information (If these criteria are not met customers look for alternate options, adversely affecting sales and brand perception with longlasting effects.)
  • 6. B2B companies must work towards the application of to provide
  • 7. $ Personalization Data analytics can be used for personalization of inbound customers by highlighting interesting related content based on their previous purchases or by making offers and promotions to returning customers. Pricing Pricing data extracted from ERPs, CRMs and other applications can be synchronized to achieve optimal pricing benefits directed user-centrically towards each customer. Optimizing Supply Chain Distribution hubs, warehouses, transport, freig ht and suppliers generate vast amounts of significant data that can be leveraged to improve buyer-supplier relationships and optimize storage space in warehouses and transport, and also reduce costs.
  • 8. $ $ Sales Opportunities Sales forecasts and pipelines have primarily been based on historical trends. Big Data Analytics helps with relevant and more precise information so sales representatives are no longer driven by hypothetical numbers. Predictive Analytics Predictive analytics, is utilized for customer behaviour modelling by creating customer touch points at crucial junctures and predicting buying patterns. It can also be used to re-activate dormant buyers by retargeting them and reviving their interest through a recommendation.
  • 9. Data Analytics in the B2B space can help companies enhance the customer experience by offering personalized content with rich and interactive product displays and dynamic pricing. This can help with customer acquisition and retention as well as cultivating brand loyalty. Data Analytics helps B2B companies capitalize on their data by not only saving on costs through self-service options, but also highlighting where they can do better in terms of chasing sales opportunities.
  • 10. THANK YOU Here