Customer Analytics

Businesses have more data at their fingertips than ever before, providing information into every step of the customer journey. Quematics could help businesses by using data analytics techniques to improve the customer experience and create a competitive advantage in today’s market

Customer Profiling & Segmentation

Whether you are looking to determine new product offerings or develop a personalized marketing campaign, customer segmentation is the principal basis for allocating resources and extracting maximum value from both high and low-profit customers. We use both demographic segmentation data and advanced clustering segmentation techniques to:

  • Conduct market segmentation to unveil meaningful and measurable segments or microsegments according to customer’s needs, behaviors, demographics and social profiles
  • Determine the revenue potential of each segment and target segments according to their profit potential and the ability of your company to serve them
  • Obtain a complete customer profile to help predict future behavior through a 360° customer view
  • Use target market analysis to tailor products, services, marketing and distribution strategies to match the needs of each segment
  • Measure performance of each segment and optimize your segmentation approach over time

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Customer Lifetime Value / Cycle Analytics.

Understanding the customer life cycle and customer lifetime value offers benefits in budgeting, segmentation and prioritization. CLV ultimately helps you in forecasting and improving the overall health of your company. Key benefits include:

Customer Acquisition and Retention: CLV gives you a better understanding of what you can spend to acquire customers and profitably retain them.

Targeted Marketing: One of the major uses of CLV is customer segmentation, which starts with the understanding that not all customers are equally important. CLV-based segmentation model allows the companies to predict the most profitable group of customers, understand those customers’ common characteristics, and focus more on them rather than on less profitable customers.

Understanding the customer life cycle and customer lifetime value offers benefits in budgeting, segmentation and prioritization. CLV ultimately helps you in forecasting and improving the overall health of your company. Key benefits include:

Customer Acquisition and Retention: CLV gives you a better understanding of what you can spend to acquire customers and profitably retain them.

Targeted Marketing: One of the major uses of CLV is customer segmentation, which starts with the understanding that not all customers are equally important. CLV-based segmentation model allows the companies to predict the most profitable group of customers, understand those customers’ common characteristics, and focus more on them rather than on less profitable customers.

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Customer Lost Analytics.

Given the high costs of customer acquisition in many industries, reducing customer lost through an intelligent segmentation of your customer base is essential to business viability. Leverage your customer data to reduce customer churn and reap maximum benefits from a well-segmented and thoroughly analyzed customer database.

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Challenges and Opportunities

Customer attrition or churn is a rate that measures the number of clients whose business is lost over a particular timeframe. In highly competitive industries where substitute products or services are readily available and the cost of retaining an existing customer is significantly lower than the cost of acquiring a new one, reducing customer churn is the key to long-term profitability. Customer segmentation—dividing a customer base into geographic, demographic, behavioral, and income categories so as to more effectively target products and services—is the key to reducing customer churn. The better segmented your customer data, the more efficiently you can invest scarce resources in those consumers who are most likely to respond to your offerings and the more able you will be to iteratively refine your products and services so as to retain their loyalty.

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Our Solution

Once that fundamental challenge is addressed, our consultants can help you to harness sophisticated Big Data techniques such as machine learning and predictive analytics to calculate and analyze your churn rate—percentage of customers whose business is lost per quarter or year; anticipated profit potential and lifetime revenue per customer by income, geography, demographics, etc.; discount rate—the cost of capital used to discount future revenue from a customer; retention cost—the amount of money required to retain a customer per quarter or year; and other metrics that may be important to your specific business. Having acquired and analyzed the data, we will make a strategic recommendation as to how best to harness it. Specifically, we can help you to design strong and highly personalized loyalty programs by identifying those services, support, and promotional offers that your most valued customer segments require to remain in good standing or increase their spending with your company. We can also help you to identify the customers that you don’t want because their risk profile is too high or their contribution to your bottom line is too minimal to warrant the investment.

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Cross Selling & Upselling

Companies can identify customers who have a higher propensity of making an additional purchase and target them with innovative and personalized cross selling and up selling strategies. Cross selling and upselling enables you to reduce acquisition costs, increase wallet share and customer lifetime value. Analytical tools and techniques such as Acquisition Pattern Analysis and Collaborative Filtering analyze the patterns in the customer’s past behavior, correlate this information with similar customers, and then identify potential service or product opportunities at each contact with the customer. We can help you do the following:

  • Identify and target prospective customers for cross selling
  • Determine products or service offerings and optimum price point for each customer
  • Build a scorecard to calculate the propensity of the target customers to purchase various products

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Market Basket Analysis & Product Bundling

Using Market Basket Analysis, our experts help you understand which product bundles are being purchased together by your customers, and in what sequence. Understanding the product combinations and the strength of these relationships is valuable information that can be used for making recommendations, cross selling and up selling, and offering coupons and promotions. Just a few years ago, Netflix offered a $10 million prize to improve the efficiency of its recommendation engine.  Using our advanced algorithmic techniques, we have the ability to build recommendation algorithms that can outperform the engine Netflix built by 10 times. Here are some of the things we can help you do for your business:

  • Assortment Planning and Shelf Storage: CPG companies can plan and create market-based, customer-based, fashion-based, and price-based assortment mixes. Putting co-dependent products close together improves the shopping experience and also allows for cross selling.
  • Online media sites and retailers can inform content and product placement in a catalog.
  • Build recommendation engines (like Amazon customers who bought this item also bought these items)
  • Targeted Marketing: Based on past buying patterns, email customers with product and service offerings that would likely interest them.

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