Marketing Analytics

Marketing Analytics

Client Details

Client is a financial services giant headquartered in New York

Challenges Addressed

Identify users who are likely to make a purchase in the future by modeling online user behavior

  • Email campaigns
  • Website visits
  • Form submissions & Referral traffic

Highlights of Engagement

  • Identifying customer segments by implementing K-means clustering algorithm
  • Feature engineering based on segments – derived temporal and spatial features
  • Predicting likelihood of purchase / conversion for each segment of customers – derived the likelihood using Random forest mode with 90% recall and precision

Benefits to client

  • Market Segmentation and targeted spend of Marketing $
  • Improved credit card transactions due to micro targeted offers
  • Targeted promotions and offers based on spending behavior
  •  Reports on Top merchants / Top Industry spends

QUOTE TO CASH

VIRTUAL CONFERENCE

6 April 2020 | 11:00 AM PST

Join the Standav Team & Frank Sohn from Novus CPQ, with Special Guests from Bayer, Box, Extreme Networks, Miro, Mobileiron, and Ross Video as we discuss CPQ, Billing, and Pricing Solutions for the Enterprise.

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