A growing online retailer for household and leisure products faced a common issue: the customer support team was overwhelmed. Hundreds of nearly identical inquiries came in every day: “Where is my order?”, “How does the return process work?”, “Is this item in stock?”. Support agents had to manually answer each one. This led to long response times and growing customer dissatisfaction.
The cost of slow replies, lost sales, and negative reviews mounted. A change was crucial. Management decided: Frequent questions must be answered automatically – reliably, scalably, and in real-time.
A smart FAQ bot was developed in cooperation with a specialized AI provider. It was trained on real customer queries, product manuals, internal knowledge articles, and CRM data. Natural Language Processing enabled the bot to understand intent and context.
The bot was seamlessly integrated into the website and appeared on product pages, in the shopping cart, and the help section. No app download or extra login was needed.
The real breakthrough came with the bloola platform, which connected the bot securely to internal systems. With bloola’s robust data integration, the bot always delivered up-to-date answers on delivery times, order status, and stock availability.
In just a few weeks, results were evident:
85% of queries were fully handled by the bot, no human required.
Response times dropped by 60%, freeing support staff for complex issues.
Customer satisfaction increased by 25%, based on checkout surveys.
Conversion rates rose by 8%, with faster answers leading to more purchases.
The bot was available 24/7, including nights and public holidays.
Beyond technical gains, this marked a cultural shift: Support staff became problem solvers, not just answer providers.
The journey is far from over. Next steps include:
Expanding the bot to support multiple languages.
Integrating it into social channels like WhatsApp and Instagram.
Enabling the bot to handle returns and warranty inquiries.
bloola remains the foundation for this growth. Its flexible data integration ensures scalability without retraining the bot. The target: automate 95% of standard support interactions.