{"p":"analyst","persona":["analyst","Investors, analysts & consultants","Investors, analysts and consultants who need location numbers they can trust, on a schedule."],"industry":{"slug":"investors-consultants","name":"Investors & consultants"},"templates":{"people":{"name":"Who lives around new places","desc":"Every week: the new cafes in your city, with the people living within 1 km of each (men, women, age groups), the busiest areas first.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"08:00"}],["aoi","My city",{"mode":"Cities","cities":[{"kind":"city","name":"Toronto","label":"Toronto","lat":43.6532,"lng":-79.3832}]}],["gscan","New cafes",{"cats":["Caf\u00e9s"],"max":"50"}],["onlynew","Only new ones",{}],["demog","People within 1 km",{"where":"Each incoming place","radius":"1 km"}],["sort","Most people first",{"by":"Another field","fname":"population","dir":"Highest first (Z to A)"}],["email","Email me the list",{"kind":"One email per run","subj":"New cafes and who lives around them"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[5,6]]},"an_market_size":{"name":"Market size of a category across cities","desc":"Every month: every coffee shop across five cities, counted per city with chains and independents, a market note from xMap AI, saved to a sheet and emailed.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["aoi","The cities",{"mode":"Cities","cities":[{"kind":"city","name":"New York","label":"New York","lat":40.7128,"lng":-74.006},{"kind":"city","name":"Chicago","label":"Chicago","lat":41.8781,"lng":-87.6298},{"kind":"city","name":"Los Angeles","label":"Los Angeles","lat":34.0522,"lng":-118.2437},{"kind":"city","name":"Houston","label":"Houston","lat":29.7604,"lng":-95.3698},{"kind":"city","name":"Miami","label":"Miami","lat":25.7617,"lng":-80.1918}]}],["nearby","Every coffee shop",{"types":["Coffee shop","Cafe"],"where":"Area of interest","order":"Nearest first","max":"500","cover":true}],["dedupe","Each one once",{"by":"Same place, job or incident (recommended)"}],["llm","Write the market note",{"scope":"The whole list","task":"Write summary","prompt":"Write a market note: the number of coffee shops in each city, the share of chains and independents, the average rating, and what stands out.","out":"report"}],["ap_google-sheets","Save the data to a sheet",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["email","Email me the list",{"kind":"One email per run","subj":"Coffee market this month"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[4,6]]},"an_new_openings_db":{"name":"New openings into my database","desc":"Every week: places that opened in the last six months across your cities, only the new ones, classified, saved to your own database for your models.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"08:00"}],["aoi","My cities",{"mode":"Cities","cities":[{"kind":"city","name":"London","label":"London","lat":51.5074,"lng":-0.1278},{"kind":"city","name":"Dubai","label":"Dubai","lat":25.2048,"lng":55.2708}]}],["nearby","New openings",{"types":["Restaurant","Coffee shop","Gym","Supermarket"],"where":"Area of interest","order":"Best rated first","max":"300","since":"Last 6 months","cover":true}],["onlynew","Only new ones",null],["classify","Classify them",{"tax":"Custom list","labels":"Food and drink, Retail, Fitness, Other"}],["dbwrite","Save to my database",{"table":"xmap_places","mode":"Add or update by a key","key":"place_id"}],["email","Email me the list",{"kind":"One email per run","subj":"New openings saved this week"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[4,6]]},"an_visit_route":{"name":"Store visit route for a due diligence trip","desc":"Every Monday: the branches of the chain you are studying in the city you visit, the strongest and the weakest marked by xMap AI, put in the best order to visit them by car from your hotel, with directions, and a visit plan with what to ask at each, emailed with a map.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"07:00","tz":"Europe/Madrid"}],["aoi","City of the visit",{"mode":"Cities","cities":[{"kind":"city","name":"Madrid","label":"Madrid","lat":40.4168,"lng":-3.7038}]}],["nearby","Branches to visit",{"types":["Fast food","Fast food restaurant","Hamburger restaurant"],"where":"Area of interest","order":"Best rated first","max":"12","chain":"Only chains"}],["llm","Mark the strongest and the weakest with xMap AI",{"task":"Score & rank","prompt":"Score each branch from 0 to 100 on how healthy it looks from its rating and number of reviews, so the visits cover both the strongest and the weakest. Explain in one sentence.","out":"fit_score, reason"}],["route","The best order to visit them",{"reps":"One route","mode":"Car","back":true,"max":"12","start":[{"kind":"place","name":"Hotel","label":"Hotel, Madrid","lat":40.4168,"lng":-3.7038}]}],["llm","Write the visit plan",{"scope":"The whole list","task":"Write summary","prompt":"For the due diligence team, in about 200 words: the branches in visit_order, one short line each on what to look at (the strongest and the weakest by fit score), then three questions to ask every manager. The directions link is in the email.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"This week\u2019s branch visits"}],["map","Show them on a map",{"name":"Branch visits","color":"Fit score"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[5,6],[5,7]]},"an_hiring_index":{"name":"Monthly hiring index for a sector","desc":"Every month: job postings in a sector across your cities, one per company, counted and summarised by xMap AI as a hiring index, saved to a sheet and emailed.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["aoi","The cities",{"mode":"Cities","cities":[{"kind":"city","name":"London","label":"London","lat":51.5074,"lng":-0.1278},{"kind":"city","name":"Dubai","label":"Dubai","lat":25.2048,"lng":55.2708},{"kind":"city","name":"Cairo","label":"Cairo","lat":30.0444,"lng":31.2357}]}],["jobs","Postings in the sector",{"kw":"logistics","where":"Area of interest","posted":"Last 30 days","limit":"100","details":true}],["dedupe","One per company",{"by":"Another field","fname":"company"}],["llm","Write the hiring index",{"scope":"The whole list","task":"Write summary","prompt":"Write a short hiring index note: how many companies are hiring in each city, the most common roles, and whether it signals growth.","out":"report"}],["ap_google-sheets","Save the postings",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["email","Email me the list",{"kind":"One email per run","subj":"Hiring index this month"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[4,6]]},"an_port_activity":{"name":"Port activity snapshot","desc":"Every day: the ships in a port area (live AIS), grouped by type and whether they are moving, a short activity note from xMap AI, saved to a sheet.","n":[["sched","Every day at noon",{"time":"12:00","tz":"Europe/Amsterdam"}],["aoi","Rotterdam port area",{"mode":"Draw on a map","shapes":{"type":"FeatureCollection","features":[{"type":"Feature","properties":{},"geometry":{"type":"Polygon","coordinates":[[[3.95,51.88],[4.35,51.88],[4.35,52.02],[3.95,52.02],[3.95,51.88]]]}}]}}],["ships","Ships in the port",{"where":"Area of interest","listen":"90 seconds"}],["llm","Write the activity note",{"scope":"The whole list","task":"Write summary","prompt":"Write a short port activity note: how many ships by type, how many are moving or waiting, and anything unusual.","out":"report"}],["ap_google-sheets","Save the snapshot",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["email","Email me the list",{"kind":"One email per run","subj":"Port activity today"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_city_profiles":{"name":"Demographic profile of each city","desc":"Every quarter: the people living in each of your cities (men and women, age groups, density), saved to a sheet and summarised by xMap AI.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["aoi","The cities",{"mode":"Cities","cities":[{"kind":"city","name":"Toronto","label":"Toronto","lat":43.6532,"lng":-79.3832},{"kind":"city","name":"Vancouver","label":"Vancouver","lat":49.2827,"lng":-123.1207},{"kind":"city","name":"Montreal","label":"Montreal","lat":45.5019,"lng":-73.5674},{"kind":"city","name":"Calgary","label":"Calgary","lat":51.0447,"lng":-114.0719}]}],["demog","Who lives in each city",{"where":"Area of interest"}],["llm","Compare the cities",{"scope":"The whole list","task":"Write summary","prompt":"Compare these cities: population, density, share of children and seniors, and what each profile means for consumer businesses.","out":"report"}],["ap_google-sheets","Save the profiles",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["email","Email me the list",{"kind":"One email per run","subj":"City profiles"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_brand_sentiment":{"name":"Brand sentiment, branch by branch","desc":"Every month: every branch of a brand in your cities, how customers rate each judged by xMap AI from its rating and number of reviews, the weakest branches first, emailed and mapped by review score.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["aoi","My cities",{"mode":"Cities","cities":[{"kind":"city","name":"London","label":"London","lat":51.5074,"lng":-0.1278},{"kind":"city","name":"Dubai","label":"Dubai","lat":25.2048,"lng":55.2708}]}],["nearby","The brand\u2019s branches",{"types":["Fast food restaurant"],"where":"Area of interest","order":"Nearest first","max":"200","brand":"McDonald's","cover":true}],["llm","Rate how customers see them, with xMap AI",{"task":"Score & rank","prompt":"Score each place from 0 to 100 on how well its customers rate it: its rating out of 5 and how many reviews it has (many reviews make a rating more certain; a high rating on few reviews counts less). Say in one sentence where it stands against the others in the list.","out":"review_score, reason"}],["sort","Weakest branches first",{"by":"Another field","fname":"review_score","dir":"Lowest first (A to Z)","keep":"The first 20"}],["email","Email me the list",{"kind":"One email per run","subj":"Brand sentiment by branch"}],["map","Show them on a map",{"name":"Branches by review score","color":"Category"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[4,6]]},"an_portfolio_watch":{"name":"Ratings of my portfolio companies\u2019 branches","desc":"Every week: each branch of your portfolio companies on the map, rating changes and closures, what each change means from xMap AI, saved to your database and emailed.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"08:00"}],["mydata","Portfolio branches",null],["gscan","Find each branch",{"area":"Around each incoming place","find":"Each place itself","radius":"300","opened":"Any time"}],["changes","Rating and closures",{"watch":["Closed","Rating"]}],["llm","What it means",{"task":"Write summary","prompt":"In one sentence, say what this change means for the portfolio company and whether the deal team should follow up.","out":"impact"}],["dbwrite","Save to my database",{"table":"xmap_places","mode":"Add or update by a key","key":"place_id"}],["email","Email me the list",{"kind":"One email per run","subj":"Portfolio branches that changed"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[4,6]]},"an_competitor_density":{"name":"Competitor density around each site","desc":"Every month: for each site in your list, the competitors and the people within 1 km, people per competitor worked out, scored by xMap AI, ranked and saved to a sheet.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["mydata","My sites",null],["nearby","Competitors around each",{"types":["Restaurant","Coffee shop","Fast food restaurant"],"where":"Each incoming place","radius":"1 km","give":"Each incoming place, with counts"}],["demog","Who lives around",{"where":"Each incoming place","radius":"1 km"}],["calc","People per competitor",{"lines":"people_per_competitor = round({{population}} / ({{nearby_count}} + 1))"}],["llm","Score each site",{"task":"Score & rank","prompt":"Score each site from 0 to 100 on the room it leaves for a new player, from the people per competitor and the competitors\u2019 ratings. Explain in one sentence.","out":"fit_score, reason"}],["sort","Best 50 first",{"by":"Fit score","dir":"Highest first (Z to A)","keep":"The first 50"}],["ap_google-sheets","Save the table",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["email","Email me the list",{"kind":"One email per run","subj":"Competitor density by site"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[5,6],[6,7],[6,8]]},"an_research_chat":{"name":"Research assistant over live location data","desc":"A chat for your analysts: they ask about a place, an AI agent looks up the people, the businesses around it and live job postings, and answers with the numbers.","n":[["chat","Chat",{"title":"Location research","welcome":"Ask me about any area: who lives there, what businesses are around and who is hiring."}],["agent","Research assistant",{"goal":"You help analysts research places. Use Who lives around it, Businesses around it and Job postings as the question needs, then answer with the numbers in short lines and one sentence of interpretation. Say clearly when data is missing."}],["demog","Who lives around it",{"where":"A point","center":"{{agent: the place to look at}}","radius":"1 km"}],["nearby","Businesses around it",{"where":"A point","center":"{{agent: where to look, as the place the person named}}","types":["Restaurant","Supermarket","Bank","Coworking space"],"radius":"2 km","order":"Best rated first","max":"20"}],["jobs","Job postings",{"kw":"{{agent: the job title the person wants}}","where":"A location","loc":"{{agent: the city the person named}}","posted":"Last 30 days","limit":"20","details":false}],["reply","Reply",{"text":"{{reply}}","give":"The answer and the items"}]],"e":[[0,1],[1,2,"tool"],[1,3,"tool"],[1,4,"tool"],[1,5]]},"an_market_entry":{"name":"Market entry study, refreshed monthly","desc":"Every month: every place of a category across four cities, grouped by chain and independent, the people around them, an AI agent profiling the strongest areas, a market entry memo from xMap AI, saved to a sheet and your database, and emailed.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00"}],["aoi","The cities",{"mode":"Cities","cities":[{"kind":"city","name":"Mumbai","label":"Mumbai","lat":19.076,"lng":72.8777},{"kind":"city","name":"Delhi","label":"Delhi","lat":28.7041,"lng":77.1025},{"kind":"city","name":"Bangalore","label":"Bangalore","lat":12.9716,"lng":77.5946},{"kind":"city","name":"Chennai","label":"Chennai","lat":13.0827,"lng":80.2707}]}],["nearby","Every gym",{"types":["Gym","Fitness center"],"where":"Area of interest","order":"Nearest first","max":"400","cover":true}],["dedupe","Each one once",{"by":"Same place, job or incident (recommended)"}],["classify","Chain or independent",{"tax":"Custom list","labels":"International chain, Local chain, Independent"}],["demog","Who lives around",{"where":"Each incoming place","radius":"1 km"}],["sort","Best 20 first",{"by":"Another field","fname":"population","dir":"Highest first (Z to A)","keep":"The first 20"}],["agent","Profile the strongest areas with the AI agent",{"goal":"You advise on market entry. For each of the densest areas, use your tools to see how customers rate the gyms there and who lives around, then write three lines on the opportunity for a new brand.","msg":"Profile the area around {{name}}.","memory":"None","steps":"6","out":"area_profile"}],["demog","Who lives around it",{"where":"Each incoming place","radius":"2 km"}],["llm","Write the market entry memo",{"scope":"The whole list","task":"Write summary","prompt":"Write a one-page market entry memo: market size by city, chain versus independent share, the most promising areas and the main risks.","out":"report"}],["ap_google-sheets","Save the data",{"action":"insert_row","per":"Once per item","inputs":{"spreadsheetId":"","sheetId":"","first_row_headers":true,"values":{}}}],["dbwrite","Save to my database",{"table":"xmap_places","mode":"Add or update by a key","key":"place_id"}],["email","Email me the list",{"kind":"One email per run","subj":"Market entry study this month"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[5,6],[6,7],[7,9],[9,10],[9,11],[9,12],[7,8,"tool"]]},"an_chain_vs_independent":{"name":"Chains against independents, city by city","desc":"Every quarter: cafes in several cities, split into chains and independents with their average rating, in a report by xMap AI for a consumer research brief.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Europe/London"}],["aoi","Cities to compare",{"mode":"Cities","cities":[{"kind":"city","name":"London","label":"London","lat":51.5074,"lng":-0.1278},{"kind":"city","name":"Paris","label":"Paris","lat":48.8566,"lng":2.3522},{"kind":"city","name":"Berlin","label":"Berlin","lat":52.52,"lng":13.405},{"kind":"city","name":"Madrid","label":"Madrid","lat":40.4168,"lng":-3.7038}]}],["nearby","Cafes",{"types":["Cafe","Coffee shop"],"where":"Area of interest","order":"Nearest first","max":"500"}],["llm","Write the comparison",{"scope":"The whole list","task":"Write summary","prompt":"For a consumer research brief: in each city, the share of chain against independent cafes, their average ratings, and what it says about the market.","out":"report"}],["ap_google-drive","Save the report to Google Drive",{"action":"create_new_gdrive_file","per":"Once per run","inputs":{"fileName":"","text":"","fileType":"text/csv"}}],["email","Email me the results",{"kind":"One email per run"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_store_closures_index":{"name":"Monthly store closures index","desc":"Every month: the shops in your watch table that closed since last month, counted by city and kind, in a short index note by xMap AI for the research newsletter.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"America/New_York"}],["mydata","Shops we track",null],["gscan","Each shop on the map",{"area":"Around each incoming place","find":"Each place itself","radius":"300","opened":"Any time"}],["changes","Closed since last month",{"watch":["Closed"]}],["llm","Write the closures index",{"scope":"The whole list","task":"Write summary","prompt":"For the newsletter: how many tracked shops closed this month by city and kind, against last month, in five lines.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Store closures index"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]},"an_luxury_footprint":{"name":"Luxury brands\u2019 store footprint","desc":"Every quarter: luxury fashion and jewellery stores in the world\u2019s shopping capitals, by city, with a note by xMap AI on where brands are expanding.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Asia/Dubai"}],["aoi","Shopping capitals",{"mode":"Cities","cities":[{"kind":"city","name":"Dubai","label":"Dubai","lat":25.2048,"lng":55.2708},{"kind":"city","name":"Paris","label":"Paris","lat":48.8566,"lng":2.3522},{"kind":"city","name":"Tokyo","label":"Tokyo","lat":35.6762,"lng":139.6503},{"kind":"city","name":"New York","label":"New York","lat":40.7128,"lng":-74.006},{"kind":"city","name":"Shanghai","label":"Shanghai","lat":31.2304,"lng":121.4737}]}],["nearby","Luxury stores",{"types":["Jewelry store","Boutique","Watch store"],"where":"Area of interest","order":"Best rated first","max":"300"}],["classify","Sort by kind",{"tax":"Custom list","labels":"Jewellery, Watches, Fashion, Leather goods"}],["llm","Write the footprint note",{"scope":"The whole list","task":"Write summary","prompt":"For the luxury analyst: how many luxury stores each city has by kind, and where expansion seems to be happening.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Luxury footprint this quarter"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]},"an_ev_charging_index":{"name":"EV charging density across cities","desc":"Every quarter: electric vehicle charging stations in each city, with people per charger, in a ranked table by xMap AI for an energy transition report.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Europe/Oslo"}],["aoi","Cities to compare",{"mode":"Cities","cities":[{"kind":"city","name":"Oslo","label":"Oslo","lat":59.9139,"lng":10.7522},{"kind":"city","name":"Amsterdam","label":"Amsterdam","lat":52.3676,"lng":4.9041},{"kind":"city","name":"Munich","label":"Munich","lat":48.1351,"lng":11.582},{"kind":"city","name":"Copenhagen","label":"Copenhagen","lat":55.6761,"lng":12.5683},{"kind":"city","name":"Stockholm","label":"Stockholm","lat":59.3293,"lng":18.0686}]}],["nearby","Chargers",{"types":["Electric vehicle charging station"],"where":"Area of interest","order":"Nearest first","max":"500"}],["llm","Write the index",{"scope":"The whole list","task":"Write summary","prompt":"For an energy transition report: chargers per city, a rough people-per-charger figure, and which cities lead and lag.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"EV charging index"}],["map","Show them on a map",{"name":"Chargers","color":"One color"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_hospital_capacity":{"name":"Hospitals and the people they serve","desc":"Every year: hospitals in your country\u2019s cities with how many people live within 5 km of each, ranked from most stretched, for a healthcare investment memo.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Asia/Kolkata"}],["aoi","Cities",{"mode":"Cities","cities":[{"kind":"city","name":"Mumbai","label":"Mumbai","lat":19.076,"lng":72.8777},{"kind":"city","name":"Delhi","label":"Delhi","lat":28.7041,"lng":77.1025}]}],["nearby","Hospitals",{"types":["Hospital"],"where":"Area of interest","order":"Best rated first","max":"150"}],["demog","Who lives around",{"where":"Each incoming place","radius":"5 km"}],["sort","Best 30 first",{"by":"Another field","fname":"population","dir":"Highest first (Z to A)","keep":"A number I choose","n":"30"}],["llm","Write the memo",{"scope":"The whole list","task":"Write summary","prompt":"For a healthcare investor: the hospitals serving the most people, where capacity looks most stretched, and the opportunity.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Hospital capacity memo"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5],[5,6]]},"an_coworking_market":{"name":"Coworking market across a region","desc":"Every quarter: coworking spaces in a region\u2019s main cities, their ratings and how many opened in the last year, in a report by xMap AI for a flexible office investor.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Asia/Singapore"}],["aoi","Region",{"mode":"Cities","cities":[{"kind":"city","name":"Singapore","label":"Singapore","lat":1.3521,"lng":103.8198},{"kind":"city","name":"Kuala Lumpur","label":"Kuala Lumpur","lat":3.139,"lng":101.6869},{"kind":"city","name":"Jakarta","label":"Jakarta","lat":-6.2088,"lng":106.8456},{"kind":"city","name":"Bangkok","label":"Bangkok","lat":13.7563,"lng":100.5018}]}],["nearby","Coworking spaces",{"types":["Coworking space"],"where":"Area of interest","order":"Nearest first","max":"300"}],["llm","Write the market note",{"scope":"The whole list","task":"Write summary","prompt":"For a flexible office investor: how many coworking spaces each city has, how many opened in the last year, their ratings, and where the market looks open.","out":"report"}],["ap_google-drive","Save the report to Google Drive",{"action":"create_new_gdrive_file","per":"Once per run","inputs":{"fileName":"","text":"","fileType":"text/csv"}}],["email","Email me the results",{"kind":"One email per run"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_job_skills_trends":{"name":"Which skills employers want this month","desc":"Every month: job postings for your sector in several cities, with the skills each asks for pulled out by xMap AI, and a trend report on the most wanted.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Asia/Kolkata"}],["aoi","Cities",{"mode":"Cities","cities":[{"kind":"city","name":"Bangalore","label":"Bangalore","lat":12.9716,"lng":77.5946},{"kind":"city","name":"Hyderabad","label":"Hyderabad","lat":17.385,"lng":78.4867},{"kind":"city","name":"Pune","label":"Pune","lat":18.5204,"lng":73.8567}]}],["jobs","Postings",{"kw":"data analyst","where":"Area of interest","posted":"Last 7 days","limit":"100","details":true}],["llm","Pull out the skills",{"task":"Extract fields","prompt":"List the main skills this posting asks for, comma separated.","out":"skills"}],["llm","Write the skills report",{"scope":"The whole list","task":"Write summary","prompt":"For a skills report: the ten most wanted skills this month, how they differ by city, and anything new.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Skills in demand this month"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]},"an_weekly_brief":{"name":"A weekly brief from your AI employees","desc":"Every Monday: a Market analyst reads everything your other AI employees found and writes the brief: openings, closures and strong fits by city against the week before, rivals\u2019 new branches near your stores, who is hiring. Charts and plain findings in a PDF, by email and in your Team inbox.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"08:00","tz":"Europe/London"}],["teamdata","What the team found this week",{"since":"Last 7 days","max":"12"}],["llm","Word the brief",{"scope":"The whole list","task":"Write summary","prompt":"Write the weekly brief for the management team from these findings: three short paragraphs, the most important first. Use only the figures given; never add a number.","out":"report"}],["pdfreport","The brief as a PDF",{"kind":"A report (A4)","title":"Weekly brief"}],["email","Email me the results",{"kind":"One email per run"}]],"e":[[0,1],[1,2],[2,3],[2,4]]},"an_satellite_activity":{"name":"Activity at industrial sites from space","desc":"Every month: the latest satellite picture of each factory, mine or port in your watch table, with an activity note by xMap AI, saved to your database for a research model.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"America/Chicago"}],["mydata","Sites we watch",null],["satellite","Latest picture of each site",{"where":"Each incoming place","radius":"1000","period":"Last 30 days","cloud":"20"}],["llm","Read the picture with xMap AI",{"task":"Write summary","prompt":"One line on visible activity at this site: stockpiles, vehicles, ships or construction, against what is normal.","out":"activity"}],["dbwrite","Save to my database",{"table":"xmap_places","mode":"Add or update by a key","key":"place_id"}],["email","Email me the results",{"kind":"One email per run"}]],"e":[[0,1],[1,2],[2,3],[3,4],[3,5]]},"an_franchise_density":{"name":"Fast food franchise density by city","desc":"Every quarter: branches of the big fast food brands in your cities, counted by brand, with people per branch, in a note by xMap AI for a franchise investor.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"America/Argentina/Buenos_Aires"}],["aoi","Cities",{"mode":"Cities","cities":[{"kind":"city","name":"Buenos Aires","label":"Buenos Aires","lat":-34.6037,"lng":-58.3816},{"kind":"city","name":"Cordoba","label":"Cordoba","lat":-31.4201,"lng":-64.1888},{"kind":"city","name":"Rosario","label":"Rosario","lat":-32.9442,"lng":-60.6505}]}],["nearby","Fast food branches",{"types":["Fast food restaurant"],"where":"Area of interest","order":"Nearest first","max":"500","chain":"Only chains"}],["dedupe","Each branch once",{"by":"Same place, job or incident (recommended)"}],["llm","Write the density note",{"scope":"The whole list","task":"Write summary","prompt":"For a franchise investor: branches by brand and city, which brands dominate, and where there is room for one more.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Fast food density"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]},"an_grocery_tiers":{"name":"Discount, mainstream and premium grocers, city by city","desc":"Every quarter: the supermarkets and grocery stores in the cities you compare, sorted by xMap AI into discount, mainstream and premium, with a note on how the mix differs between cities.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Europe/Berlin"}],["aoi","Cities to compare",{"mode":"Cities","cities":[{"kind":"city","name":"Berlin","label":"Berlin","lat":52.52,"lng":13.405},{"kind":"city","name":"Madrid","label":"Madrid","lat":40.4168,"lng":-3.7038},{"kind":"city","name":"Milan","label":"Milan","lat":45.4642,"lng":9.19}]}],["nearby","Supermarkets and grocers",{"types":["Supermarket","Discount supermarket","Grocery store","Gourmet grocery store"],"where":"Area of interest","order":"Best rated first","max":"120"}],["classify","Sort them into price tiers",{"tax":"Custom list","labels":"Discount, Mainstream, Premium"}],["llm","Write the market note",{"scope":"The whole list","task":"Write summary","prompt":"For the retail analyst: how many grocers each city has in each price tier, which chains lead each tier, and what the mix says about each market.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Grocery price tiers this quarter"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]},"an_hub_disruption":{"name":"Weekly disruption watch at logistics hubs","desc":"Every Monday: the week\u2019s weather and the road closures around the logistics hubs you follow, joined by xMap AI into a short risk note for supply chain clients.","n":[["sched","Every Monday",{"freq":"Every week","weekday":"Monday","time":"08:00","tz":"Europe/Amsterdam"}],["aoi","Logistics hubs",{"mode":"Cities","cities":[{"kind":"city","name":"Rotterdam","label":"Rotterdam","lat":51.9244,"lng":4.4777},{"kind":"city","name":"Singapore","label":"Singapore","lat":1.3521,"lng":103.8198},{"kind":"city","name":"Los Angeles","label":"Los Angeles","lat":34.0522,"lng":-118.2437}]}],["weather","Forecast for 7 days",{"where":"Area of interest","days":"7","what":["Temperature","Rain","Wind"]}],["incidents","Closures around the hubs",{"where":"Area of interest","types":["Road closures","Roadworks","Other incidents"]}],["llm","Write the risk note",{"scope":"The whole list","task":"Write summary","prompt":"For supply chain clients: the hubs where storms, heat or road closures may slow freight this week, how serious each looks, and what to watch.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Logistics hub disruption this week"}]],"e":[[0,1],[1,2],[1,3],[2,4],[3,4],[4,5]]},"an_nightlife_index":{"name":"Nightlife index across cities","desc":"Every quarter: bars, night clubs and late cafes in several cities, counted and rated, in an index by xMap AI for a hospitality investor.","n":[["sched","On the 1st of every month",{"freq":"Every month","monthday":"1","time":"08:00","tz":"Europe/Madrid"}],["aoi","Cities",{"mode":"Cities","cities":[{"kind":"city","name":"Madrid","label":"Madrid","lat":40.4168,"lng":-3.7038},{"kind":"city","name":"Barcelona","label":"Barcelona","lat":41.3874,"lng":2.1686},{"kind":"city","name":"Lisbon","label":"Lisbon","lat":38.7223,"lng":-9.1393},{"kind":"city","name":"Athens","label":"Athens","lat":37.9838,"lng":23.7275}]}],["nearby","Nightlife",{"types":["Bar","Night club","Pub","Cocktail bar"],"where":"Area of interest","order":"Nearest first","max":"500"}],["classify","Sort by kind",{"tax":"Custom list","labels":"Bar, Club, Pub, Cocktail bar"}],["llm","Write the nightlife index",{"scope":"The whole list","task":"Write summary","prompt":"For a hospitality investor: nightlife places per city by kind, their ratings, and which city looks most open for a new venue.","out":"report"}],["email","Email me the list",{"kind":"One email per run","subj":"Nightlife index"}]],"e":[[0,1],[1,2],[2,3],[3,4],[4,5]]}},"info":{"people":{"p":"analyst","ind":["Retail","Real estate","Food and drink"],"goals":["sites","leads"],"promise":"The new cafes in your city with the people living around each.","why":"An opening is only as good as the people around it. This flow shows both together, busiest areas first.","uses":["An investor tracking a category","A supplier prioritising new outlets","A planner checking demand"],"gets":["A weekly email"],"min":60},"an_market_size":{"p":"analyst","ind":["Finance","Consulting","Food and drink"],"goals":["data"],"promise":"Every coffee shop in five cities, counted and summarised every month.","why":"Market sizing usually takes days of desk research. This flow does it every month with the same method, so trends are real.","uses":["An investor looking at a category","A consultant sizing a market","A brand planning entry"],"gets":["A market note by email","A data sheet"],"min":480},"an_new_openings_db":{"p":"analyst","ind":["Finance","Consulting"],"goals":["data"],"promise":"New openings saved to your own database every week, classified.","why":"Analysts want raw data in their own models. This flow feeds your database with new openings on a schedule.","uses":["A data science team","A fund building signals","A research firm"],"gets":["Rows in your database","An email"],"min":120},"an_visit_route":{"p":"analyst","ind":["Finance","Consulting"],"goals":["data"],"promise":"The branches of a chain you are studying, the strongest and the weakest marked, in the best order to visit them.","why":"Site visits are the slowest part of commercial due diligence. This flow picks which branches to see and plans the day around them, with directions and what to ask at each.","uses":["A private equity deal team","A franchise buyer","A consultant on a market study"],"gets":["A visit plan by email","A map of the branches"],"min":90},"an_hiring_index":{"p":"analyst","ind":["Finance","Consulting"],"goals":["data","hiring"],"promise":"A monthly hiring index for a sector across cities.","why":"Hiring is a leading indicator of growth. A monthly index shows where a sector is expanding.","uses":["An economist","An investor tracking a sector","A government analyst"],"gets":["A note by email","A data sheet"],"min":240},"an_port_activity":{"p":"analyst","ind":["Finance","Logistics"],"goals":["data"],"promise":"A daily snapshot of port activity: ships by type, moving or waiting.","why":"Port activity tracks trade before official figures. A daily snapshot builds a series you can use.","uses":["A commodity analyst","A shipping investor","A trade economist"],"gets":["A note by email","A data sheet"],"min":20},"an_city_profiles":{"p":"analyst","ind":["Consulting","Retail","Finance"],"goals":["data"],"promise":"The demographic profile of each city, compared, every quarter.","why":"Comparing cities by who lives there is the first step of any market entry. The profiles land in one sheet.","uses":["A consultant comparing markets","A retailer choosing a city","A fund analyst"],"gets":["Profiles in a sheet","A comparison by email"],"min":240},"an_brand_sentiment":{"p":"analyst","ind":["Finance","Food and drink","Consulting"],"goals":["competitors","data"],"promise":"Every branch of a brand ranked by how customers rate it, weakest first.","why":"Branch-level ratings show operational problems before they show in sales.","uses":["An investor in a restaurant chain","A brand's operations team","A consultant"],"gets":["An email","A map by review score"],"min":300},"an_portfolio_watch":{"p":"analyst","ind":["Finance"],"goals":["data"],"promise":"Rating changes and closures at your portfolio companies' branches, weekly.","why":"Portfolio monitoring should not wait for quarterly reports. This flow flags problems as they happen.","uses":["A private equity firm","A lender","A franchise investor"],"gets":["Rows in your database","An email of changes"],"min":120},"an_competitor_density":{"p":"analyst","ind":["Consulting","Retail","Real estate"],"goals":["sites","data"],"promise":"People per competitor around each of your sites, ranked.","why":"Competition only matters relative to demand. People per competitor gives one comparable number per site.","uses":["A site selection consultant","A franchise investor","A retail analyst"],"gets":["A table in a sheet","An email"],"min":240},"an_research_chat":{"p":"analyst","ind":["Consulting","Finance"],"goals":["chat","data"],"promise":"A research chat over live people, business and hiring data.","why":"Quick questions about a place should get numbers, not a ticket to the data team.","uses":["A research team","A consultant in a client meeting","An investor screening an area"],"gets":["Answers in the chat"],"min":20,"runs":100},"an_market_entry":{"p":"analyst","ind":["Consulting","Finance"],"goals":["data"],"promise":"A market entry study refreshed every month: size, chains, demand, the best areas and the risks.","why":"A market entry study is usually a one-off that is stale in a quarter. This one refreshes itself monthly with the same method, so you see the market move.","uses":["A brand entering the Gulf","A consultant running an entry study","An investor screening a category"],"gets":["A market entry memo","A data sheet and your database","An email"],"min":600},"an_chain_vs_independent":{"p":"analyst","ind":["Consulting","Food and drink"],"goals":["data","competitors"],"promise":"Chains against independents in several cities.","why":"The share of chains tells how mature a market is. The comparison is ready each quarter.","uses":["A consumer research firm","A coffee brand entering a market","A franchise consultant"],"gets":["A report in Google Drive"],"min":240,"runs":1},"an_store_closures_index":{"p":"analyst","ind":["Consulting","Retail"],"goals":["data"],"promise":"Tracked shops that closed, as a monthly index.","why":"Closures are a lead signal for a retail economy. The index counts them each month.","uses":["A retail research firm","A business journalist","A credit analyst"],"gets":["An email"],"min":180,"runs":1},"an_luxury_footprint":{"p":"analyst","ind":["Consulting","Retail"],"goals":["data","competitors"],"promise":"Luxury stores in the shopping capitals, by kind.","why":"Where luxury brands open shows where wealth is going. The footprint is tracked each quarter.","uses":["A luxury analyst","A mall developer","A brand consultant"],"gets":["An email"],"min":240,"runs":1},"an_ev_charging_index":{"p":"analyst","ind":["Consulting","Energy"],"goals":["data"],"promise":"EV chargers per city, ranked.","why":"Charging density shows how fast cities electrify. The index compares them.","uses":["An energy research firm","A charging investor","A city sustainability office"],"gets":["An email with the list","A map of the results"],"min":240,"runs":1},"an_hospital_capacity":{"p":"analyst","ind":["Consulting","Health"],"goals":["data"],"promise":"Hospitals ranked by the people within 5 km.","why":"Stretched hospitals point to where investment is needed. The memo ranks them.","uses":["A healthcare investor","A development bank","A health ministry adviser"],"gets":["An email"],"min":240,"runs":1},"an_coworking_market":{"p":"analyst","ind":["Consulting","Real estate"],"goals":["data"],"promise":"Coworking spaces across a region, new and rated.","why":"Flexible offices grow city by city. The report shows where the market is open.","uses":["A flexible office investor","A coworking operator","A real estate consultant"],"gets":["A report in Google Drive"],"min":240,"runs":1},"an_job_skills_trends":{"p":"analyst","ind":["Consulting","Recruiting"],"goals":["data","hiring"],"promise":"The skills employers ask for most this month.","why":"Skills in demand shift every quarter. Reading the postings shows how.","uses":["A skills research team","A training provider","A labour market analyst"],"gets":["An email"],"min":240,"runs":1},"an_weekly_brief":{"p":"analyst","ind":["Consulting","Management"],"goals":["data"],"promise":"One brief a week from everything your AI employees found.","why":"Each employee sees its own corner. The brief puts them together, with the figures, so the team reads one page on Monday.","uses":["A head of strategy","A regional manager","An analyst"],"gets":["A PDF","An email","A Team inbox note"],"min":120,"runs":1},"an_satellite_activity":{"p":"analyst","ind":["Consulting","Manufacturing"],"goals":["data"],"promise":"Activity at industrial sites from space, into your database.","why":"Stockpiles and trucks show output before reports do. The notes feed your model.","uses":["A hedge fund\u2019s research team","A commodity analyst","A supply chain risk team"],"gets":["Rows in your database"],"min":120,"runs":1},"an_franchise_density":{"p":"analyst","ind":["Consulting","Food and drink"],"goals":["data","competitors"],"promise":"Fast food branches by brand and city.","why":"Franchise investors need to know who dominates where. The density note says.","uses":["A franchise investor","A QSR consultant","A mall leasing team"],"gets":["An email"],"min":180,"runs":1},"an_grocery_tiers":{"p":"analyst","ind":["Retail","Consulting"],"goals":["data","competitors"],"promise":"Grocers in each city sorted into price tiers.","why":"The share of discount and premium grocers says a lot about a market. The same count in every city makes them comparable.","uses":["A retail analyst","A consumer goods strategy team","A property investor"],"gets":["An email"],"min":240,"runs":1},"an_hub_disruption":{"p":"analyst","ind":["Logistics","Consulting"],"goals":["data","ops"],"promise":"Weather and road closures at logistics hubs, every week.","why":"Freight slows when storms and closures hit a hub. A weekly note lets clients plan before it happens.","uses":["A supply chain risk firm","A freight analyst","A procurement team"],"gets":["An email"],"min":90,"runs":4},"an_nightlife_index":{"p":"analyst","ind":["Consulting","Hospitality"],"goals":["data"],"promise":"Bars and clubs counted and rated across cities.","why":"Nightlife shows where young spending goes. The index compares cities.","uses":["A hospitality investor","A drinks brand","A city tourism analyst"],"gets":["An email"],"min":240,"runs":1}}}