Before the connection
Tostco's problem was never demand. They were buying ads and the traffic was arriving — it was arriving in the chat, where it died. Every enquiry went to a human. During peaks, evenings and nights, 60 to 70 messages a day were never answered at all.
Paid traffic was converting into missed messages: the store paid for the click, the customer asked a question, and no one replied until the customer had bought elsewhere.
The chat also left no trace. There was no record of what customers asked for, what they could not find, or why they left — so there was nothing to optimise and no data to plan the assortment against.
What we did and what changed
EzguSavdo was connected to the store's chat channels and to its catalogue and live stock, and took over the front line of the conversation: replying in the customer's language, checking availability in real time, quoting prices computed by the store's own rules rather than by the model, and taking the order.
Zero missed enquiries. Every message gets an answer, including nights and peaks.
Message-to-order conversion up 30% against their previous level — the same paid traffic, more completed sales.
Demand analytics surfaced what customers were asking for and the store did not carry. Tostco now uses that list to expand its assortment — an input they simply did not have before.
The third outcome matters most commercially: the same conversations that close today's sale also tell the merchant what to buy for tomorrow.