Retail
+2000 employees
Milan, Italy
Warehouse System Integration
Multichannel Ticket Management
Proprietary Mobile App
Automatic Routing to Store
Real-time Assistance for Online and In-store Product Availability
For Bricocenter, a key player in retail specializing in construction, DIY, carpentry, gardening, decoration, lighting, and bathroom furnishings, it's crucial for customers to interact with highly qualified staff in-store. Customers trust the expertise and advice they receive from staff regarding the products they are looking for or have purchased.
However, it's also important to consider the challenge for in-store staff to simultaneously and optimally manage both in-store and online customer relationships. To address this, Bricocenter has opted to leverage the support of Stip AI.
In addition to automatically and in real-time resolving simple requests that do not require in-store staff intervention, it sends more complex requests to the store via a customized mobile app built for Bricocenter. The requests arrive on the app already categorized and equipped with all the necessary data and information to manage them easily.
Thanks to Stip's mobile application, Bricocenter store staff can directly engage with customers and respond to requests from any channel, using a single interface directly from their smartphone.
Stip AI uses its plug-ins to monitor all digital channels of interest to Bricocenter.
This activity allows for faster and smoother request management and less frustration for the end customer: no matter which channel they choose to communicate with Bricocenter, they won't be forced to repeat the same information to different operators or change channels (e.g., from Facebook to email).
In addition to enabling consistent multichannel management, Stip AI automatically and in real-time manages and resolves simple assistance or information requests without the need for operator or in-store staff intervention.
Without Stip AI:
To check the availability of a product in any Bricocenter store, the customer can:
Call the store
Go to the Bricocenter website and search for the store and product of interest
With Stip AI:
Customers can ask Bricocenter for the availability of a product using any contact channel (social media, web chat, WhatsApp, live chat) and receive an immediate response, made possible by integration with the warehouse systems.
Once they find the product of interest, they can:
Purchase it directly online
Chat with the store to ask for further details and reserve the product.
For the most complex requests that require human intervention, Stip’s AI interacts directly with the customer, asking for the necessary data and collecting information within the ticket.
Once the ticket is categorized, Stip AI routes it to the reference store, putting the customer directly in touch with the store staff who can quickly resolve the request and provide support, converting the request into a sale.
Each Bricocenter store only views tickets within its purview and can create specialization areas, allowing staff to manage only certain types of requests.
Using filter systems, staff can view and search tickets by channel of origin, date, reason for contact, collected data, and much more.
On their smartphone, store staff can view all tickets received, regardless of the channel used by the customer, in a single interface.
They can chat with the customer, view data and information, and any attached files.
The Stip platform is extremely easy to use and customized for the company.
In some cases, changing contact channels is necessary. In these cases, with just one click, the operator or store staff can, for example, close a request on Facebook and send a discount code to the customer via email.
All tickets are contained within an archive. In the archive, tickets can be searched by entry channel, sender, type of collected data, date range, ticket category, and much more.
Stip AI tracks activities and prepares a set of statistics, allowing the company to:
analyze the performance of various departments and staff
analyze the operations and performance of individual stores
understand the type and distribution of requests.
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