Drive Sales Growth with Personalized Recommendations
Implement AI-powered Recommendation Engines to Enhance Customer
Experience and Increase Revenue.
This use case demonstrates how businesses can leverage a prescriptive recommendation engine to provide personalised product and service recommendations to their customers. By analysing customer behaviour, purchase history, and preferences, the recommendation engine delivers tailored suggestions that enhance customer satisfaction and increase sales. The engine uses advanced algorithms and machine learning techniques to continuously learn and adapt to customer preferences, ensuring that recommendations remain relevant and effective. Implementing a prescriptive recommendation engine allows businesses to drive higher engagement, foster customer loyalty, and achieve significant growth in revenue.
Key Benefits
By deploying a recommendation engine into their online shopping website, our client saw a 17% increase on basket size, estimated to generate an additional $100K in sales each month.
Business Challenge
An online fashion retailer wanted to understand what makes certain clothing items popular.
Traditional research highlighted fashion trends, but they sought a more data-driven approach to understand what drives the popularity of specific pieces.
Our Approach
We first needed to understand the client’s business model, including how they buy and promote their clothing products.
We explored which attributes could be used to predict the popularity of products, measured by the volume/quantity sold.
Since the descriptions provided by manufacturers were insufficient for analysis, we decided to create our own attributes using computer vision.
The Solution
Using images from their online/ecommerce store, we conducted feature engineering in two stages:
Top-Level Identification: Identifying basic attributes such as collar, sleeve, colour, and pattern.
Detailed Feature Engineering: For each top-level attribute, further analysis was conducted based on manual labelling (e.g., collar styles: straight point, semi-spread, cutaway, long button-down).
We then analysed the common attributes of high-selling products.
Business Outcomes
We discovered that many products shared common attributes that correlated with high sales volumes.
This insight allowed the client to predict the likely sales volumes of different clothing items based on their attributes, enabling them to optimise their purchasing decisions.
The client estimated that this data-driven approach would save them tens of thousands of dollars by optimising their inventory management.
Features and Capabilities
AI Powered Recommendation Algorithms
Personalized Shopping Experiences IInfohensive’s Prescriptive Recommendation Engine leverages advanced AI and machine learning algorithms to analyze customer data in real-time. By processing customer behavior, preferences, and historical purchase data, our solution generates personalized product recommendations that resonate with each individual shopper. This dynamic approach enhances customer engagement, increases average basket size, and drives sales conversion rates.
Dynamic Personalization
Real-Time Adaptation Our solution dynamically adapts recommendations based on ongoing customer interactions, browsing behavior, and contextual data. Whether customers are exploring your website, engaging with promotional emails, or interacting through mobile apps, Infohensive ensures that recommendations remain relevant and timely. This capability enables businesses to deliver seamless and personalized shopping experiences that foster loyalty and repeat purchases.
Revenue Impact
Drive Sales Growth By implementing Infohensive’s Prescriptive Recommendation Engine, businesses experience tangible revenue growth. Our solution is designed to optimize sales performance by encouraging upsells, cross-sells, and impulse purchases through strategic product recommendations. Clients have seen substantial increases in average basket size and overall sales revenue, such as a 17% increase in basket size, estimated to generate an additional $100K in sales per month.
Customer insights
Actionable Data Analytics Infohensive provides comprehensive insights into customer preferences, shopping behaviors, and product interests. Through intuitive dashboards and analytics tools, businesses gain deep visibility into customer segmentation and purchasing patterns. These insights empower marketing and merchandising teams to make data-driven decisions, refine product assortments, and tailor promotional strategies effectively.
Scalability and Security
Flexible and Secure Solutions Our solution is scalable to accommodate varying business needs and growth trajectories. Whether you operate a small boutique or a multinational enterprise, Infohensive’s recommendation engine scales effortlessly to handle increasing data volumes and customer interactions. Security is paramount; we employ robust data protection measures, including encryption and access controls, to safeguard customer information and ensure compliance with data privacy regulations.
Reasons to Choose Our: Prescriptive Recommendation Engine
Potential clients choose our use case for solving their business performance because it:
- Enhances Inventory Management: Provides data-driven insights to predict the popularity of products, allowing for optimised purchasing decisions and significant cost savings.
- Improves Understanding of Customer Preferences: Utilises advanced feature engineering to identify attributes that drive sales, helping businesses better understand and cater to customer preferences.
- Increases Sales and Profitability: Enables accurate forecasting of sales volumes, ensuring that the right products are stocked in the right quantities, leading to increased sales and improved profitability.
