One-minute narrated stories of a flow at work. The scenarios and figures are illustrative, not customer results.
Organic cosmetics
The challenge. Jonas leads sales for an organic cosmetics brand in Hamburg. His team of five sells to concept stores and beauty shops. Their prospect list comes from three places, so the same shop shows up two or three times. Reps call stores that already stock them. One owner in Ottensen got four calls in a week, and asked them to stop.
The flow. With xMap Flows, Jonas built Prospector. Every Monday at eight, across greater Hamburg, Prospector finds the beauty and concept stores, searches the map for zero-waste and organic shops, keeps each shop once, leaves out the ones that already stock the brand, scores how well each one fits, and puts them in the team’s prospect sheet.
The result. This Monday, the sheet holds thirty-one fresh shops, each listed once, best fit first. No rep calls a current stockist. In a month the team opens nine new accounts, and the shop in Ottensen orders its first box. Jonas’s team stopped calling the same shop four times. One call is enough now.
31fresh shops a week
0calls to stockists
9new accounts in a month
Blocks: Schedule → Area of interest → Nearby places → Map business scan → Remove duplicates → Match with my table → xMap LLM → Google Sheets
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Phone repair
The challenge. Elsa runs a phone repair shop on Södermalm in Stockholm. Cracked screens and tired batteries pay her rent. Seven repair shops sit within a short walk. When one of them slips, its customers go looking, and she finds out months later. Last spring a rival closed, and its regulars walked straight past her door to a chain store.
The flow. With xMap Flows, Elsa built Sentinel. Every morning at eight, across Södermalm, Sentinel searches the map for phone repair shops, spots any whose rating fell or that closed, explains what it means for her shop, and sends it to her phone on WhatsApp.
The result. In March, Sentinel tells her a rival’s rating fell from four point six to three point eight in two weeks. Elsa puts a same-day promise in her window and online. Within a month, twenty-three new customers mention the other shop by name. When a rival stumbles, Elsa’s door is already open.
7rival shops watched daily
3.8a rival’s rating, from 4.6
23customers who switched
Blocks: Schedule → Area of interest → Map business scan → What changed → xMap LLM → WhatsApp Business
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Luxury watches
The challenge. Nina manages the dealer network for a Swiss watch brand in Zurich. Two hundred shops sell its watches. Her dealer list is a spreadsheet that ages every day. Shops move, rename or quietly close, and the store finder keeps sending customers to them. A visitor from Tokyo once walked to an address that had become a bakery.
The flow. With xMap Flows, Nina built Meridian. Every Sunday night, Meridian reads the two hundred dealers, looks each one up on the map, spots any that closed, moved or changed their name, updates the dealer sheet, and emails the area manager.
The result. This week, Meridian finds two dealers closed and one moved across the Limmat. By Monday morning the sheet is right, and the store finder reads from it. Nina’s team spends the week selling watches, not checking addresses. Nina’s dealer list no longer ages. It wakes up right every Monday.
200dealers checked weekly
3changes caught this week
0wrong addresses online
Blocks: Schedule → My data → Map business scan → What changed → Google Sheets → Email
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Sneakers and streetwear
The challenge. Wei Ling leads retail marketing for a sneaker brand in Singapore. Every month she opens a pop-up store for a new drop. Choosing the spot is a gamble. Her team walks the malls, takes photos, and argues for a week. The last pop-up sat in a quiet corner of a brand new mall, and half the stock went back to the warehouse.
The flow. With xMap Flows, Wei Ling built Watchtower. On the first Monday of every month, from Orchard Road to Tampines, Watchtower finds the malls and food halls, keeps the ones with a high traffic score where people stay longest, picks the top five, explains why each one fits the drop, and turns it all into slides for the team.
The result. This month, Watchtower ranks five spots, with Bugis on top: people there stay well over an hour. The team agrees in one meeting instead of five. The pop-up sells out in nine days, a week faster than the last one. Wei Ling’s team stopped arguing about corners. Now they argue about restocking.
5spots ranked each month
1meeting, not five
9 daysto sell out the drop
Blocks: Schedule → Area of interest → Nearby places → Filter → Sort and limit → xMap LLM → Make a report
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Furniture
The challenge. Ava runs digital for a furniture brand with nine showrooms across Los Angeles. Shoppers see a sofa they like on the website, but they cannot tell which showroom has it. They send an email, wait a day for the answer, and lose interest. Of every hundred people who ask, only four ever walk into a showroom.
The flow. With xMap Flows, Ava built Host. When a visitor asks on the website, Host finds out what they love and where they live, checks which showroom nearby has it on the floor, books them a visit with a designer, and answers right there in the chat, in seconds.
The result. On Saturday, a couple in Santa Monica asks about a green velvet sofa. Host tells them it is on the floor in Venice, ten minutes away, and books them in at two. Now eighteen of every hundred who ask come in. Ava’s website stopped answering questions. It started opening doors.
9showrooms behind one chat
18in 100 now visit, from 4
Secondsto answer, not a day
Blocks: Chat → AI agent → My data → Google Calendar → Reply
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Souvenir shop
The challenge. Lucia runs a ceramics shop in Santa Cruz, the old quarter of Seville. Her best days are when a river cruise ship docks. Nobody tells her when they arrive. Some mornings two hundred passengers stream through the old town while her shop is still shut and her nephew is still asleep. Other days she opens early for nobody at all.
The flow. With xMap Flows, Lucia built Harbor. Every hour, at the river port, Harbor listens for the ships on the Guadalquivir, keeps the passenger ships, spots the moment one reaches the quay, and messages Lucia and her nephew on WhatsApp.
The result. At seven on Wednesday, Harbor tells her a cruise ship has reached the quay. Lucia opens at eight with fresh coffee and her nephew at the door. By noon, she has sold more tiles and plates than in the whole week before. Lucia no longer waits for the crowds. She is open when they step ashore.
Hourlychecks of the river port
8 amopen for the first guests
1 weekof sales by noon
Blocks: Schedule → Area of interest → Ships (AIS) → Filter → Zone alert → WhatsApp Business
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Local delivery
The challenge. Yi-ting runs a small family delivery company in Taipei, with six drivers and orders from three online shops. Every morning she prints the orders and splits them by hand. The same customer often orders from two shops, so two drivers climb to the same flat. Some drivers get all the far stops in Neihu, others finish by noon, and arguments start before nine.
The flow. With xMap Flows, Yi-ting built Swift. Every morning at seven, Swift takes the day's orders from all three shops, keeps one stop for each address, splits the city into six fair areas, one for each driver, plans each driver's route in the best order, and puts every route in the drivers' shared sheet.
The result. This morning there are one hundred and forty orders. Swift finds eighteen going to a door already on the list, so the drivers make one hundred and twenty two stops, about twenty each. Everyone finishes by four, and nobody argues. Yi-ting used to referee her drivers. Now she just waves them off.
18double stops saved
20stops for each driver
0 minsorting by hand
Blocks: Schedule → My data → Remove duplicates → Split by territory → Route planner → Google Sheets
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