Find out the top ten bigdata - ecommerce use case. Every E-Commerce site is Different. SpotDy BigAI provides 100% customized solutions to you. Tailor fit solutions drive 5X more revenue.

1. Top Ten
Big Data - ECommerce
Use Cases
Powered by SpotDy
Arvind Rapaka
CEO, SpotDy Inc.

2. Why Big Data and Predictive Analytics
for ECommerce
Fact 1 : Companies that use Predictive Analytics achieve 73%
higher sales than those who have never done it.
Fact 2: 65% of customers feel completely frustrated with the
bad customer experience, targeting?
Fact 3: Real time personalization helps upsell and cross sell
by 68%.

3. Top 10 Use Case

4. Personalization & Recommendation
Real time personalization based on
○ Recent views
○ Most Recent buys
○ Gender and Demo
○ Location
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5. Upsell or Cross selling
● Real time upselling and cross selling while user browsing
○ Item based filtering
○ User based filtering
Frequently bought together Customers Who Bought This Item Also Bought

6. Optimal Pricing
● Price is the most effective way to convert
● Finding Optimal Price is always a challenge
Data Sources:
● Competitor Pricing
● Current Pricing
● Product Meta Info
● Inventory & Demand
● Merchant Discounts
● Shipping costs
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7. SEO
SEO is big. If the user can’t discover your content, you can’t sell.
○ Site In-linking
○ Taxonomy
○ Demand Insights
Site In Linking
Demand
Insights
Taxonomy
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8. CRM
Customer Retention
○ Email personalized content
○ Price notification
○ Product notifications
○ Notify personalized coupons and discount offers
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9. Cross Device Correlation
● User are browsing on various devices
○ Building continuity helps user experience
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10. Traffic Acquisition/Advertising
Advertising is the important but understanding the following are the key:
○ ROI. Advertising is expensive.
○ What/Why/How are Channels the working
○ Which Campaigns are the most efficient
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Data Sources:
● Campaign Data
● Campaign Pricing
● Sales related to
Campaign
● CTR
Campaign
Performance
Optimal
bidding Pricing

11. Customer Analysis
Understanding your customer is a must. Following are the key metrics:
● customer lifetime value (CLV)
● customer future value (CFV)
● customer churn
Data Sources:
● Customer Sales Data
● Customer browsing history
● Customer Click Data
● Customer Demo/Geo Data
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12. Dynamic Promotion
Promotions are powerful tools to help increase revenue, but they are
costly and important to manage closely.
● Build data-modeled approach that ensures each promotion is
presented to just the customer who needs it to drive a purchase.
Data Sources:
● Customer profile data
● Product Inventory
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13. Personal Shopping Assistant
Tools such Personal Shopping
Assistant help better user
experience to drive conversions.
The Process involves:
● building Knowledge database
● product Image Repository
● building Q&A Engine

14. About SpotDy BigAITM
BigAI™ for enterprises introduces a completely new model of operational
intelligence using deep data science, giving companies a competitive edge by
uncovering new insights in real time. BigAI™ solutions gives you the power to
truly understand what your customer want to drive product discovery,
marketing etc.
Each step unlocks the next, creating a unique customer experiences that drive
incremental revenue and customer satisfaction. As a complete, integrated and
dynamic platform, it reduces time to results and eliminates costly stovepipe
architectures, reducing complexity and delivering at a fraction of the cost.

15. Want to see how we can help you:
Please contact arvind.rapaka@spotdy.
com