LDB Group: Using leading-edge text analytics to reveal customer insights that generate real business benefits
Company Size
200-1,000
Country
- Worldwide
Product
- IBM SPSS Modeler Premium
- IBM SPSS Statistics
Tech Stack
- Text Analytics
- Data Analysis
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Revenue Growth
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Automotive
- Consumer Goods
Applicable Functions
- Business Operation
- Sales & Marketing
Services
- Data Science Services
About The Customer
LDB Group is a company that specializes in helping its clients to better understand their customers’ needs and desires. The company serves businesses of all sizes and industries, with a focus on investigating customer experiences and identifying areas for improvement. LDB Group employs around 500 people at locations across the world. One of its key offerings is investigating customer experiences, and identifying areas for improvement. The company serves a wide range of industries, including the automotive industry.
The Challenge
LDB Group specializes in helping its clients understand their customers’ needs and desires. One of its key offerings is investigating customer experiences and identifying areas for improvement. When a client from the automotive industry asked LDB Group to study customer satisfaction, the firm saw huge potential in offering similar services to more clients. However, the challenge was to scale processes to handle information more efficiently. The company realized that if it launched customer satisfaction surveys as a new analytics service, it could provide additional value to its existing clients and present a more valuable offering to attract new business.
The Solution
LDB Group decided to deploy IBM® SPSS® Modeler Premium, a powerful analytics platform featuring state-of-the-art text mining capabilities. When an automotive workshop customer participates in a satisfaction survey, the results are automatically sent to the IBM solution. The software then analyzes the feedback to understand why the customer was happy or unhappy with the service they received. Most importantly, it enables LDB Group to pinpoint any opportunities for enhancement. LDB Group is also using IBM SPSS Statistics analytics software to delve even deeper into the survey feedback by performing cluster analyses to understand how the different parts of the customer experience relate to each other.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
.png)
Case Study
Improving Vending Machine Profitability with the Internet of Things (IoT)
The vending industry is undergoing a sea change, taking advantage of new technologies to go beyond just delivering snacks to creating a new retail location. Intelligent vending machines can be found in many public locations as well as company facilities, selling different types of goods and services, including even computer accessories, gold bars, tickets, and office supplies. With increasing sophistication, they may also provide time- and location-based data pertaining to sales, inventory, and customer preferences. But at the end of the day, vending machine operators know greater profitability is driven by higher sales and lower operating costs.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
