Boosting Profitability and Customer Acquisition for a Leading Photo Sharing Platform

About the Customer

The customer is a popular image-sharing platform with over 5 million photographs. They offer photo and video hosting, and basic e-commerce functionalities for amateur and professional photographers. This platform not only lets users display but also enables them to sell photos online.

Their Challenges

In today’s competitive landscape, maximizing profitability and attracting new customers is crucial. Our customer, a leading platform for photographers, faced several challenges in achieving these goals:

Manual and Inaccurate Pricing

Setting optimal prices for millions of photographs was a time-consuming and error-prone manual process. This limited their ability to implement strategic pricing based on market trends and customer segments.

Limited Insights into Buyer Behavior

Relying solely on manual pricing lacked the ability to leverage valuable data on user behavior and purchase history. This hindered their ability to predict customer willingness to pay for specific photographs.

Scalability for Future Growth

As the platform’s user base grows, manually managing pricing would become even more cumbersome and inefficient. They needed a solution that could scale effectively with their increasing photo volume.

The Solution

Machine Learning-Powered Price Prediction

Searce built a machine learning model on Google Cloud’s Vertex AI platform. This model, trained on historical sales data, predicts optimal prices for photographs by considering factors like customer segments, product categories, and photographer information.

IMPACT

Improved Pricing Strategy

Sellers on the customer’s platform gain access to AI-powered price recommendations for optimized profitability

IMPACT

Increased Sales & Profits

Eliminating manual predictions lead to higher sales & revenue

Seamless Data Integration and Analysis

The customer provided Searce with a rich dataset encompassing transaction details, photographer information, user profiles, and user behavior data. This comprehensive data empowered the model to identify pricing patterns and optimize pricing strategies.

Scalable and User-Friendly Deployment

The machine learning model was deployed on Vertex AI, a scalable and intuitive platform. This allows the customer to process new data efficiently (e.g., newly uploaded photos) and generate bulk price predictions, freeing them from manual pricing tasks.

IMPACT

Data-Driven Approach

Empowers sellers with data-centric product pricing, paving the way for wider adoption of machine learning in e-commerce