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May 5, 2017

Enriched customer profiling yields more accurately targeted offers leading to improvement in uptake rate and campaign effectiveness producing increased revenues.

Big data analytics are increasingly being used in the banking and financial services industry to better target customers and prospects with ever more relevant offers. Banks can use a big data analytics system to help:

• Increase customer value growth with targeted offers
• Improve lift on campaign effectiveness
• Insights to rationalize product portfolio based on performance
• Programmatic marketing with persona linked & real time contextual offers/NBO*


Banks rely on trial and error or piecemeal campaigns to solicit customers for additional share of wallet. Customers may or may not open, read, or accept / reject offers based mostly on the chance of the offer aligning with their current needs.


Investing in a customer analytics enables the bank to start aligning offers to customers at relevant times with existing data, and is designed to grow as data matures. For example, a bank can analyze recent transactional data to identify potential customer needs and design offers based on customer profiles. As digital personas are created and new data sources are incorporated (like IoT beacons / geo-location), banks can begin developing a mutually beneficial partner ecosystem that yields new revenue streams.

Why The Time is Right?

Powerful forces are reshaping the banking industry. Customer expectations, technological capabilities, regulatory requirements, demographics and economics are creating an imperative to change. When every aspect of banking can be done digitally, competitive reach is no longer defined by a physical footprint. Technology, regulatory requirements, and marketing budgets will become the driving forces of growth and reputation. New non-traditional entrants will fragment the competitive landscape further making branding and marketing even more important than ever before. Banks and credit unions need to get ahead of these challenges to stay relevant and be successful.

Designing Marketing Campaigns with Data Insights using Existing Data

Start with what you have. Oftentimes this is customer profile data, product data, transaction and interaction data. A platform that ingests data from myriad sources including internal and external data allows for endless growth opportunities as data and experience matures.

Step One: Aggregate customer profile information across the organization such as satisfaction, experience and credit scores, lifetime value or churn propensity, demographics, channel preference, and portfolio of products owned into a centralized view of the customer.

  • This has the added benefit of creating a 360 view of the customer facilitating improved service delivery and customer experience and optimized operations.
  • The result: Improved personalization and targeting.

Step Two: Tap into recent transaction data to identify spending patterns and product / brand affinities.

  • Use this information to better understand your customers and their needs, and to develop digital personas. The result: Improved understanding of customer population at a more granular level.

Step Three: Conduct Product Whitespace and Affinity analyses to identify top products in alignment to customer needs.

  • Coupled with strategic initiatives a highly targeted marketing campaign is created, launched on preferred customer channel, evaluated for effectiveness, and modified on-the-fly as needed.
  • The result: Increase in campaign efficiency and measurable ROMI. Tests have shown a 54% increase in acceptance rates over previous campaigns.

Step Four: Evaluate campaigns for additional customer insights which can be factored in to personas, segmentation, strategic initiatives, or creative messaging.

  • Insight into factual results of a marketing campaign provides a strategic edge over banks relying on piecemeal information and ‘gut instinct.’

As data matures and new data becomes accessible, it can be incorporated into the existing models and expanded into other areas of the organization such as operations for optimization. For example, incorporating interaction data may enable the contact center to better address customer concerns and inquiries or more efficiently resolve issues. Tapping in to the world of IoT or geo-location opens up oceans of possibility in developing a partner network or ecosystem to generate new revenue streams.

Suzanne is a Product Consultant for Customer Intelligence & Insights at TCS Digital Software & Solutions Group. She has 15 years of experience consulting on performance, management, and technology with several companies across the main industry verticals (finance, healthcare, telco, retail, travel / transportation, hospitality / entertainment) and enjoys helping clients realize quantifiable ROI as a result of her projects. With the digital disruption shaking all industries, she sees great opportunities for technology investment to yield solid ROIs while improving both the customer and employee experiences and optimizing operations. Prior to joining TCS Suzanne worked for customer analytics software companies, a performance management consulting group, in executive management at two small businesses, and a nonprofit. She has her Master's Degree from Northwestern University where her studies focused on Integrated Marketing Communications & Business, and undergraduate degrees from University of Dayton in Marketing, Management, International Business, and German.


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