Join Dayapreet Singh (Dollar General), Impu Chunchegowda (City Furniture), Jason Bryant, and Shashi Ereti (Tapestry) as they explore how quality engineering drives seamless digital experiences in retail. Learn how top teams balance automation, compliance, and innovation to deliver secure, high-performing, and personalized customer experiences.
Discover strategies for scaling QE, optimizing testing processes, and adapting to the challenges of omnichannel retail while maintaining operational efficiency and quality at every stage.
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How do we balance rapid releases with strict compliance requirements like PCI DSS or GDPR?
Does security testing and vulnerability assessment a play role within QE practices (to safeguard sensitive customer data, prevent breaches, and maintain trust)?
How do you approach load testing for massive retail events like Black Friday?
What strategies can retail businesses employ to cultivate a proactive (not reactive) culture of quality engineering across all departments?
How can QE safely but effectively use emerging technologies like quantum computing and advanced AI for testing financial modeling, risk assessment, and fraud detection?
How might QE effectively use AI and machine learning technologies to accelerate testing cycles and enhance test coverage in complex retail systems and environments?
What are some key best practices for integrating quality engineering into agile and DevOps workflows in the retail sector?
How do you see quality engineering evolving to ensure trust in retail transactions powered by AI and blockchain?
What metrics or KPIs best measure the “digital quality” of retail experiences?
What role should testing play in validating the inclusiveness and accessibility of retail digital interfaces?
Whats harder in AI testing, catching hallucinations or explaining why they happened?
AI is everywhere -recommendation engines, chatbots, dynamic pricing. These tools rely on data, but how do you test for accuracy and fairness? A biased recommendation system could turn off customers. How do QE teams validate AI models
How can automation and AI-driven testing help retailers reduce release cycles without compromising quality?
How can quality engineering help stores give customers a better online shopping experience?
How do you approach testing LLM model?
What’s your red flag when an AI testing tool is overpromising?
How do you handle quality assurance across multiple platforms (web, mobile, in-store systems) simultaneously?
What are the biggest challenges in balancing speed of delivery with maintaining high-quality digital experiences?
What are the emerging tools or technologies that are shaping retail quality engineering today?
