Case Studies - Rezilyens, LLC

Case Studies

Improve Conversion Process: 

Implemented an analytics solution for a retail client to track leads through the entire sales conversion process, from a click on an ad word to the final transaction, in order to uncover insights on how the conversion process can be improved. 

Identify Customer Values: 

Enabled telecom client leveraging multiple indicators, such as billing and sentiment analysis, in order to identify customers that can be upgraded to higher quality products, as well as to identify those with a high lifetime customer-value, so its team can focus on retaining those customers. 

Big Data Analytics 

Optimize Funnel Conversion

Improve Customer Retention:

Implemented a big data solution for a communications client in order to improve customer retention and boost its market share by improving the marketing campaign process. The company used real-time data to create a personalized campaign for each customer based on which products or offers the customer would most want or need.

Predict Consumer Buying Behavior:

Leveraged predictive analytics to predict which financial products or services a customer would appreciate, so it can better target consumers during the sales process. With these insights, the bank increased average revenue by 22 percent and reduced costs by 9 percent.

Big Data Analytics 

Optimize Funnel Conversion

Consumer Behavior:

With 1.8 billion customers, our financial services client is in the unique position of being able to analyze the behavior of customers in not only their own stores, but also thousands of other retailers. The company teamed up with us to collect and analyze data on shoppers’ behavior, and provide the insights it finds to other retailers in

Customer Feedback Loop:

To better keep track of customer sentiment and what is being said about the company online, our client created a listening system for all of the conversations about the company and its products on social media. The company will actively engage with those that post about them online in order to mitigate damage and build customer loyalty.

Analytics 

Behavioral

Customer Segmentation:

With services like Hulu and Netflix competing for viewers’ attention, our telecommunications collects data on how frequently customers tune in, the effect of bandwidth on consumer behavior, customer engagement and peak usage times in order to improve their service and increase profits. The company also segments its customers for advertisers by correlating viewing habits with public data— such as voter registration information—in order to launch highly targeted campaigns to specific locations or demographics.

Analytics 

Behavioral

Customer Experience:

Our client tracks vast amounts of data in order to improve operations and boost the customer experience. The company looks at factors such as the design of the drive-thru, information provided on the menu, wait times, the size of orders and ordering patterns in order to optimize each restaurant to its particular market.

Personalization:

Our client collects data on its customers’ purchasing habits in order to send personalized ads and coupon offers to the consumers’ mobile phones. The company also identifies trends indicating whether customers are losing interest in their product and directs offers specifically to those customers in order to regenerate interest.

Analytics

Personalization

Customer Segmentation:

Thanks to its partnerships with the likes of Google, our client has access to vasts amounts of data about its customers that it uses to create real-time, personalized marketing messages. One project we did for our client utilized delivered real-time content to fans while they were watching a sponsored event.

Personalization:

Our music industry client uses data from user profiles and users’ playlists, and historical data on music played to provide recommendations for each user. By combining data from millions of users, we were able to make recommendations even if a particular user doesn’t have an extensive history with the site.

Analytics

Personalization

Safety:

Southwest analyses sensor data on their planes in order to identify patterns that indicate a potential malfunction or safety issue. This allows the airline to address potential problems and make necessary repairs without interrupting flights or putting passengers in danger.

Analytical Personalization:

Our retail client combines public data, social data and internal data to monitor what customers and friends of customers are saying about a particular product online. The retailer uses this data to send targeted messages about the product, and to share discount offers. Walmart also uses data analysis to identify the context of an online message, such as if a reference to “salt” is about the movie or the condiment.

Analytics

Predictive

Infrastructure Performance:

Our client provides big data analytics to its users, so they can monitor the performance of applications in real time, pinpoint problems with the infrastructure and optimize the
platform to correct performance issues.

Prioritization:

Our client uses real-time wire data analytics to detect problems in its applications and prioritize which issues should be addressed first. The company also uses big data to determine the impact of a particular market event, as well as its original cause.

Analytics

Predictive

Simulation:

Implemented simulation models and predictive analytics for our CPG client in order to create the best design for its products. It creates and sorts through thousands of iterations in order to develop the best design for its product, and uses predictive analytics to determine how moisture affects the molecules, so the right fragrance comes out at the right time in the manufacturing process

Revenue Optimization:

Our airline client seeks to expand globally, it uses big data to determine which destinations and connections should be added in order to maximize revenue.

Analytics

Optimization

Optimization:

Implemented an algorithm for a CPG client to ensure that its drinks has a consistent taste throughout the year. The algorithm incorporates satellite imagery, crop yields, consumer preferences and details about the flavors that make up a particular ingredient in order to determine how the juice should be blended.

Analytics

Optimization

Risk Management:

Our banking client analyzed criminal activities at ATMs to determine factors that increased the risk of becoming victimized. For instance, it discovered that proximity to highways, weather conditions and the season all affect the risk of a security threat.

Loss Prevention:

With massive items in its catalog, our e-retailer client has a lot of product to keep track of and protect. We leveraged a analytics solution to predict which items are most likely to be stolen, so it can better secure its warehouses.

Analytics

Security

Variance:

Implemented a data analytics solution for our banking client to detect anomalies across channels that indicate potential fraud. The fraud team receives data from several hundred sources—some in real-time—to monitor activity, such as if a customer makes a mobile banking transaction at the same time as a branch transaction.

Fraud Detection:

Implemented a big data analytics to identify fraudulent claims and possible fraudulent prescriptions. For instance, it can identify if a healthcare provider is charging for a more expensive procedure than was actually performed.

Analytics

Security

Internet of Operations:

Shell uses sensor data to map its oil and gas wells in order to increase output and boost the efficiency of its operations. The data received from the sensors is analyzed by artificial intelligence and rendered in 3D and 4D maps.

Internet of Equipment:

Sensors placed on John Deere equipment, along with historical and real-time data on soil conditions, the weather and crop features are all used together to help farmers determine where and when to plant to get the highest yield, and how to boost the efficiency of their work to reduce fuel costs.

Analytics

Internet of Things

Challenge:

With an exponential growth in their customer base, our airline client support team was burdened with increasing volume of work. The challenge faced by Rezilyens was to
deliver a customized solution for the client in a short timeframe, which would seamlessly integrate with the client's existing IT infrastructure.

Rezilyens Touch:

Rezilyens adopted a well-planned phased approach to smoothly transition the IT Infrastructure management operations to the remote location at Rezilyens's offshore center. Rezilyens established multiple support teams that provided a wide array of IT support services to the client. By working in overlapping shifts, Rezilyen’s support teams were able to provide real-time, 24x7 support to address any issues raised from the client side.

RIM

Outcome:

The 24/7 support model resulted in uninterrupted services to the client and their end customers, improving the client's business credibility. By outsourcing the IT infrastructure support & management operations to Rezilyens, the client was able to focus on its core operations and generate more business.

Challenge:

Revenues at our manufacturing client were growing multifold and workforce strength tripled during a span of 4 years. The cost of servicing the IT needs of so many more employees worried the customer. IT helpdesk team was spread across multiple locations around the globe

Rezilyens Touch:

Rezilyens centralized the clients remote infrastructure management team at its offshore center in addition to some onsite support; established standardized processes for the client across multiple locations. This was followed by an effective leverage of automation, mechanisms and governance to measure SLA’s and the stated objectives of the engagement. Six Sigma and other continuous improvement processes was established to provide the necessary predictability and sustainability.

IT Services Desk

Outcome:

Centralization and standardization of remote infrastructure management helped reduce costs by about 18% for the client while simultaneously improving service levels.

Challenge:

Our client wanted to beef up security support due the ongoing threat of cybersecurity. The challenge was beyond cost and required ‘active defense’ processes, talent and technology.

Rezilyens Touch:

Rezilyens brought top tier security talent, processes and technology to the engagement. The goal was to look at the problem holistically from a people, process and technology
applying best practices and tailoring them to client at every level. Further, time was a critical so an aggressive ramp up and transition was required. A new shared services model
was integrated seamlessly within the customer.

Security Services

Outcome:

The engagement achieved its goals ahead of expectations. The key here was to integrate state-of-theart processes and technology in relatively short order in addition to a long-term view of bringing the overall TCO to manageable levels

Challenge:

Manage and operate the complete multi-technology and platform portfolio of databases for the North America operations of High Tech client; handling structured data in excess of 150 Terabytes. The goal is to significantly reduce TCO.

Rezilyens Touch:

Designed, developed, re-engineered and supported the migration of all mainframe to Oracle DB resulting in a ‘run’ cost saving of about 33% against the existing budget.

Infrastructure Support

Outcome:

24/7 production support and maintenance of databases enabling significant ticket reduction, performance tuning, zero down time and reduction of TCO.

Challenge:

Our retail client was facing a all-time low customer satisfaction rating. Incidents were often not reported lack of confidence in the IT service desk. Not all reported incidents handled diligently leading to diverse impact to business operations. The incident tracking system was inefficient resulting in improper escalations and backlog. Impaired communication between the existing outsourced IT service desk team and the client.

Rezilyens Touch:

Rezilyens conducted an in-depth ITSM assessment and identified the pitfalls. Utilizing an SLA-driven and six sigma based approach, a new service desk model was setup with experienced and service driven staff that provided round the clock coverage across time zones. KPIs were identified, metrics collection was set-up to monitor the SLAs and delivery efficiency.

IT Service Desk

Outcome:

Average First Contact Resolution Time reduced to 8 minutes from an average of 43 minutes.
Second level resolution came down to 2.5 days from an average of 9 days.
Unique Route Ratio increased from 5 to 12.
Cost savings by 25%
Customers ranking to our client #1

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