Background:

Rowenta, a prominent provider of vacuum cleaners, is committed to boosting its machine sales. To achieve this objective, Rowenta has developed a strategy that involves offering cashback incentives to potential new customers and soliciting reviews shortly after their purchase.

Leveraging the power of machine learning and artificial intelligence, Rowenta encourages prospective customers to verify their purchases by completing a form on the Rowenta website. While adhering to GDPR regulations, this initiative focuses on collecting personal details, purchase information, and valuable analytics data.

This approach not only enables Rowenta to gather a significant number of new customer reviews but also provides valuable insights into their preferences and experiences. The importance of capturing both new customers and their feedback is paramount. It drives growth, informs marketing strategies, enhances customer retention, and offers invaluable feedback for product improvement. These ongoing operations help Rowenta continually refine its automation system. All collected data is centralized in a data lake, and a data visualization system, such as Qlik, is seamlessly integrated for comprehensive analysis and reporting.

Challenges:

1. Customer Engagement: Encouraging potential customers to participate in the cashback program, submit reviews, and provide valuable feedback requires effective communication and compelling incentives.

2. Data Accuracy: Gathering accurate and comprehensive data about customer purchases, reviews, and other details is essential for deriving actionable insights.

3. Data Integration: Efficiently integrating and managing the collected data within a data lake for analysis and visualization.

4. GDPR Compliance: Ensuring that all data collection and processing activities comply with GDPR regulations is crucial to safeguard customer privacy.

Approach:

1. Incentive Strategy: Design an attractive cashback program, follow up with customers shortly after their purchase to request reviews, and encourage them to provide valuable feedback by making the process user-friendly.

2. User-Friendly Data Capture: Develop an intuitive online form on the Rowenta website that allows customers to easily submit their proof of purchase, reviews, and feedback, ensuring user-friendliness and accessibility.

3. Analytics and Insights: Leverage machine learning and AI algorithms to analyze data collected from conversion channels, user locations, customer reviews, and feedback. This will provide actionable insights into customer behavior, preferences, and overall product performance.

4. Automation and Cross/Up-Selling: Leverage the insights obtained to continually enhance Rowenta's automation system, enabling targeted cross-selling and up-selling strategies to maximize customer value.

5. Data Visualization with Qlik: Implement the data visualization using Qlik to create interactive dashboards and reports for in-depth analysis and decision-making.

Expected Outcomes:

Increased customer engagement through the cashback and review solicitation program.

GDPR-compliant data collection and processing practices, ensuring customer privacy and data security.

An influx of new customer reviews, deep insights into customer behavior and preferences, and constructive feedback for improving product quality.

Improved sales and customer retention through effective cross-selling and up-selling efforts.

Comprehensive data visualization using Qlik for real-time monitoring and informed decision-making.

Conclusion:

Rowenta's data capture initiative, supported by machine learning and artificial intelligence, is strategically positioned to enhance customer engagement, foster GDPR compliance, generate valuable insights, and capture reviews and feedback. 

The emphasis on capturing both new customers and their reviews is paramount, as it drives growth, informs marketing strategies, increases customer retention, and provides essential input for product enhancement. 

This approach will ultimately lead to improved sales, customer satisfaction, and informed decision-making through advanced data visualization with Qlik.