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Customer Lifetime Value

Analytics can assess the purchasing behavior and customer needs. The insights gained can help a business drive actions at various stages of the customer lifecycle to improve the CLV.

 Customer Lifetime Value

It is a prediction of the total (business) value generated by a customer across the customer lifecycle.

Analytics can assess the purchasing behavior and customer needs. The insights gained can help a business drive actions at various stages of the customer lifecycle to improve the CLV.

Prospecting to the right target audience to optimize customer acquisition cost

Analytics-driven practices to help a Business boost its CLV during its engagement with the customers

Customer Retention

Prospecting to the right target audience to optimize customer acquisition cost
  • Lookalike modelling, a statistical analysis to help with Customer Acquisition
  • Finding prospects from online and offline data sources based on insights gained from Lookalike modelling
  • Choosing the right target audience for custom made marketing campaigns
Analytics-driven practices to help a Business boost its CLV during its engagement with the customers
Customer Segmentation

  1. Leveraging analytical data based on behavioral traits and demographics
  2. Create promotional plans, arrive at new pricing initiatives etc.that suit each segment
  3. Improve sales and profit in each segment leading to overall profitability

Cross-Selling

  1. Bundling complementary or related products to generate higher sales
  2. Collaborative filtering to enable cross-selling
  3. An approach to enrich the customer experience

Survey Analytics

  1. Gauge the usage of products or services among the consumers
  2. Customize marketing messages based on analytics
  3. Update usability of products
Customer Retention
  • Predictive analytics to prevent customer churn
  • Derive insights to earn customer loyalty
  • Make personalized offers to revive engagement with dormant customers