Banking & Financial Services

Platinumetrix helps Banking and Financial institutions optimize their processes, maximize revenues and run their business in a smarter way, through its tailor made object oriented Customer and Marketing Analytics solutions catering to specific business needs

Customer Acquisition and Onboarding

Prospect Selection
Use historical response to identify the key attributes driving the most likely as well as the most profitable prospects who can be brought in the book.
Need Identification
Reach out to the customers with the right set of products and services using existing customer behavior attributes, and look alike segmentation approach.
Targeting and Cost Management
Optimize acquisition cost with the right targeting strategies using the right mix of marketing campaigns and channels.

Customer Management

Segmentation and Profiling
Segment customers into homogeneous groups with similar behavioral patterns to understand which part of the value chain they belong to and adequately address their needs.
Customer Profitability - Cross Sell/Up Sell
It is necessary to engage customers in using more products and services, thereby enhancing relationship and increasing profitability. A data driven cross sell strategy using behavioral propensity models typically serve best in getting the right strategy in place.
Customer Experience - Next Best Offer/Market Basket Analysis
Use statistical methodologies to identify which offer is the customer most likely to accept and device your sales strategy in accordance. This approach of being customer centric rather than product centric helps not only improve customer experience, but also increase customer profitability.

Customer Retention and Loyalty

Customer engagement - Share of Wallet Analysis
Helps understand customer worth with the bank as a percentage of the total customer worth across all other banks for a given portfolio, or for all relationships taken together. Typically survey or bureau data is used combined with statistical methods to assess the same. We also help you devise data driven strategies to increase SOW.
Customer stickiness - Life time Value
Assess the net value the customer is likely to generate over the course of his tenure with the bank across all portfolios. The key to finding LTV is to clearly assess the need for customer retention, and total worth of relationship that could potentially be lost in the case of an attrition. Helps bank segment high net worth customers, and strategize accordingly
Customer Experience - Next Best Offer/Market Basket Analysis
Use statistical methodologies to identify which offer is the customer most likely to accept and device your sales strategy in accordance. This approach of being customer centric rather than product centric helps not only improve customer experience, but also increase customer profitability.
Customer Churn - Attrition and Retention Analysis
One of the key areas of concern across all banks is customer retention. Our solutions help you understand the key factors behind customer attrition, and predicts the likelihood of churn in advance giving you an opportunity to take proactive measures. We help you build an anti-attrition framework which not only combats attrition but also helps you with the most effective strategy to retain customers.

Market Measurements

Pricing Strategies/Price Elasticity Models
A combination of statistical methods to analyze and assess the optimal pricing for banking products. An effective strategy is imperative to customer loyalty.
Sales drivers and Profitability Analysis
Understand the key attributes that drive sales and help increase customer profitability.
Channel Analytics
It is imperative to understand customer channel preference and optimize channel costs with the right multi channel mix approach in reaching out to customers at every stage of life cycle. Channel preference overlaid against response rate and channel costs together combine to generate the most effective strategy.

Campaign Analytics

Historical Response Based Analysis
Campaign response models are key to any direct-to-customer marketing campaign. Statistical Techniques used to predict most likely responders using historical data.
Campaign Management - Tracking and Monitoring
Fully automated end-to-end campaign tracking application.
Marketing Spends Allocation and ROI optimization
Analyze Marketing Spends/Marketing investment vs returns for mass marketing channels, and assessment of performance of channel parameter, effect of seasonality and base sales on incremental spends. using Marketing Mix

Social Media Analytics

Natural Language Processing
Means to convert unstructured noisy text from the social media into structured data for analysis
Knowledge Discovery
Analysis of data extracted from Social Media platforms to evaluate customer sentiment towards products or brands. Profiling and Segmentation, event trigger based analysis on customers.
Big Data Framework
Capability to handle large and dynamic datasets generated across the Social Media using the most advanced Big Data Analytics tools and technologies.
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