eComjini E-commerce analytics services helps global marketing organizations and digital agencies to improve and expand their capabilities for capturing, gathering, reporting, analyzing the digital marketing data
eComjini offer global marketing organizations and e-commerce agencies, a competitive advantage through increased ability to enhance their data capturing capacities. This would help companies understand the dynamicity of market needs based on our extensive industry knowledge and day-to-day working experience
Our Offerings
Cart Abandonment
All online retailers experience shopping cart abandonment. In order to combat shopping cart abandonment, it’s important to analyze the shopping experience from the moment a shopper adds a product to their cart through purchase completion in order 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 and automating post-abandonment messages will lead to increased revenue without requiring a major effort.
Dynamic Pricing
This is a technique to identify the patterns of different price sensitivities based on the purchase behavior, transactional behavior and demographic information of customers.
Dynamic pricing techniques help to bring the right price to the right customer and focused customer acquisition by better understanding of the customer and predict the price sensitivity score of the customer.
Personalized User Experience
Personalization is the process of tailoring content to individual users’ characteristics or preferences.
It is a meeting helps meet the customer’s needs effectively and efficiently, making interaction faster and easier and, consequently, increasing customer satisfaction and retention.
Campaign Optimization
Today’s marketers leverage many established best practices and tools to efficiently collect the necessary data to analyze marketing campaigns and make informed data-driven business decisions.
Campaign analysis can not only help the marketers to with make short term fixes to their marketing campaign mix but can also provide them marketer with insight into maximizing the lifetime value of a customer over time. The campaign analysis and optimization process can be divided into two major categories:
Harvesting of Low Hanging Fruit: Refers to areas in need of improvement that are easy to identify and provide quick and effective results.
Long Term Optimization: Refers to the process of continual optimization over time and includes improving the customer’s overall lifetime value.
Customer Acquisition
Today’s consumers are more sophisticated and empowered and 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 ways to improve customer acquisition. Companies can also improve the 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 is a technique used by online advertisers to increase the effectiveness of their campaigns, and is playing an increasingly important role in the online advertising market.
The assumption behind behavioral targeting is that the users who have similar search or browsing behaviors will have similar interests and thus have higher probability to click the same ad than the users who have different online behaviors. Different machine learning algorithms are used to mine data and predict the 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 the web logs.
Demand / Price Forecasting
Demand / price forecasting is the method of understanding of the future demand of the products or a group of products which helps the e-retailors to keep or optimize their inventory and they can reduce the warehouse cost accordingly which leads to the reducing the operational cost.
Refund Prediction
One important aspect of reverse logistics is to have a correct and timely estimation of return flow of material. Improved forecast accuracy can lead to a better decision making in strategic, tactical and operational areas of the organization.
Inventory & Order Management
Inventory & Order management is the operational process which can be optimize based on the location and demand sales, price, delivery time etc.
Offerings
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.
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.
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.
Projects
Above is simply a small selection of the elements covered by our projects. We have covered many other areas, from specific projects around UX consultancy, trading, and analytics transformation, to overarching Ecommerce Strategy projects. If you are looking for assistance, or simply a chat about opportunities, get in touch below.