The client* is a leading EU distributor of professional-grade cosmetic products, offering over 5,000 positions. The company operates in a B2C e-commerce marketplace and has a dedicated mobile app designed for beauty professionals and salons.
* We recognize the importance of protecting our clients’ privacy and follow the policies to maintain their confidentiality and security. That is why the company name will not be disclosed.
The client faced increasing volumes of repetitive customer service inquiries, both via chat and phone. These requests ranged from product recommendations to order status updates. Manual support wasn’t an effective way to manage the inquiries. It was time-consuming, resource-heavy, and not scalable for peak periods (e.g., promotions, holidays). Our e-commerce testing expertise covers AI-driven features, including virtual assistants, recommendation engines, and automated support flows.
Moreover, manual processing meant missing opportunities for cross-sells, upsells, and recovering abandoned carts. Also, supporting professional cosmetics customers required in-depth training for the support team to ensure expert-level guidance.
Our team suggested implementing a tailored AI assistant to automate and enhance customer support and drive sales. The project was rolled out in three key phases:
We fine‑tuned a natural language model specifically for the professional cosmetics domain and deployed a chat‑based virtual assistant on the store’s website and mobile app.
The assistant’s capabilities included:
Testing AI‑powered assistants requires specialized validation of NLP accuracy, dialog flows, and system integrations — core capabilities of our AI‑driven testing service.
We extended the assistant into a voice‑based interface, allowing users to call the store and interact via speech, and the call center to make outbound cold calls.
New features added at this stage were:
We enhanced the assistant to not only help but also sell.
The key upgrades featured:
Domain-specific fine-tuning for cosmetics and salon products, along with seamless transition between chat and voice, enabled the client to build an effective support flow. Integration with business systems (CRM, order tracking, analytics) and additional focus on sales had a positive impact on the overall business performance.
By the end of the 6-month project, total sales increased by 18.8%, driven by a combination of smart automation, intelligent selling, and operational optimization:
The call center, which had 11 employees across two shifts, was reduced to just 2 Level 2 supervisors, with the AI assistant handling first-line support autonomously.
With increased sales and significant operational cost savings, the solution achieved full ROI in under six months and continues delivering long-term value. QA Madness provided end-to-end quality assurance across all three development phases, ensuring each feature — from NLP accuracy to CRM sync — performed reliably before going live.
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