How the Contact Center Helped Increase the Revenue of an Online Sleep Products Store by 22%

Cloud-based contact center solutions are widely used by online retailers for a number of reasons. Among them are the ability to flexibly manage customer support resources based on demand and to integrate communication channels into a single system.

This was also the motivation of our client – an online store specializing in sleep products. Below, we’ll describe how the company implemented the KOMPaaS.tech Contact Center and what results it achieved.

KOMPaaS’s Client Profile

The online sleep products store offers a wide range of items, including mattresses, pillows, blankets, bed linen, and accessories for comfortable sleep.
Customer demand traditionally peaks in autumn and winter, as well as during seasonal sales and holiday promotions.

The store has a large customer base that requires efficient support and continuous efforts to attract new buyers. Before implementing the cloud contact center, communication with customers was carried out through standard phone lines and email, which often led to delays in processing inquiries – especially during high-demand periods.

Customers frequently experienced long waiting times, and operators struggled to handle multiple requests simultaneously. This affected the quality of personalized consultations and overall customer satisfaction.

Searching for a Solution

To address these challenges, the company considered several options for modernizing its customer service system, including hiring additional staff and implementing a new CRM system.

However, after a detailed analysis, the store’s management concluded that deploying a cloud-based omnichannel contact center would be the most effective solution. This would enable full integration of all communication channels, minimize waiting times, and ensure a high level of service personalization.

KOMPaaS.tech Solution Description

The omnichannel contact center solution from KOMPaaS.tech included chatbots, voice bots for handling inbound and outbound calls, and AI-powered speech analytics for call analysis.

The chatbots were configured to handle typical customer requests – such as order status updates, product specifications, and delivery conditions – relieving operators from routine tasks and speeding up response times.

Voice bots were introduced to automatically answer calls during peak hours and to perform outbound calls to inform customers about new promotions and offers. Their flexible configuration allowed scripts to be easily adjusted for current marketing campaigns and operational needs.

Speech analytics was implemented to improve service quality. The AI analyzes all inbound and outbound calls, identifies key words and phrases, and helps quickly detect problematic interactions for further staff training. This also supports the development of more effective communication scripts and contributes to higher customer satisfaction levels.

Implementation Results

After implementing the cloud contact center, the store significantly improved its customer service quality. The system enabled simultaneous processing of phone calls, chat messages, emails, and messenger inquiries, which reduced waiting times to a minimum.

As a result, the conversion rate from inquiries to purchases increased by 15% within the first three months.
The omnichannel technology greatly enhanced order processing and customer communication: the average response time decreased from 5 minutes to 1 minute, while the number of repeat inquiries dropped by 30%.

Additionally, due to accurate and timely consultations across all communication channels – whether via phone or chat – the store’s revenue grew by 22% within the first six months after implementation.
The results were measured using analytics tools integrated into the system, providing real-time data for timely service strategy adjustments.

Conclusion

The implementation of the KOMPaaS.tech cloud contact center became an important step in advancing sales and customer service for the online sleep products store.

In the future, the company plans to further expand the contact center’s functionality by integrating additional AI technologies for even more personalized customer experiences. It is also exploring the use of analytics for demand forecasting and inventory optimization.