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Happiest Minds eCommerce analytics services helps global marketing organizations and digital agencies enhance their data capturing, reporting and analyzing capabilities to stay ahead of the competition. We help  organizations in understanding the dynamicity of market needs based on our extensive industry knowledge and day-to-day working experience.


Increase Coneversion

Cart Abandonment

All online retailers experience shopping cart abandonment. To combat this problem, analyzing the shopping experience, right from the moment shoppers start adding products to their cart till the time they finish their purchase, is important to determine what post-abandonment marketing tactics can be leveraged to eventually gain conversion. Covering every fork in the road that could cause a customer to abandon their purchase by using ecommerce analytics services and automating post-abandonment messages will lead to increased revenue without major efforts.

Dynamic Pricing

This helps identify price sensitivity patterns based on purchase behavior, transactional behavior and demographic information. Our ecommerce analytics services enable companies to understand these behavioral patterns. Dynamic pricing techniques help offer the right price to the right customer, ensure focused customer acquisition (by understanding the customer better), and predict the price sensitivity score of the customer.

Personalized User Experience

Personalization is the process of tailoring content to suit individual user preferences/characteristics. Powered by our ecommerce analytics services, companies can meet customer demands effectively and efficiently, and make interaction faster and easier, thereby increasing customer satisfaction and retention.

Improve Traffic Quality

Campaign Optimization

Marketers, today, leverage many established best practices and tools to efficiently collect the data necessary to analyze marketing campaigns and make informed data-driven business decisions.

Campaign analysis can not only help marketers to make short term fixes to their marketing campaign mix but also provide them with the insights needed to maximizing the lifetime value of a customer over time. The campaign analysis and optimization process can be divided into two major categories:

  • Harvesting Low Hanging Fruits: This refers to areas needing improvement that are easy to identify and provide quick and effective results.
  • Term Optimization: This refers to the process of continual optimization over time and includes improving the customer’s overall lifetime value.

Customer Acquisition

The digital age consumers are more informed sophisticated; they expect businesses to understand when and how they wish to be engaged.

Customer analytics transforms your data into actionable insights, so you can anticipate what customers want and discover the most effective way to improve customer acquisition. Companies can also improve customer acquisition through segmentation and clustering techniques, reduce costs by targeting prospects that are mostly likely to respond and, anticipate which products, services and/or features customers care about the most.

Search Engine Optimization

Behavioral Targeting, a technique used by online advertisers to increase the effectiveness of their campaigns, is playing an increasingly important role in the online advertising world.

The assumption behind behavioral targeting is that the users who have similar search or browsing behaviors will have similar interests, and thus are more likely to click the same ad (as compared to users who have different online behaviors). Different machine learning algorithms are used to mime data and predict online visitors’ behavior.

Buyer’s Behavior Prediction

Web servers keep track of web users’ browsing behavior in web logs.From these logs, one can build statistical models that predict the users’ next requests based on their current behavior. These data are complex due to their large size and sequential nature. In the past, researchers have proposed different methods for building association-rule based prediction models using such web logs.

Reduce Operation Cost

Demand/Price Forecasting

Demand/price forecasting helps predict the demand of products or a group of products in future, which helps e-retailers to keep or optimize their inventory, thereby helping them reduce warehouse operational costs.

Refund Prediction

Reverse logistics helps in the correct and timely estimation of reverse material flow.Improved forecast accuracy can lead to better decision making in strategic, tactical and operational areas of an organization.

Inventory & Order Management

Inventory & Order management can be optimized based on the location, demand, sales, price, delivery time, etc.


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