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Data Analytics: Case Studies of Success

Data Analytics Excellence

Data Analytics: Case Studies of Success

by Barton Goldenberg

Today there are more than 11 billion connected devices producing more than 8 zetabytes of data per year. In the next five years, the number of connected devices will increase eightfold, while the amount of data they produce will increase a staggering 22 times. This trend will only accelerate over time. Organizations that expect to thrive in the future must learn how to drink from this digital firehose. Robust, up-to-date data analytics capabilities will be key to their ability to do so.

In recent years, ISM has participated with a variety of world-class B2B and B2C companies on a diverse range of customer intelligence and data analytic projects. Here’s how we’ve helped three global companies put data analytics to work:

Case Study #1: Automotive Sales & Marketing Effectiveness

Every automotive company is challenged by how best to spend their sales and marketing dollars, and how to determine the impact of this spend.  Using standard tools found in most data analytics software packages, Automotive Company X examines baseline sales trends, analyzes repeat buying trends and model preferences, does cross-brand purchase analysis including model preferences, builds repeat-buyer look-alike models, and performs campaign-conversion predictive modeling.

The output of this analysis allows the company to know which existing and competitive customers to target for their cars, which car models to promote to each customer, what channels are best for reaching each customer, and what ‘contextually relevant’ messages will best resonate with each customer.  Using closed-loop measurement tools, they can assess the sales and revenue impact of their marketing investments, and show how their data analytics program has driven dramatically higher car sales.

Case Study #2: Selection of Partners for a New Financial Product

Financial Company Y wanted to launch a new line of mutual funds to complement its existing annuity products.  They sell their products through more than 30,000 independent financial advisors.  Their challenge was to determine which financial advisors would be best able to launch the new product line, and why.  To identify the advisors with the highest probability of cross-selling mutual funds, Company Y created two analytical models.  One model provided a predictive score to suggest the advisors with the highest potential. The second model predicted total mutual fund sales for each suggested advisor.

The results of this exercise have been impressive. The company was able to select an optimized group of financial advisors, the launch of their new mutual fund product line was completed in record time, and it produced strong financial results.

Case Study #3: Consumer Segmentation & Customer Journey Mapping

Consumer Company Z offered a program where they train people who sign up, pay a membership fee, and get certified.  They had two challenges: grow sales, and address the high level of churn among members.  To overcome these challenges, Company Z concluded they need better segmentation with personas, and a deeper understanding of their customer journeys by segment.

The goal of a journey map is to focus resources on the touch points having the biggest impact on satisfaction across the customer lifecycle, including both ‘moments of truth’ and risk factors.  Using data modeling, the company integrated customer-profile and transactional data with 3rd party lifestyle data, to build a predictive model that included a scoring algorithm to guide appropriate activities for their new segments.  The insights and results produced to date have been amazing.

The number of available data analytics technologies and the opportunities they present have never been greater. These include segmentation, acquisition modeling, lead scoring, cross-sell/upsell, next best offer, retention modeling, response modeling, look-alike modeling, CLV modeling, and many more. All are opportunities that your company at least should be aware of, if not actively pursuing.  If your goal is to thrive in today’s digital deluge, ISM will be happy to help you evaluate your current data analytics capabilities, and assist with implementing new ways to achieve data analytics excellence.


For more than 30 years, ISM has worked closely with world-class B2B and B2C companies like Jaguar Land Rover, Zumba, Kraft Foods, and Pacific Life on data analytics and customer intelligence projects. Our offering covers the spectrum – from data strategy and management to sales, customer-service and marketing programs that leverage historical, real-time, and predictive analytics and modeling for both structured and unstructured data.

We work with our clients to first identify and acquire the right data sets. From there, we determine the right analytic approach to develop new ways to explore and exchange data, drive better insights, increase business revenue, and create happier, more loyal customers. If you have yet to make data analytics part of your company’s DNA or wish to enhance the analytical capabilities you already have, we would welcome the opportunity to assist.

Barton Goldenberg speaks about changes and trends in the ways organizations engage with today’s connected consumer. His real-world examples and humorous style have distinguished him at events including the Gartner 360 Customer Summit, Dreamforce, CRM Evolution and others.

Barton is founder and President of ISM Inc., where clients include Chase Bank, ExxonMobil, Jaguar Land Rover, Johnson Controls, Kraft Heinz, Marriott, Nike, Schlumberger, T. Rowe Price, U.S. Department of Defense, Zumba Fitness and many more.

An acclaimed author, keynote speaker, and member of the CRM Hall of Fame, Barton holds a B.Sc. (Economics) degree with honors from the Wharton School of Business and a M.Sc. (Economics) degree from the London School of Economics.on, always-connected’ consumer.

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