FischerJordan Case Studies

Our Case Studies feature FischerJordan clients’ successes through the filter of our 4-step process.  See how our proprietary approach consistently solves problems for the companies we work with.



Leveraging cross-functional performance data to optimize marketing investment portfolio

Business leaders at a Fortune 500 Financial Services firm wanted to quantify the value generated by their marketing investments.  A multitude of customer interactions across products and marketing channels complicated the problem. Solving it required combining data across a variety of databases and functional areas into a holistic view of customer experience and performance.


Enhancing margins and growth by optimizing operations utilization and impact

A leading US health services firm was facing pressure to close a P&L gap by significantly reducing in-year expenditures. Their leaders’ goal was to reduce costs while minimizing any adverse business impact.  By combining customer service utilization and outcomes data with financial databases, they identified multiple levers for reducing expenses while minimizing impact on client service levels, growth potential, and strategic flexibility.


A Data-Driven Approach to Fine Tuning Product & Pricing Strategy

A leading US financial services firm sought to validate their hypotheses regarding their competitive advantages and disadvantages in each of three markets. An analysis of the major competitors in each space allowed them to prepare and refine a data-driven strategy to expand their market share.


What Does Your Real Sales Cycle Look Like?

Executives at a leading US healthcare provider faced unexpected shortfalls and volatility in revenue, in addition to inconsistent forecasting. Sales pipeline metrics indicated a level of robust activity at logical odds with the decline in sales revenue. Examining their sales pipeline in greater detail helped them to understand revenue variations and eventually enabled better forecasting and investment allocation.


How to Size a Market Using Publicly Available Information

Companies of all sizes and within all industries face a common strategic challenge of understanding their markets and competition better. Leaders at a credit card information system provider wanted to explore growth opportunities within their existing client base. A dearth of existing market studies complicated the problem. Solving it required combining and validating data from an array of public sources.



Driving Revenue Growth by Identifying Untapped Cross-Sell Opportunities

Post-merger, executives at a leading US healthcare firm faced operational, profitability and scalability problems in their sales. Analyzing the bottlenecks in sales pipeline provided insight to an untapped incremental revenue opportunity. Identification of sequential cross-sell opportunities and bundling helped increase client revenue and build customer equity.


A Top Down Approach to Minimizing Revenue Leakage

Executives at a leading US financial services firm had anecdotal evidence that they were not realizing the full contractual revenue on many transactions they fulfilled. Identification of the primary causes of revenue leakage not only helped increase revenue realized but also prevent future leakage.


Managing Business Performance through Driver-based Analysis and Dashboarding

Executives at a leading healthcare firm needed to understand the profitability drivers of their business and optimize them across customer and product segment.  Understanding the value generated by each dollar of opex spent, and developing an interactive P&L to help manage them on an ongoing basis, allowed them to convert their opex base into an asset with continuously improving top-line and bottom-line returns.


Using Customer Data to Develop Models for Long-Term Profitability

Marketing executives at a top US credit card issuer were interested in cross-selling more business products to their >20mm consumer card holders.  Based on their research, their penetration rate was at less than 25% of its potential.  By employing customer-level analytics across marketing channels, products, and segments, and combining these with a real-time investment optimization engine, we were able to help them drive a 40% lift in customer NPV, $1B in incremental card spending, and a 5% lift in new customers acquired. 


Consolidation of Multiple Public Data Sources Through Advanced Soft-Matching Techniques

Soft matching algorithms within Excel, R, and Python are convenient but lack contextual relevance when matching business names and entities. We developed an Excel-based soft-matching algorithm optimized for combining multiple business databases into a “single source of truth.” The algorithm is being used to continuously update client CRM databases with the latest publicly available information about their customers.


Leveraging Customer Relationship Data to Quantify Price Elasticity

Leaders at a US based financial services firm wanted to increase prices for one of their lending products. Given the aggressive competition in the market, they were reluctant to go for a blanket increase. Hence, they wanted to determine how they might leverage their customer relationship data to implement a differentiated pricing model. Identifying price insensitive segments allowed them to achieve their financial goals without incurring incremental attrition.


Projecting Business Volumes & Revenues Using Macroeconomic Data

Finance executives at a leading US card issuer sought to gain confidence in their financial projections by understanding their dependencies on underlying macroeconomic drivers. By leveraging a range of verified data sources and proprietary indicators, a model was developed to project volumes and revenues for each of their main products, each based upon market specific macroeconomic indicators, with average quarterly errors of less than 10% over 5 years.






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