spotIndustry
Scale
4,700 garden and terrace products
Modules
Years on market
16
Integrations
Custom integration · Freshdesk
Results
Key results for a garden furniture store
Measured in AskSpot over 30 days – what the agent does for the basket, and how much of the queue it closes on its own.
€1.9M
of furniture added to the cart a month
20.2%
of chats fill a basket
46.3%
of chats with a recommendation click it
70%
of chats resolved
“The rollout took less time than we expected and did not require rebuilding our processes. The AskSpot team fit the solution to the way we work, not the other way around. We saw that flexibility at every stage, including when we raised feedback.
Before going live we tested the assistant on our own hardest questions and decided which cases it starts with. We are widening its scope step by step and still see room to grow. Repetitive questions no longer take up our advisors’ time, so they can spend it on the conversations that call for judgement and a human touch. Customers get accurate answers in the evenings and at weekends too, while our team’s working hours have stayed the same.”
Before AskSpot
Every set has to fit a garden nobody at the shop has seen
Meblobranie sells outdoor living in fixed sizes: a pergola is 3×4 m, a steel shed is 240×300 cm, a corner set has a 138 cm short arm. The shopper has a terrace, a fence line and a wall – and needs to know whether those numbers work together before committing several hundred euros. That arithmetic is not on a category page, and getting it wrong means returning something that arrived in five boxes.
The other half is what the catalogue cannot be talked into. Sets ship in the configurations shown, so the cushions do not come in a darker shade and the mosquito net is not sold on its own. Saying that plainly, and naming what does work instead, is most of the job – and the demand runs into the evening and across the weekend, when the terrace is in front of the shopper and the shop is shut.
Cover outside opening hours
none
Questions that repeat most
dimensions & configuration
Peak enquiry time
evenings & weekends
Queues to staff
chat & Freshdesk email
Rollout
How Meblobranie rolled out AI chat and a Freshdesk inbox
The catalogue first, because a garden set is chosen on its measurements; then the purchase rules, because anchoring, delivery and assembly decide whether those measurements are usable; then the email queue, where the same set turns up again as the logistics of a big delivery – dates, parcels and order changes.
Step 01
Catalogue & Spec Sync
Sizes, materials and colour variants
The whole outdoor range went in – pergolas, gazebos, technorattan corners, steel sheds, carports and hot tubs – with the dimensions the products are actually chosen on. The agent does the arithmetic out loud: a 3 m pergola against a 2.40 m terrace, a 138 cm short arm against 140 cm of wall. Where a size does not exist it says so and names the nearest one that does.
What shoppers ask
- My terrace is 2.40 by 4.50 m – which pergola fits?
- A shed 5 metres wide and 2 metres deep
- How thick and wide is the top profile?
Step 02
Knowledge Base & Purchase Rules
Anchoring, delivery and the limits of the range
Anchoring requirements, multi-box delivery, instalment payment and – just as important – what the range will not do came from Meblobranie’s own knowledge base. So “can I swap the cushions” and “is there an assembly service” get the shop’s answer rather than a guess, with the alternative that does exist named in the same reply.
What shoppers ask
- Does the pergola have to be fixed to paving, or can it go in the ground?
- Can I order just the mosquito net for a 3×6 pavilion?
- Is there an assembly service, and what does it cost?
Step 03
Freshdesk Integration
The post-sale email queue
The Freshdesk queue joined the same catalogue and order data, so a delivery rule only has to be right once to be right on chat and in the inbox. Because a set arrives in several boxes, most of this queue is delivery logistics – which anchor size, how many parcels, when the order lands, a date to move. Anything that needs a judgement call, like a claim with photos, goes to the team with the thread intact.
What customers write in
- Can the delivery be moved by one day?
- What size anchors do I need for a 3×3 pergola?
- When will the second box of the set arrive?
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 Meblobranie shoppers actually ask
Garden furniture is bought on measurements. A third of everything asked is a dimension or a specification – how thick the top profile is, whether a 3 m pergola clears a 2.40 m terrace, whether the cushions come in a darker shade. The rest is the practical half of a big-ticket delivery: what it costs and when it lands, how many boxes to expect, and which net or blind fits the model already standing in the garden.
Based on tagged conversations over 30 days · a conversation can carry several tags, so the shares add up to more than 100% · 7.7 messages each · 62% 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 Ogrodosfera turns garden questions into €412,000 a month
A pergola is bought on specs, not on a whim. Ogrodosfera's AskSpot agent answers dimensions, materials and wind ratings – €412,000/mo in chat orders.
Read the story →
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 9 languages
Militaria.pl runs AskSpot across three domains in nine languages: 27% add-to-cart after a chat, 72% resolved with no human, 16,600 conversations a month.
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 →
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 →
How moderno.dk resolves 64% of furniture chats with no human
moderno.dk's AskSpot agent resolves 64% of furniture questions with no human – delivery, sizing, stock and order changes – and turns 12.3% of chats into carts.
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.