AI-Driven Ad Targeting for Beauty E-Commerce Platform

A leading UK-based e-commerce platform specializing in luxury beauty products faced a critical challenge in its digital marketing strategy. Despite having access to vast customer data, the company struggled to target potential high-value customers effectively. As a result, their conversion rates were suboptimal, and their advertising campaigns yielded a lower ROI. It was clear that refining their ad targeting approach was crucial to maximize their marketing efforts.

What was the business objective?

The e-commerce platform aimed to enhance its advertising strategy and drive business growth with key objectives:

1. Targeting Precision: Improve ad targeting by focusing on customers interested in luxury beauty products, identifying high-value customers, and understanding their preferences.
2. Conversion Rate Improvement: Increase conversion rates from targeted campaigns by translating ad engagement into sales and minimizing customer drop-offs during the purchase process.
3. ROI Enhancement: Optimize advertising spend by allocating budget to effective channels and measuring the impact on sales and profitability.
4. Efficiency in Marketing Efforts: The world of digital traffic is in a state of constant flux. Thus, we incorporated mechanisms that enabled the system to refine its responses based on real-time data continually. This ensured that as new patterns emerged, the system was already poised to manage them effectively

Achieving these objectives required integrating advanced AI and machine learning capabilities into the e-commerce platform's advertising system, enabling smarter and more effective marketing campaigns for their luxury-oriented customer base.

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How did we accomplish it?

Data Collection and Management:

• Partnered with the client's marketing team to consolidate and augment their existing customer data.
• Executed comprehensive data mining to enrich the dataset with additional relevant data points.‍

Data Preparation:

• Conducted thorough data cleaning to ensure the accuracy and relevance of the data used for modelling.
• Undertook data exploration to understand underlying patterns and relationships within the data.
• Performed feature engineering to construct relevant input variables for the predictive model.

Predictive Modeling:

• Developed a sophisticated machine learning model capable of identifying customers most likely to yield a high ROI on advertisement spending.
• Utilized Big Data analytics and predictive modelling techniques, training the model on historical customer and ad campaign data.

Deployment and Integration:

• Deployed the final model onto a cloud platform using AWS for scalability and reliability.
• Integrated the model with the client’s existing ad campaign management system for real-time targeting optimization.

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The Results

The implementation of the AI-driven model by Sigmoidal led to a transformative increase in the effectiveness of the client's advertising campaigns. The client experienced a 3.5-fold increase in advertising uplift, significantly boosting their marketing ROI. Additionally, the improved targeting strategy resulted in a 15% increase in revenue for Q3 when compared to the results in the previous year. The ability to pinpoint high-ROI customers also allowed for more efficient ad spending, culminating in a 20% reduction in overall ad expenditure.