spotIndustry
Scale
87,000 products
Modules
Languages
PL · ES · DE · IT · FR · RO · PT · HU · DK · SK · CZ
Integrations
IdoSell
Results
Key results for a car-accessories store
Measured in AskSpot over 30 days, on all twelve storefronts – what a confirmed fit does to the basket, and how much of the queue never reaches a person.
€22,100
in chat-driven orders a month
19.6%
of chats add an item to the cart
11.3%
of chats end in a purchase
72%
of chats resolved
“Thanks to AskSpot, we have significantly reduced customer response times and improved the quality of service at carmager.com. The automation works reliably and delivers real value to both customers and the team. The solution scales well with store traffic and proves itself in day-to-day operations.”
Before AskSpot
Twelve storefronts, and one question that never changes
Nothing in this catalogue is generic. A seat cover, a trunk liner or a roof rack is matched to one specific car. During the chat the shopper gives the vehicle’s details – make, model, generation or production years – along with the specifics they still have to go and check: the trim, whether the rear bench splits 2/1, whether the roof has factory fixing points. Every sale turns on the same question, and getting it wrong turns into a return.
That question then arrives twelve times over, in twelve country storefronts, in the shopper’s own language. Seven in ten of those conversations come from outside Poland – Spain, Germany, Italy, France, Romania, Portugal, Hungary – while the phone line runs weekday mornings from one office in Toruń. Most of the asking happens after it has closed.
Country storefronts to cover
12
Phone line
25 h a week
Help outside those hours
none
Every part sold by
make · model · year
Rollout
How Carmager rolled out AI chat on IdoSell
Two moves, in the order that removed the most work: the fitment question first, then the same agent on every country storefront – all reading one catalogue.
Step 01
Fitment Catalogue Sync
Which part fits which car
The IdoSell catalogue is indexed by production range, so the agent answers a fit question from the same data the product page is built on – across Auto-Dekor, Aristar, Amos or Amal Plast.
What shoppers ask
- Does it mount into the factory fixing points?
- Are the covers compatible with side airbags?
- Is the rear bench split 2/1?
Step 02
Per-Market Agent Rollout
Every storefront in its own language
One agent per country subdomain, from the Polish shop out to es, de, it, fr, ro, pt, hu, dk, sk, cz and at – same catalogue underneath. Spain, Germany and Italy alone now outweigh the home market.
What shoppers ask
- Passen diese Bezüge auch auf den VW Transporter T5?
- Hola, ¿tenéis las del Toyota Rav4 2026?
- Aká je dodacia doba?
Around the clock
Your busiest hours aren't nine to five
Each bar is the share of chats by hour of day, in local time. The shaded window is when a typical team is at their desks. Everything outside it is the agent working a shift no one else is on.
From real conversations
What Carmager shoppers actually ask
Three of the top four are the same question wearing different clothes: does this part fit my car. Specs, finding the right part and outright compatibility checks are 70% of everything asked – make, model, production year, trim, and whether the rear bench splits 2/1. Delivery is a distant fourth.
Based on tagged conversations over 30 days · about 8 messages each · 61% 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 Morele.net cut customer service costs by 90%
Morele.net cut support costs 90%, from 50 agents to 5. AskSpot resolves 65% of its 37,600 monthly chats with no human and answers Allegro questions too.
Read the story →
How Militaria resolves 72% of chats in 8 languages
Militaria.pl runs AskSpot across three domains in eight languages: 61% recommendation click-through, 26% add-to-cart after a chat, 72% resolved with no human.
Read the story →
How 4FIZJO resolves 61% of customer chats with AI
AskSpot's AI Chat resolves 61% of 4FIZJO's 21,360 monthly chats with no human across 6 markets; its Inbox Agent auto-resolves 25% of email tickets.
Read the story →
GadziSklep: 81% of exotic-pet chats resolved by AI
GadziSklep's AskSpot chat helps hobbyists build a whole terrarium setup – enclosure, UVB, heating, feeders and supplements – resolving 81% of chats, sending 30.6% to the cart at a 48% recommendation click-through, 69% of it after hours.
Read the story →
How chat advice puts €1.9M of garden furniture in baskets a month
Meblobranie's AskSpot agent answers the questions garden furniture is bought on – size, colour, anchoring, spare nets. Chat advice puts €1.9M into the cart a month, 20% of chats fill a basket, 70% resolved.
Read the story →
How one AI agent runs across Szopex’s three retail brands
One AskSpot agent runs across Szopex's three storefronts – Sklep Biegacza, Warsaw Sneaker Store and SKStore – on three e-commerce platforms. 67% of chats resolved, 58% product CTR, 11.7% end in a purchase.
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 →
Other industries
Built for these industries too
This store is one vertical – see how AskSpot works across the others, each from its own catalogue.