Tag: vendor analysis

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Improving Service Quality Through Customer Analytics for a Leading Airline Company

Quantzig’s recent study on customer analytics for a leading airline company provides insights on competitive benchmarking, improving service quality, and devising customer retention strategies to ensure higher customer loyalty.

Importance of customer analytics in the airline industry

Customer analytics entails techniques such as data visualization, predictive analytics, information segmentation, and management. Customer analytics usually refers to the processes and tools that offer organizations relevant, timely, and accurate consumer insights that help them to devise effective marketing strategies. Every organization, irrespective of the industry that it operates in, has laid great emphasis on building long term relations with the customer and enhancing the consumer experience. Customer analytics assists businesses to analyze customer life cycle and gain detailed insights into their preferences and industry trends. In the airline industry, companies have faced low customer loyalty as they regularly change their airline preference. The high customer attrition levels can be attributed to factors such as an increase in ticket fares, low service quality and delivery standards among several others, thereby having a major impact on the success of the airline industry.

Quantzig’s team of expert analysts assist organizations by providing in-depth insights based on customer feedback on service quality. We help the company to identify the service quality gaps and redesign marketing strategies to build customer loyalty. Our analytics team helped the client develop a model for targeting customers and revamp the customer retention strategies by leveraging the insights obtained from various sources such as sales and account data, customer feedback, and revenue statements.

Robotic process automation enhances customer experience

Robotic process automation (RPA) helps organizations to achieve standardized service delivery levels. The RPA tools and software’s perform routine processes and lend a human touch while interacting with the customer, thereby enhancing user experience. Through RPA, businesses can automate the complete process of onboarding customers with limited human involvement. Companies can drive profitability and customer experience by integrating RPA technologies within its business processes.

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Outcomes and solutions offered

Quantzig’s customer analytics study on enhancing the service quality for the airline industry delivers incremental value to the client based on customer feedback, thereby re-designing customer retention and marketing strategies.  Some of the solutions offered are as follows:

  • Identified key factors that drive customer loyalty and devised new strategies to attract customers
  • Developed a robust customer targeting model by analyzing customer preferences and identifying areas of improvement
  • Helped increase flexibility and customer responsiveness to improve service quality levels

The complete case study on Customer Analytics Helps a Leading Airline Company is now available.

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Leveraging Big Data Analytics to Optimize Route Planning and Assist in Traffic Network Congestion

Quantzig’s current big data analytics assessment on transport network congestion examines the transport demand and supply to optimize routes, reduce costs, and develop network optimization solutions.

Big data analytics in traffic management

The higher risk of passenger safety, loss of productivity, increase in fuel consumption, and pollution is all effects of urban traffic congestion. Efficient traffic management will reduce congestion, improve performance measurements for seamless traffic flow, and proficiently manage current roadway assets. Government organizations and administrative authorities are implementing coordinated traffic signals and variable messages to manage traffic network congestion. By implementing big data solutions, administrators can leverage historical trends, a combination of real-time information, and new-age algorithms to improve and traffic networks in urban areas. The growing focus on the development of intelligent network systems and use of big data analytics will assist the traffic management and result in reduced congestions and roadblocks. The big data analytics by Quantzig helps service providers in the mobile services industry to analyze the efficiency of the current transportation system, estimate the transport models, and predict future network scenarios.

The adoption of advanced sensors and GPS signal systems is revolutionizing the urban traffic network. These systems are designed to help reduce network congestion and act as alerts that notify traffic authorities of potential roadblocks and how to avoid them. The sensors are installed in trucks, ships, and airplanes that give real-time insights into the driver’s capabilities and the traffic. GPS signals are utilized for bottlenecks and predict the condition of the transportation network.

Emergence of smart vehicles

The advent of smart vehicles will help reduce the network congestion across several cities in the world. These are connected vehicles that provide a real-time estimation of traffic patterns and help authorities with the deployment of management strategies. These systems are designed to improve the communication vehicle-to-infrastructure (V2X) communications and monitor the traffic network to reduce collisions and accidents. Additionally, the implementation of speed trackers, traffic sensors, and display boards will result in smarter roads and help control speed and traffic issues efficiently.

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Telematics solutions

Telematics is extensively used in traffic management to provide statistics and information data such as weather conditions, traffic conditions, and navigation systems. These systems provide real-time information and authorities leverage predictive analysis to determine the state of the transportation network. Moreover, telematics provides speech-based internet access to the consumers through wireless links that monitor the driver’s state and stress levels and send alerts to systems if there is any issue to avoid or reduce chances of collision.

Outcomes and solutions offered

Quantzig’s big data analytics assessment on traffic network congestion identifies a set of transport indicators that are measured using the mobile phone data available to travel agencies to optimize route planning.  Some of the solutions offered are as follows:

  • Developed an integrated platform to perform data analysis in a scheduled, easy, and controlled way using a user-friendly interface
  • Offered an exhaustive understanding of how traffic demand is distributed in the transportation network and how it varies over time
  • Enlisted the different types of bottleneck of the transportation network and enabled enhanced route planning
  • Evaluated the travel delay due to congestion based on travel time distribution between peak and non-peak periods
  • Provided a comprehensive analysis of total number of trips made to and from each zone based on day, time, month, and holiday

The complete case study that states big data analytics reduces transport network congestion is now available.

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Leading CPG Manufacturer Achieved a 22% Increase in Conversions Using Big Data Analytics

Quantzig’s recent study on sales force effectiveness for a leading CPG manufacturer guarantees a double-digit increase in conversion rate and improves sales performance using big data analytics.

Big data and its effectiveness in the retail industry

Big data analytics help retailers make informed business decisions and effectively manage the sales force. These solutions help companies to manage the issue of the seasonality of the products and the demand for inbound shipments. Data analytics help CPG companies improve their network coverage strategy and ensure maximum reach and acceptance at minimum cost levels. The data collected analyze the potential of the sales force, build achievable territories, identify weaknesses, and set expectations. Big data analytics help retailers manage multiple sales channels and guarantee that their sales forces are well positioned to succeed by using data efficiently. The big data analytics solutions by Quantzig helps retailers manage their sales force and minimize time and cost of territory coverage. The study also develops strategies that help companies maximize sales force coverage to improve sales performance and long-term profitability.

Workforce optimization is the biggest challenge faced by several leading retailers in the market. Big data tools offer tactics that optimize marketing and merchandising process, thereby increasing the productivity of the sales force. These data tools are used to analyze the predicting trends, forecasting demand, and optimizing pricing policies. Moreover, the analytics streamlines data in an effective way that results in efficient decision making and changing operations to match the dynamic changes in the market.

Customer analytics

The biggest advantage of using big data in the retail sector is identifying and profiling potential customers. These solutions help organizations evaluate their customers’ interests, requirements, preferences, and spending capacity. This information is leveraged while designing sales and advertising campaigns resulting in the motivated sales force. Moreover, sales force uses this information to provide personalized services, offer exclusive and customized product offerings, and discounts, thereby increasing the brand loyalty and retention rate.

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Boosting social listening capabilities

Big data analytics facilitates the management and analysis of large amounts of unstructured data collated from social media channels such as Facebook, Instagram, Twitter, and LinkedIn. Social listening is essential to improve customer interactions, brand loyalty, boost revenue, and profit margins. This solution analyzes data from tools such as natural language processing (NLP) to understand the buying preference of the end-user. Additionally, companies can use this data to train a sales force to understand the target audience and boost the sales revenue.

Outcomes and solutions offered

The sales force optimization assessment for leading CPG manufacturer integrates multisource data to facilitate end-to-end visibility on each sales person’s journey. Some of the solutions offered are as follows:

  • Developed dashboard for real-time updates and insights on salesperson performance, operational metrics, target and achievement details, and new prospects
  • Delivered comprehensive information on a new number and location of cities to maximize territory potential and optimize transpiration costs
  • Resulted in around 11% reduction in miles per sales person
  • Provided insights on potential opportunities for territory optimization across all divisions and effectively apply best practices
  • Projected centralization of network optimization effort across all the divisions of the company and reduce 17% of transportation costs

The complete case study on big data analytics that improves sales performance for a leading CPG manufacturer is now available.

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customer analytics in retail

Supply Chain Analytics – Efficient Inventory and Distribution Management for the Pharmaceutical Industry

Quantzig’s latest study on supply chain analytics for an established healthcare provider in the US provides strategies for cost optimization, better supply chain visibility, and efficient inventory and distribution management.

Supply chain analytics in the healthcare industry

The intense competition and stringent government regulations are encouraging healthcare and pharmaceutical companies to revamp their supply chain sector and increase operational efficiency. The continual efforts to update IT systems and network infrastructure will help enterprises in the industry to gain visibility into the inventory and distribution processes. By implementing supply chain analytics, pharma companies can identify opportunities to improve the efficiency of their operational and production systems. The optimization of their supply chain functions will enable them to manage market pressures pertaining to government involvement and FDA approvals. Supply chain analytics help organizations in the pharmaceutical and healthcare industry to monitor, measure, and improve individual business processes and overall performance of the operational cycle. The recent supply chain analytics assessment by Quantzig enables inventory optimization, inbound supply chain visibility for cost reduction, and improved supply chain planning. The study also provides valuable information on efficient inventory and distribution management, cost optimization, and better supply chain visibility.

Pharma companies are implementing supply chain analytics to increase their demand visibility and understand the customer preferences in the market. These solutions are designed to help enterprises optimize their sales and operations planning processes through demand forecasting metrics and KPIs. The data analytics solutions aim to improve the strategy, performance, management, and risk associated business decisions for organizations in the industry.

Increasing manufacturing efficiencies

The advent of automation and digitalization is boosting the requirement for manufacturing efficiencies. Effective management of filling, replenishing, loading, and troubleshooting processes will result in optimal production and increase sales revenues. The introduction of technological innovations such as 3D printing makes decentralized production cost-efficient at low volume and increases the requirement for supply chain analytics solutions. These cost-effective business operations will revolutionize the pharma industry over the next few years.

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Effective decision making

Many organizations in the industry are implementing sensors in the supply chain to offer real-time visibility and effective decision-making. The systems generate information that enables sales and operations teams to make dynamic decisions in response to changing conditions in the volatile market. These solutions also provide data analysis that results in forecast and planning accuracies, reduce risks of over or under stocks, and help healthcare institutions provide better patient care using advanced therapeutics.

Outcomes and solutions offered

Quantzig’s supply chain analytics for an established healthcare provider in the US offers comprehensive information on various supplier profiles, invoices, inbound logistic data, order history, inventory data, and operations. Some of the solutions offered are as follows:

  • Streamlined the order processing to enable easier access to valuable supply chain information
  • Improved inventory management through central and regional warehouses
  • Provided solutions to effectively manage safety stock levels for critical SKUs and supply chain costs
  • Improved the administrative cost savings and reduced the inventory replenishment cycle time
  • Monitored the delivery times of materials from suppliers to out-patients for cost reimbursements

The complete case study on supply chain analytics reduces inventory costs for an established healthcare provider is now available.

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Big Data Analytics Helps MNCs to Analyze Call Center Data to Streamline Business Processes

The latest big data analytics solutions by Quantzig helps a leading multinational company in the United States to improve their operational efficiency and customer service.

Big data analytics for effective call center services

Big data analytics in call centers help companies to structure data from the recordings and use it effectively for training purposes. The introduction of natural language processing (NLP) is used to direct customers’ calls to the respective department when a particular word or phrase is used in the conversation. The adoption of big data analytics and innovations in NLP systems will improve customer service and operational efficiency of call center operations. These solutions can be used to enhance the customer journey and offer customized solutions. Big data solutions collate data that offer detailed information on the customers’ preferences and help decision makers learn the patterns in their query behavior. The big data analytics solutions by Quantzig designs queuing and regression algorithms to estimate the influx rate and service time for inbound calls to develop service levels during peak hours. The study also offers predictive analytics to identify and upgrade important services that were negatively affected due to long waiting time.

With the help of big data, companies are analyzing data and information from previous interactions, emails and notes, support requests, back office solutions, CRM helpdesk, and social media portals. These solutions also help companies to perfect the quality of the interactions by studying the characteristics and behavior patterns of the customers.

Introduction of speech solutions

Speech solutions help reduce operating costs and enable organizations to expand services without additional overhead costs. This innovation is designed to identify words spoken by an individual, convert them into a machine-readable format, and respond automatically. The tools maximize the ROI of the company, have minimal upgradation costs, and the transaction models reduce the time spent on calls. Some of the systems accessible in the market can also analyze the caller’s tone, sentiment, vocabulary, and silences to evaluate emotion and satisfaction.

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Focus on enhancing customer relationships

The primary objective of big data analytics helps companies analyze customer feedback on an organization’s products and services and develop superior service and product portfolios. By using various language processing tools such as speech analytics, text analytics, and recognition methods, enterprises are focusing on improving customer satisfaction and increasing brand loyalty. The implementation of such system solutions will result in efficient communication systems and successful customer relationships to build profitable businesses.

Outcomes and solutions offered

With hands-on expertise in big data analytics, Quantzig assessed inbound data to improve customer service and operational efficiency of call center operations across businesses. Some of the solutions offered are as follows:

  • Built a tableau dashboard to determine the average delays for customer
  • Created an integrated data repository that was continuously updated by multiple data sources
  • Enabled real-time data analysis across both operational and marketing data
  • Developed highly precise forecasts for call arrival rates at different times of the day
  • Identified estimation and forecasting parameters from the various data sources

The complete case study on big data analytics improves customer service for a leading multinational company is now available.

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