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Churn Prevention
Companies across the domains are spending a lot of money and time to retain their customer base when a business loses customers, it needs to bring new customers in to replace the loss in revenue.
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Acquiring new customers is a costly affaire than retaining existing customers.
Machine Learning and Deep Learning help to identify churn in your customer base. Based on various parameters of your customers and identify those customers that are at the most risk for leaving. Companies can take the necessary steps to prevent the churn of high-risk customers and retain them.
Key Industries: Retail, Automotive, Banking, Insurance, Telecommunications, Manufacturing, Subscription-based business.
Customer Segmentation
Companies define the markets and customers such as high growth markets, Potential Markets, etc. According to various business parameters.
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Customer clustering helps the companies to divide the customers into groups based on similar behavior. The company can devise customized marketing/sales strategies to target the different groups, formed based on customer segmentation. This same data can also help to identify segments and potentially even entire markets that you didn’t even realize existed.
Key Industries: Automotive, Banking, Life Sciences/Pharmaceutical, Insurance, Retail, Telecommunications, Utilities, Engineering.
Risk Modeling
Risk modeling has been using in various industries for years to determine the risks associated with business decisions.
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Combination of these analytics with a risk management approach, companies can quantify risks, evaluate them, prioritize the action plans to mitigate those risk factors deemed most critical. Recently, organizations across the domains and govt sectors adopting the wide gamut of the models to solve the problems in strategic, operational, compliance areas.
Key Industries: Automotive, Banking, Manufacturing, Logistics & Transportation, Oil & Gas, Utilities.
Product Propensity
Analysis of customers’ online behavior and historical purchase data to determine what kind of customers would buy what kind of products.
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It helps to identify the efficient channels to reach your customers and maximize those channels that have the best chance of producing significant revenue
Key Industries: Banking, Insurance, Retail, and Telecommunications
Customer Lifetime Value
Every company wanted to understand how much money a customer will bring throughout the journey as a paying customer to you.
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The customer lifetime value gives you the idea about a customer would become repeat customers. If the customer Lifetime value is high, the customer is satisfied with your product/ service and would be a loyal customer to you. The insight we get from the customer Lifetime Value enables the companies to optimize their marketing, sales resources, and focus the energies on the important customers.
Key Industries: Manufacturing, Banking, Insurance, Retail, Telecommunications, Utilities, and Subscription-based business.
Predictive Maintenance
Predictive Maintenance is to find out potential causes of failure in machine/equipment.
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By analyzing data related to technical equipment, companies can predict both timelines for probable maintenance events and estimate budgets for warranty cost, allowing them to streamline their maintenance costs and avoid critical downtime.
Key Industries: Automotive, Manufacturing, Logistics & Transportation, Oil & Gas, Utilities, Telecommunications, Engineering
Sentiment Analysis
Approximately 80% of the data is unstructured data and text data is one of the most important unstructured data.
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Analyzing reviews, opinions, and reports and generating useful information from the text data is sentiment analysis. It involves web scraping, extracting text data through APIs, and preprocessing and determine the polarities of the text.
Key Industries: Life Sciences/Pharmaceutical, Education, Insurance, Retail, Telecommunications
Up and Cross-Selling
Acquisition of new customer costly affair in the competitive market. What if the companies get more revenue from existing customers?
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Your customer base is the source of both existing revenue and revenue growth for your company. Data science can help in identifying potential customers who can buy more or different products or services which is referred to as Up / Cross-selling.
Key Industries: Banking, Insurance, Retail, Telecommunications, Automotive, and Subscription-based business.