Longstreet Solutions

Longstreet Solutions started building front-end loyalty solutions for the restaurant, eCommerce, and retail industries. Longstreet Solutions’ passion to bridge marketing and data led the Company to develop innovative, data-driven solutions for marketers and businesses alike. The Company’s goal was to use technology to understand who customers are, how they behave, and when to send relevant, targeted messages at the precise time. Ultimately, Longstreet Solutions aimed to improve marketing campaign effectiveness and drive an increase in revenue for its customers.

“Our focus is to improve and expand our Big Data and marketing automation services. The role Cloudreach plays in providing and maintaining our core technologies will be vital to our ability to execute.”

Daniel Waltzer CEO, Longstreet Solutions

Summary

Longstreet Solutions shifted focus over three to four years to analyze customer data and automate processes. Daniel Waltzer, Chief Executive Officer at Longstreet Solutions, knew that Big Data would lead to better decision-making but encountered challenges with making sense of how to tackle Big Data. The Company hoped to solve the issues of quickly storing, querying, and securing data as well as improving the reliability of mission- critical programs and applications.

 

The Situation

Waltzer knew that Big Data was so much more than a trendy industry buzzword. At the time, there was not much public application of Big Data in the restaurant and retail industries. However, Waltzer knew that the retail and restaurant industries generate a wealth of data, making the business case for using data analytics clear.

The Solution

Big Data technologies in AWS enabled Longstreet to harness the power of data and deliver intelligent marketing. Waltzer commented, “Cloudreach presented AWS Big Data solutions which enabled us to develop strategy and move to using buying patterns, closed loop reporting, and persona profiling to make marketing more effective.”

Cloudreach recommended Amazon EC2, S3, DyanmoDB, Redshift, and Datapipeline. Cloudreach was able to create predictive data, targeted analytics, and detailed customer segments using rapid queries to determine the right time to send relevant, targeted promotions to customers.

Portfolio Scoring

To predict the claims associated with a portfolio of mortgages, the data file is dropped into an S3 bucket. EMR is used to scrub the data, identify features and append geography and peril attributes. The prediction models are applied to predict claims and recovery for the properties contained in the portfolio. The results are aggregated using EMR to provide a final report for the client investor.

 

The Benefit

Longstreet Solutions delivered concrete ROI for its customers using AWS Big Data solutions. According to Waltzer, “Cloudreach and Big Data in AWS helped us recapture 40% of lapsed customers, increase customer response rates to 50-200% above industry averages, and deliver concrete ROI for clients.”

Longstreet found that AWS Big Data technologies also created ancillary benefits, including comprehensive views of business operations, delivery process and order fulfillment, and the ability to predict responses and adjust costs at a moments notice.

Longstreet Solutions needed technology that can deliver and improve results.

 

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