際際滷

際際滷Share a Scribd company logo

Advance marketing analytics

Download as PPTX, PDF
R
Rajiv Kumar

This document discusses the need to rethink traditional marketing analytics approaches and leverage big data solutions. It notes that while many firms want to be data-driven, few are good at taking action on data. Traditional approaches have limitations in scaling and real-time processing across new data sources like mobile and apps. A big data approach allows for a 360-degree customer view, real-time campaign adjustments, accurate customer value scoring, and understanding customer behavior patterns. It presents architectures for ingesting diverse customer data, building customer profiles, modeling to gain insights, and optimizing marketing based on those insights.

1 of 13
Downloaded 22 times
Transforming Marketing Analytics with Big Data Solutions RAJIV KUMAR DATA SCIENTIST
Why to Rethink marketing analytics? 29% of firms are good at turning data in to action 73% of firms aspire to be data- driven Source: Forresters Global Business Technographics Data and Analytics Survey,2015
Why to Rethink marketing analytics? Big data means big opportunities
Why to Rethink marketing analytics? Traditional Solutions Campaigns CRM/Profile Location Social ClickStream Data Marts ETL/ Stored Procedures Data Warehouse Segmentation and Churn Analysis BI Tools Marketing Offers Does not Model easily in to RDBMS schema New data sources-Mobile, Apps, network Logs? Limited processing power Scaling is Expensive and cumbersome. Manual Work. Few automated system feeds Based on Sample and Limited data Limited processing power Loss in Fidelity
Why to Rethink marketing analytics? continued Gaining a competitive advantage requires operating in real-time across various customer touch points. Big data analytics enables businesses to leverage data driven, insightful, 360 degree view of customer to: Develop customer profiles based on characteristics of individuals and segments. Execute targeted marketing campaigns with real time adjustments to maximize performance. Generate Accurate customer life time value scores. Big data analytics allows business to analyze customer behavior in real time to: Identify customer behavior patterns for any anomalies in behavior. Fostering brand loyalty through clear understanding about customers. Real time tracking of customer journey in marketing funnel.
Why to Rethink marketing analytics? continued Real time and Targeted cross selling and upselling offers Real time offer management Real time Prediction of future behavior of customers to act upon before its too late Real time Prediction of future behavior Understand customer interaction through Omni channel touch points to generate useful insights Which channels primarily maintain brand awareness? Brand Interaction Benchmarking Existing Marketing plans Marketing investments Ratio Purchase Intent behavior Increased ROI Reveal the ideal ratio of marketing investments to maximize sales. Mapping customer behavior with purchase to target right individual at right time Which channels are the primary drivers of current sales? Which channels can deliver incremental sales?
Journey to Advance Marketing Analytics Omni channel Customer interaction Purchase history Social media and web activity Customer behavior Integrate and Understand Customer affinity Conversion path Customer behavior Brand value Customer lifecycle Analyze and Discover Customer segmentation Marketing channel attribution Real time offer management Business processes Decision making Act and Optimize
Journey to Advance Marketing Analytics- Big Data Landscape
Hadoop Ecosystem Journey to Advance Marketing Analytics- High Level Path Data Ingestion Customer Profile Statistical Modeling Structured Data Unstructured Data Semi Structured Data Customer segmentation Marketing channel attribution Offer management Informed business decisions Improved Business Processes Cost optimization ROI
Sample Customer 360 degree profile Who are you? Where are you? What have you purchased? What product you prefer? Who do you know? What can you afford? What is your value to business? How/why have you contacted us? Continue to enrich profile Continue to enrich profile
Journey to Advance Marketing Analytics- Solution Architecture Customer Service Data Demographic data Customer interaction Campaign Data Sales Force Trouble Ticket data Billing data Orders data Contact data Contract Data Product Quall Data Survey Social Media Web Activity Chat /email interactions Voice Call Recordings Textual Correspondence R D B M S Semi Structured Data Unstructured Data HDFS Data lake Machine Learning Data Ingestion Data Access Data Validation Application layer 360 Degree Customer profile Real Time/Stream ing Data Real Time/Stream ing Data
Reference Deployment Architecture Ad hoc/on Demand Source Streaming Source Batch source Reference Data Spark Stream Processing Data Pipe Line Long term Data Warehouse Advance Analytics Operational Reporting Data Discovery Business intelligence Machine Learning(Spark ML) Data Sources Data AccessData Processing, Storage & Analytics
Advance marketing analytics

More Related Content

Advance marketing analytics

  • 1. Transforming Marketing Analytics with Big Data Solutions RAJIV KUMAR DATA SCIENTIST
  • 2. Why to Rethink marketing analytics? 29% of firms are good at turning data in to action 73% of firms aspire to be data- driven Source: Forresters Global Business Technographics Data and Analytics Survey,2015
  • 3. Why to Rethink marketing analytics? Big data means big opportunities
  • 4. Why to Rethink marketing analytics? Traditional Solutions Campaigns CRM/Profile Location Social ClickStream Data Marts ETL/ Stored Procedures Data Warehouse Segmentation and Churn Analysis BI Tools Marketing Offers Does not Model easily in to RDBMS schema New data sources-Mobile, Apps, network Logs? Limited processing power Scaling is Expensive and cumbersome. Manual Work. Few automated system feeds Based on Sample and Limited data Limited processing power Loss in Fidelity
  • 5. Why to Rethink marketing analytics? continued Gaining a competitive advantage requires operating in real-time across various customer touch points. Big data analytics enables businesses to leverage data driven, insightful, 360 degree view of customer to: Develop customer profiles based on characteristics of individuals and segments. Execute targeted marketing campaigns with real time adjustments to maximize performance. Generate Accurate customer life time value scores. Big data analytics allows business to analyze customer behavior in real time to: Identify customer behavior patterns for any anomalies in behavior. Fostering brand loyalty through clear understanding about customers. Real time tracking of customer journey in marketing funnel.
  • 6. Why to Rethink marketing analytics? continued Real time and Targeted cross selling and upselling offers Real time offer management Real time Prediction of future behavior of customers to act upon before its too late Real time Prediction of future behavior Understand customer interaction through Omni channel touch points to generate useful insights Which channels primarily maintain brand awareness? Brand Interaction Benchmarking Existing Marketing plans Marketing investments Ratio Purchase Intent behavior Increased ROI Reveal the ideal ratio of marketing investments to maximize sales. Mapping customer behavior with purchase to target right individual at right time Which channels are the primary drivers of current sales? Which channels can deliver incremental sales?
  • 7. Journey to Advance Marketing Analytics Omni channel Customer interaction Purchase history Social media and web activity Customer behavior Integrate and Understand Customer affinity Conversion path Customer behavior Brand value Customer lifecycle Analyze and Discover Customer segmentation Marketing channel attribution Real time offer management Business processes Decision making Act and Optimize
  • 8. Journey to Advance Marketing Analytics- Big Data Landscape
  • 9. Hadoop Ecosystem Journey to Advance Marketing Analytics- High Level Path Data Ingestion Customer Profile Statistical Modeling Structured Data Unstructured Data Semi Structured Data Customer segmentation Marketing channel attribution Offer management Informed business decisions Improved Business Processes Cost optimization ROI
  • 10. Sample Customer 360 degree profile Who are you? Where are you? What have you purchased? What product you prefer? Who do you know? What can you afford? What is your value to business? How/why have you contacted us? Continue to enrich profile Continue to enrich profile
  • 11. Journey to Advance Marketing Analytics- Solution Architecture Customer Service Data Demographic data Customer interaction Campaign Data Sales Force Trouble Ticket data Billing data Orders data Contact data Contract Data Product Quall Data Survey Social Media Web Activity Chat /email interactions Voice Call Recordings Textual Correspondence R D B M S Semi Structured Data Unstructured Data HDFS Data lake Machine Learning Data Ingestion Data Access Data Validation Application layer 360 Degree Customer profile Real Time/Stream ing Data Real Time/Stream ing Data
  • 12. Reference Deployment Architecture Ad hoc/on Demand Source Streaming Source Batch source Reference Data Spark Stream Processing Data Pipe Line Long term Data Warehouse Advance Analytics Operational Reporting Data Discovery Business intelligence Machine Learning(Spark ML) Data Sources Data AccessData Processing, Storage & Analytics