Why customer analytics matters

Customer analytics aids businesses in boosting
response rates

In the digital age, consumers have access to information on where to obtain goods and services, what to buy, and what to expect to pay for them. Organisations must leverage CRM led data analysis to provide customers with appropriate marketing campaigns and products to achieve fulfilment, before competitors do. Organisations can accomplish this by using customer analytics solutions to comprehend and act before their customers’ next move in the micro moment.
The goal of customer analytics is to provide a single, accurate view of an organisation’s customer base so that decisions on attracting and retaining new customers can be made with agility and ease. Additionally, it may recognise valuable customers and provide pro-active ways to communicate with them.

Leverage better customer insights with customer analytics by PredictiVu

The customer journey can be optimised by businesses that have a thorough understanding of customer demographics, purchasing patterns, web/social media activity, lifestyle preferences, and the purchasing history of customers. Large quantities of precision data are necessary for accurate predictive analysis. Without them, analysis could be completely off and useless.

Our approach to customer analytics

PredictiVu’s customer analytics journey starts by gathering raw data from numerous sources, including marketing tools, CRM systems, third-party sources, and ingesting this structured and unstructured data into a customer data platform. The next step is to prepare the customer data so that it can be used in the customised customer analytics tool. Businesses can use this tool to interpret the data generated and obtain predictive insights with charts and graphs to empower their leaders to make the right business decisions.




The 360 Degree Customer View
Using behavioural analytics and 360-degree modelling, businesses can obtain a comprehensive view of their customers by amassing data from different touch points that a consumer may use to contact a company to purchase items and receive service and support.
Micro Segmentation & Behavioural Analytics
With machine learning, businesses are able to identify client patterns and behaviours as they emerge, expanding your view of customers beyond a fixed set of categories. Unknown identities and archetypes can be uncovered via dynamic micro segmentation.
Customer Lifetime Value (CLV) Modelling
Using predictive and behavioural analytics, businesses will be able to calculate and predict the value of every consumer over time, product lines, segments, and even channels. Global businesses can create faster monetising initiatives with the use of CLV models.
Customer Engagement Strategies
Driven by data led customer engagement strategies, and by engaging in more positive relationships with customers, businesses can enhance their satisfaction level through any channel. Effective techniques transform reactive consumer involvement into proactive engagement.
Customer Acquisition Analytics
Helps in leveraging strategies to learn what consumers buy, why they buy it, and when they buy, to improve the marketing tactics of your business towards building a strong healthy customer base.
Customer Satisfaction Analysis (CSAT)
Collecting customer satisfaction data can assist businesses in identifying what aspects of their services, products, and internal procedures are performing well and what needs to be changed or improved. In order to foster wholesome customer connections, analytics can assist in uncovering new factors that improve customer relationships and deliver higher CSAT scores.
Customer Retention and Win Back
Early churn prediction and prevention are worthwhile investments because losing a customer is expensive. To stop churn, identifying churn risk indicators via predictive models are an imperative.

Benefits of using customer analytics

41% of C-suite executives think customer analytics has assisted them in developing better focused products for prospective consumers.

Investment in customer analytics has aided 86% of organisations in accurate and quick decision-making and 81% have improved customer communication.

81% of businesses rely on customer analytics to gain better customer insights based on their behaviour, experiences, beliefs, needs or desires.

According to studies, the cost to retain an existing customer is significantly less than acquiring a new one. By assisting organisations in better understanding their consumers, analytics can improve retention, boost profitability by improving efficiencies, and reduce wasteful costs.


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