Welcome to Ibex Analytics

Customer Analytics

A better knowledge of the client has never been more crucial than now. Social media, accessible information, innovative business models, and ever-increasing possibilities make it critical to analyze and forecast client behavior.

The essential objectives of consumer happiness, loyalty, and value remain constant, but the tools to that aim are continuously evolving. Combining in-store and online habits, as well as social listening and surveys, provides firms with a 360-degree perspective of their customers.

Analytics is assisting businesses in predicting buying trends, client behaviors, and lifestyle choices, as well as providing hyper-personalized proposals. Customer interactions are being redefined via the use of data, technology, and predictive analytics.

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Why You Need Customer Analytics In Your Business

Customer Analytics is a process of collecting, gathering and analyzing customer data across a wide range of channels, interactions, funnels and help businesses make better business decisions. Customer analytics help businesses make better strategies, build better products, and provide better services to the customers. Important steps in the customer analytics process are data collection, data segmentation, visualization, modelling etc. Companies can use customer analytics for Direct marketing, better brand positioning and better customer relationship management. With proper analysis, one can provide a better experience to the customers, and make them stick to the brand. The likes and dislikes of the majority of customers can make or break a brand/ product. So, knowing customer habits are important and a well-implemented Customer Analytics strategy helps in predicting customer behaviour.

  • Customer Acquisition

    Gaining new customers is a vital part of any business, without customers there will be no business. Effective marketing and sales strategies can help in gaining new customers. Creating personalized and viral marketing campaigns are easy with the correct data and insights.

  • Customer Satisfaction and Retention

    Retaining customers is very important. By studying and understanding customer behavior, we can perform predictive customer analytics. Techniques can be developed to engage with the retained customers and improve their satisfaction.

  • Lower costs and Improve Revenue

    Better customer analytics can help lower acquisition costs and operating costs. Increased sales can also help in increased revenues. Consumers nowadays are very much price-conscious, informed, and selective. So brands and companies need to focus on selective targeting.