spotIndustry
Markets
2 storefronts: PL · DE
Modules
Helpdesk
Thulium
Results
Key results
Measured in AskSpot across 5,001 shopper chats over 30 days — what the agent does for the basket, and how much of the queue it closes on its own.
17%
of chats fill a basket
2.0
items in an average chat basket
54%
product recommendation click-through
71%
of chats resolved with no human
Before AskSpot
Most of the work arrives after the order, not before it
A multi-brand sports catalogue generates two very different kinds of question. Before the sale: how two Arc’teryx shells differ, which SUP suits a ten-year-old, what insole length a size 40 really is. After it: cancel this, return that, where is it, why was my payment refused.
The second group is the larger one, and it doesn’t respect opening hours or stop at the Polish border — Sportano runs a German storefront too. Restock questions add a third pattern: shoppers landing on an out-of-stock product with nowhere to go, which is a lost sale unless somebody offers the alternative.
Where the volume sits
after the order
Cover outside opening hours
none
Queues to staff
chat & e-mail
Languages to cover
PL & DE
Rollout
How they rolled it out
The catalogue first, so the agent could answer specs and rescue out-of-stock visits; then live order data, because most of the conversation happens after the order; then the e-mail queue, on the same two sources.
Step 01
Catalogue & Availability Sync
Specs, comparisons and restock
Two agents went live on one catalogue — “Twój asystent” on sportano.pl and “Ihr Assistent” on sportano.de, each answering in its own language. On an out-of-stock product the agent opens the conversation itself and offers the alternative.
What shoppers ask
- What’s the difference between these two Arc’teryx Beta SL jackets?
- When will the Nike Mercurial in 40 be back in stock?
- I’m looking for a SUP for a 10-year-old
Step 02
Order API Integration
Everything after the order
Sportano’s chat is more post-sale than pre-sale, so cancellations, delivery status and payment problems come from live order data — including whether a piece can still be collected in the Warsaw or Zielona Góra store.
What shoppers ask
- I ordered today — can I still cancel it?
- What does the status “extended processing” mean?
- Can I try the Scarpa climbing shoes in the Warsaw store?
Step 03
Thulium Integration
The post-sale e-mail queue
7,750 e-mails a month joined the same catalogue and order data the chat already used, so a restock answer or a cancellation rule is written once and holds in both channels and both languages.
What shoppers ask
- I can’t pay for my order — please help
- Will the Pinpack Comp packraft be available without a deck?
- Ist die Rücksendung kostenlos?
From real conversations
What Sportano shoppers actually ask
Specs and delivery lead, as they do everywhere — but the shape underneath is unusual. Restock questions are a sixth of everything asked, and returns, cancellations and complaints together are nearly a third. More of this chat happens after the order than before it.
Based on 5,006 tagged conversations over 30 days · about 9 messages each — the longest of any sports merchant on file · 36% arriving outside business hours.
More case studies
See how other stores use AskSpot
More stories from teams that automate support and grow sales with AskSpot.
How Sport-Shop turns 17% of chats into cart-adds
Sport-Shop.pl's AskSpot chat agent puts an item in the basket in 17% of conversations and resolves 88% with no human — delivery timing, sizing and fit for camping, beach and garden gear. 15,800 conversations a month across chat and email.
Read the story →
How Morele.net cut customer service costs by 90%
Morele.net cut customer service costs by 90% and went from 50 support agents to 5. AskSpot resolves 71% of its 37,600 monthly chats with no human, and answers Allegro marketplace questions from the same catalog.
Read the story →
How Militaria resolves 83% of chats in 9 languages
Militaria.pl runs AskSpot AI chat across three domains in nine shopper languages: 48% product recommendation click-through, 27% add-to-cart after a chat and 83% of chats resolved with no human — 16,600 conversations a month, over half after hours.
Read the story →
How 4FIZJO automated 50% of customer inquiries with AI
4FIZJO cut website calls and messages by 40% and automates a third of its helpdesk tickets. AskSpot's AI Chat resolves 74% of its 21,360 monthly chats with no human, across 6 markets, and its Inbox Agent clears email and Allegro tickets in Thulium.
Read the story →
How Tatuum turns 18% of fashion chats into a sale
Tatuum's AskSpot sales agent turns 18% of chats into a purchase and 28% into cart-adds — reading the size chart from real body measurements, in Polish and Hungarian. Its inbox agent auto-resolves 41% of post-sale emails.
Read the story →
How Twoje Meble fills 1 in 5 furniture carts
Twoje Meble's AI sales agent adds an item to the cart in 18.5% of chats and resolves 88% with no human — 2,057 furniture conversations a month, 41% of them after the showroom closes.
Read the story →
See every story
Every merchant we have measured — what shoppers asked, what the agent did, and the numbers it moved.
Browse them all →