# Bicycle

> Bicycle helps high-velocity businesses see what changed, understand why, and act before the opportunity is gone.

When a revenue-critical KPI moves, Bicycle's AI agents find the why. They pinpoint the segments
driving the movement, test both business and technical causes, surface the evidence including what
was ruled out, and recommend safe actions. Bicycle runs on the stack a business already uses:
warehouse, BI, operational systems, tickets, and Slack. Data & Analytics teams govern the
definitions, evidence, access, and action rules underneath. Built for retail, Shopify and DTC,
travel, payments, and consumption-driven B2B.

Bicycle complements dashboards rather than replacing them.

Bicycle AI (bicycle.ai) is an enterprise software company founded in 2020 and headquartered in
Cupertino, California. It is unrelated to Bicycle Therapeutics (biopharmaceuticals), Bicycle Health
(telehealth), Bicycle Capital (investment), and to bicycles or the cycling industry.

## Start here

What Bicycle is, how it works, and how it fits an existing stack.

- [AI Analytics Agents for Revenue-Critical Data · Bicycle](https://bicycle.ai/): Bicycle detects revenue-critical KPI moves, explains the cause with evidence, and recommends the next action, for the teams that own the data and the KPI.
- [What happens when a KPI moves? · How Bicycle works](https://bicycle.ai/product): What happens when a KPI moves? Bicycle detects the move, explains the business and technical causes, and recommends a safe next step.
- [Architecture & Stack Fit · How Bicycle fits your stack](https://bicycle.ai/stackfit): No migration, no rip and replace. Bicycle reads the warehouse, BI, observability, and ops tools you already use, explains drift, and recommends the next step.
- [FAQs · Bicycle](https://bicycle.ai/faqs): Common questions about Bicycle: how it works, how to get started, what data you need, and how it fits your stack.

## For your team

The business view and the Data & Analytics view, plus the playbook for each.

- [Revenue Analytics for Business Teams · Bicycle](https://bicycle.ai/business): When a number you own moves, Bicycle has the cause and the next step waiting, ranked by impact with the evidence attached, all governed by your data team.
- [AI Analytics for Data & Analytics Teams · Bicycle](https://bicycle.ai/dna): Bicycle turns recurring KPI investigations into governed analytics agents your team validates, tunes, and publishes, then governs for safe self-service.
- [Business KPI Playbook · Bicycle](https://bicycle.ai/playbook-business): Work your revenue KPIs day to day: know what changed, understand why with the evidence, and act inside the guardrails your data team set.
- [Data & Analytics Playbook · Set Up Bicycle](https://bicycle.ai/playbook-dna): Connect and model the data once, tune how Bicycle detects and explains change, and set the guardrails that let the business self-serve on defensible numbers.

## By industry

- [Solutions by industry and role · Bicycle](https://bicycle.ai/solutions): Bicycle for retail, Shopify, travel and payments. 24 roles that own a number and get asked why it moved, each with the KPIs, patterns and systems behind it.
- [Revenue Analytics for Retail · Bicycle](https://bicycle.ai/retail): Bicycle watches retail conversion, availability, pricing, promo, and checkout KPIs, explains the cause with evidence, and recommends the next action.
- [Revenue Analytics for Shopify · Bicycle](https://bicycle.ai/shopify): Bicycle watches Shopify conversion, campaigns, availability, and returns, explains the cause with evidence, and recommends the next action.
- [Revenue Analytics for Travel · Bicycle](https://bicycle.ai/travel): When bookability or look-to-book conversion slips, Bicycle ranks the cause with evidence and recommends the next action, for travel teams that own the funnel.
- [Revenue Analytics for Payments · Bicycle](https://bicycle.ai/payments): When approval rate dips or settlement drifts, Bicycle ranks the cause with evidence and recommends the next action, for the payments teams that own the number.

## How Bicycle compares

Where Bicycle sits against dashboards, chatbots, warehouse AI, and building in-house.

- [Bicycle vs Dashboards: Tableau, Looker, Power BI · Bicycle](https://bicycle.ai/product-vs-dashboards): Dashboards render what happened and wait to be read. Bicycle detects the KPI move, explains the cause with evidence, and recommends the next action.
- [Bicycle vs Analytics Chatbots: Beyond Text-to-SQL · Bicycle](https://bicycle.ai/product-vs-chatbots): Conversational analytics waits to be asked, then guesses an answer. Bicycle watches every KPI, finds the cause from statistics, and answers before you ask.
- [Bicycle vs Warehouse AI: Cortex, Genie, BigQuery · Bicycle](https://bicycle.ai/product-vs-warehouse-ai): Warehouse AI ships SQL and a model endpoint. Bicycle adds the cause engine, vertical context, and governance across your whole stack, not just the warehouse.
- [Bicycle vs Build-Your-Own AI Analyst on an LLM · Bicycle](https://bicycle.ai/product-vs-build-own): An LLM wired to your warehouse demos well. Bicycle is the cause engine, governance, and connectors it never will be, as a product you don't build or own.

## Use cases

Grouped by the KPI that moved.

- [Use cases: find why a KPI moved · Bicycle](https://bicycle.ai/use-cases): From stockouts to settlement spikes: see how Bicycle detects a KPI the moment it moves, finds the cause and recommends the next step.
- [Booking anomaly alerts without false positives · Bicycle](https://bicycle.ai/use-case-anomaly-alert-false-positives): Most booking alerts are noise. Bicycle tests every candidate driver against seasonality and supplier shifts before an alert fires, so the few that arrive are real.
- [Approval rate drop: find the cause · Bicycle](https://bicycle.ai/use-case-approval-rate-drop): You shipped a new model on Tuesday and approvals dropped on Wednesday. Bicycle ties each approval shift to the model, rule or change behind it.
- [Booking failures by airline · Bicycle](https://bicycle.ai/use-case-booking-failures-by-airline): Bookings for one airline start failing more than usual. Bicycle compares booking success per airline and point of sale to its baseline and names the pattern.
- [Broken links on offer pages: find them first · Bicycle](https://bicycle.ai/use-case-broken-offer-links): Today's best deal links to an error page. Bicycle checks every published offer link each day and flags the broken ones before customers click.
- [Daily sales reporting by rep · Bicycle](https://bicycle.ai/use-case-daily-sales-reporting): Your reps sell every day and need yesterday's numbers by morning. Bicycle delivers daily sales by rep and product line that match your CRM and finance.
- [Dark store productivity: find the slow store · Bicycle](https://bicycle.ai/use-case-dark-store-productivity): Two dark stores, same orders, one is far slower. Bicycle shows where time goes in each store, by associate and job, and names the reason.
- [Fare-drop alerts that bring searchers back · Bicycle](https://bicycle.ai/use-case-fare-drop-alerts): A traveler searched a flight and the fare dropped two days later. Bicycle detects fare moves per route and date and triggers the alert that brings them back.
- [Fulfillment delays by step: find the slow one · Bicycle](https://bicycle.ai/use-case-fulfillment-delays-by-step): A delivery promise breaks at one step. Bicycle tracks every step from order to doorstep against its own target and names why it slipped.
- [Slow hotel booking decline: find it early · Bicycle](https://bicycle.ai/use-case-hotel-booking-decline): Half a percent a day looks like noise. Over weeks it is real revenue. Bicycle finds slow declines in hotel bookings and splits them into causes you can fix.
- [Invoice exception triage into cases · Bicycle](https://bicycle.ai/use-case-invoice-exception-triage): Millions of processing events a day and a handful need attention. Bicycle triages invoice failures and opens cases, bringing people in only where needed.
- [Kiosk funnel drop-off analysis · Bicycle](https://bicycle.ai/use-case-kiosk-funnel-drop-off): Kiosk conversion slips by a fraction. Bicycle finds the exact mix of location, device, software and network behind the drop, the same day.
- [KPI insights for product managers · Bicycle](https://bicycle.ai/use-case-kpi-stories-for-product-managers): Dozens of product managers, one analytics team. Bicycle sends each product manager the story behind their own KPIs when they move.
- [Margin per load: detect overpaid carriers · Bicycle](https://bicycle.ai/use-case-margin-per-load): A carrier was just paid more than the lane supports. Bicycle flags margin problems on each order before the transaction closes.
- [Marketing ROI and customer acquisition cost by channel · Bicycle](https://bicycle.ai/use-case-marketing-roi-by-channel): You know what each channel costs. Bicycle shows your customer acquisition cost and return by channel, campaign and segment, in one view.
- [Marketing performance vs forecast by channel · Bicycle](https://bicycle.ai/use-case-marketing-vs-forecast): Forty markets, six channels, three devices. Bicycle finds which combination missed forecast, and by how much, every week.
- [Online orders failing at the POS · Bicycle](https://bicycle.ai/use-case-online-orders-failing-at-pos): The order was placed and the kitchen never saw it. Bicycle finds where orders fail between the delivery app and the POS, and the main cause.
- [Order turnaround time by store · Bicycle](https://bicycle.ai/use-case-order-turnaround-time): Orders are on time on average. Bicycle computes turnaround for every store and city each day and flags the ones slowing down, with the slow step.
- [Out-of-stock root cause analysis · Bicycle](https://bicycle.ai/use-case-out-of-stock-root-cause): Find why each stockout happened, before the customer does. Bicycle tags every stockout with its cause and recommends the fix to the team that owns it.
- [Partner booking drops: detect them the same day · Bicycle](https://bicycle.ai/use-case-partner-booking-drops): One partner's bookings halve and your total barely moves. Bicycle watches bookings for every partner and alerts the team the day one drops.
- [Predict late deliveries before pickup · Bicycle](https://bicycle.ai/use-case-predict-late-deliveries): An order will miss its pickup window tomorrow. Bicycle predicts at-risk orders every day and recommends a carrier fix while there is still time.
- [Promotion profitability: did it make money? · Bicycle](https://bicycle.ai/use-case-promotion-profitability): The promotion sold well, but did it make money? Bicycle tracks promotion profit against plan while it runs and names what is pulling it down.
- [Real-time conversion drop alerts · Bicycle](https://bicycle.ai/use-case-real-time-conversion-alerts): Your warehouse tells marketing about yesterday. Bicycle watches web conversion as it happens and checks each drop against outside causes like weather.
- [Search conversion drop: find the cause · Bicycle](https://bicycle.ai/use-case-search-conversion-drop): Searches are up but purchases are down. Bicycle finds the keywords, locations and products behind a search conversion drop and names the cause.
- [Settlement rate spikes by merchant · Bicycle](https://bicycle.ai/use-case-settlement-rate-spikes): One missing field downgrades thousands of transactions. Bicycle finds settlement and interchange rate spikes by merchant every day and names the gap behind each.
- [Stockouts by region: find where availability breaks · Bicycle](https://bicycle.ai/use-case-stockouts-by-region): Overall availability can look healthy while one region keeps running out. Bicycle tracks every region separately and names the regional cause.
- [Store shown offline on delivery apps · Bicycle](https://bicycle.ai/use-case-store-offline-on-delivery-apps): Your location is open but the delivery app says closed. Bicycle flags stores and menu items wrongly shown unavailable, with the likely cause.
- [Supplier outage, lost bookings: switch off fast · Bicycle](https://bicycle.ai/use-case-supplier-outage-lost-bookings): A supplier starts failing at peak. Bicycle detects the degradation within minutes and recommends shifting traffic away before bookings are lost.

## Customers and results

- [Our Customers · Bicycle](https://bicycle.ai/customers): See how retail, payments, and travel leaders use Bicycle to turn real-time data into action, with named results from bigbasket, Billtrust, ACERTUS, and more.
- [An automotive logistics provider Case Study · Bicycle](https://bicycle.ai/case-automotive-logistics-provider): How an automotive logistics provider uses Bicycle to detect operational anomalies in real time, protect margin, and improve on-time delivery.
- [Billtrust Case Study · Bicycle](https://bicycle.ai/case-billtrust): How Billtrust uses Bicycle to analyze payment settlement in real time, prevent revenue leakage, and act on interchange issues before they reach customers.
- [A leading retailer Case Study · Bicycle](https://bicycle.ai/case-dark-store-productivity-ops-intelligence): How a leading retailer unifies warehouse and workforce data with Bicycle to see where dark store productivity is slipping and why, in minutes not days.
- [A fintech firm Case Study · Bicycle](https://bicycle.ai/case-fintech-firm): How a fast-growing fintech firm uses Bicycle to unify fragmented marketing data, gain complete campaign visibility, and see true ROI across every channel.
- [A fintech innovator Case Study · Bicycle](https://bicycle.ai/case-fintech-innovator): How a fintech innovator uses Bicycle to monitor underwriting workflows in real time, detect anomalies in approval rates, and uncover root causes across teams.
- [A global online travel agency Case Study · Bicycle](https://bicycle.ai/case-global-ota): How a global online travel agency uses Bicycle to monitor flight prices across tens of millions of daily searches and boost booking conversions.
- [A Global OTA Case Study · Bicycle](https://bicycle.ai/case-global-ota-hotel-trend-analytics): How a global OTA uses Bicycle to detect slow-building hotel booking trends across millions of listings and protect revenue before drift becomes visible.
- [A global OTA Case Study · Bicycle](https://bicycle.ai/case-global-ota-supplier-circuit-breaker): How a global online travel agency uses Bicycle to detect supplier degradation in real time and route flight traffic to healthier suppliers before bookings fail.
- [A leading online retailer Case Study · Bicycle](https://bicycle.ai/case-leading-online-retailer): How a leading online retailer uses Bicycle to detect out-of-stock risk in real time, find root causes, and act before top SKUs go unavailable.
- [A quick commerce retailer Case Study · Bicycle](https://bicycle.ai/case-quick-commerce-otd-anomaly-intelligence): How a quick-commerce retailer uses Bicycle to monitor the delivery journey, detect SLA risk in real time, and surface root causes before customers feel it.
- [Case Studies · Bicycle](https://bicycle.ai/case-studies): Bicycle case studies from retail, payments, and travel: how teams prevent revenue leakage, resolve issues faster, and act on KPI movement in real time.
- [UrbanPiper Case Study · Bicycle](https://bicycle.ai/case-urbanpiper): How UrbanPiper uses Bicycle to detect store availability and order-processing issues in real time, cutting resolution from days to hours.

## Try it

- [Vibe Analytics · The fastest path into Bicycle](https://bicycle.ai/vibe-analytics): Vibe coding let anyone build. Vibe Analytics lets anyone decide: a prompt plus your data becomes a working agent for the KPI you own.
- [Connect Snowflake to Bicycle: a working KPI agent in 15 minutes](https://bicycle.ai/snowflake): Point Bicycle at Snowflake with a read-only connection. It reads your schema, proposes agents, and builds the data model in about 15 minutes. Queries run in place on your warehouse.

## Writing

- [Bicycle AI Blogs | Retail, Payments, Travel & Agentic Analytics Insights](https://bicycle.ai/blogs): Writing from the Bicycle team on revenue leaks, operations, and agentic analytics across retail, travel, and payments.
- [AI in Payment Operations: The Human-in-the-Loop Framework](https://bicycle.ai/blog/ai-in-payment-operations-where-humans-are-still-critical): AI can compress a payments firefight but it can't replace the judgment calls. Here's the framework for deciding what to automate and what to keep human.
- [eCommerce Revenue Leakage During Promotions: 5 Hidden Risks](https://bicycle.ai/blog/an-ecommerce-leaders-guide-to-revenue-leakages-during-promotions): Promotions can leak revenue in five places at once. How ecommerce leaders detect and close those leaks while the campaign is still running.
- [Dashboard Theater: Why Dashboards Miss Revenue Leaks](https://bicycle.ai/blog/dashboard-theater-what-we-miss-in-revenue-firefighting): Dashboards reveal that revenue is leaking but not where, why, or how to fix it. See where dashboard theater fails and what should replace it.
- [2026 Retail & eCommerce Revenue Leak Benchmark | Bicycle AI](https://bicycle.ai/blog/ecommerce-retail-revenue-leakage-benchmark-report-2026): We surveyed retail and eCommerce leaders (158 responses). 50.6% notice a revenue leak within an hour; 16.5% fix it that fast. See where recovery stalls.
- [eTail 2026: What Retail Leaders Told Us | Bicycle](https://bicycle.ai/blog/etail-2026-retail-leaders-challenges): Bicycle.ai's takeaways from eTail 2026: the five pain points retail and ecommerce leaders raised most often, and how AI analytics is changing the answer.
- [Fix Omnichannel Complexity to Protect Retail Margin](https://bicycle.ai/blog/how-omnichannel-complexity-quietly-drains-retail-margin--and-what-the-best-ops-teams-do-differently): Omnichannel chaos drains retail margin. See how leading ops teams simplify decisions and how Bicycle AI enables faster, smarter retail operations.
- [How Bicycle AI Prevents Payment Revenue Leaks with Agentic Analytics](https://bicycle.ai/blog/how-payment-revenue-leaks-and-how-to-stop-it): Discover how agentic analytics finds hidden payment revenue leaks, pinpoints root causes, and recommends real-time fixes to protect approval rates and profit.
- [Retail Revenue-Leak Prevention with Agentic Analytics](https://bicycle.ai/blog/how-retail-revenue-leaks-and-how-to-stop-it): Retail revenue leaks through small cracks: inventory gaps, promo errors, payment failures. How AI agents detect them in time to act.
- [AI in Retail: The Smart Way to Prevent Stockouts and Overstock](https://bicycle.ai/blog/how-stockouts-and-overstock-quietly-drain-retail-revenue--and-what-the-best-ops-teams-do-differently): Stockouts cut sales and overstock drains margin. Bicycle AI helps retail ops teams detect, explain, and act quickly to stop revenue leaks before they compound.
- [Stop Hidden Travel Revenue Leaks with Agentic Analytics](https://bicycle.ai/blog/how-travel-revenue-leaks-and-how-to-stop-it): How travel brands catch hidden revenue leaks across fares, inventory, and payments, before they reach conversion or margin.
- [The Metrics That Matter in Revenue Firefighting | Bicycle](https://bicycle.ai/blog/metrics-that-matter-in-revenue-firefighting): Time to visibility tells you instrumentation works. Time to full resolution tells you whether your business actually recovers revenue before it leaks.
- [Modern BI Buyer's Guide: Evaluate Platforms That See, Explain & Act](https://bicycle.ai/blog/modern-bi-buyers-guide-how-to-choose-tools-that-see-explain-and-act): Choosing a modern BI or analytics tool is about outcomes, not feature counts. Fifteen practical criteria that separate dashboards from tools that explain and act.
- [Retail Operations Intelligence: How Top Teams Turn Data Into Action](https://bicycle.ai/blog/retail-operations-intelligence-from-dashboards-to-decisions): See how top retail teams move beyond dashboards with AI agents that detect and fix issues in inventory, pricing, and store operations instantly
- [The 7 Deadly Traps in Revenue Operations | Bicycle AI](https://bicycle.ai/blog/seven-revenue-leak-traps-revops-leaders-miss): Revenue leaks rarely come from one big failure. Seven revenue operations traps that drain revenue quietly, and how to detect and diagnose each one.
- [Hidden Costs of Building Retail Ops AI](https://bicycle.ai/blog/the-hidden-cost-of-building-your-own-retail-ops-ai--and-when-its-worth-it): Discover the hidden costs of DIY retail ops AI. Learn when building makes sense and how Bicycle AI helps teams scale smarter.
- [Traditional BI vs Agentic Analytics: What Actually Moves Revenue?](https://bicycle.ai/blog/traditional-bi-vs-agentic-analytics): Discover how traditional BI compares to agentic analytics in driving real-time revenue growth. Learn when to use each and boost your business impact with proven examples
- [Travel Leader's Guide to High-Latency Incidents | Bicycle](https://bicycle.ai/blog/travel-leaders-guide-to-high-latency-incidents): High-latency incidents quietly cost travel revenue. A guide to spotting supplier, cache, app, and payment delays before bookings disappear.
- [Agentic Analytics Explained: Full Guide with Bicycle Use Cases](https://bicycle.ai/blog/what-is-agentic-analytics-bicycle-ais-take-on-analytics-that-acts): What agentic analytics means, how it differs from dashboards and chatbots, and worked examples of analytics that recommends the next step.
- [Revenue Operations: Who Owns This Leak? | Bicycle](https://bicycle.ai/blog/who-owns-this-anyway-revenue-operations): Revenue leaks rarely match the org chart, so ownership stalls while teams hand off. See how connecting signal, cause, and owner turns debate into action.

## Webinars

On-demand recordings with Bicycle leaders.

- [The 7 Deadly Revenue Traps in Revenue Operations | Bicycle AI Webinar](https://bicycle.ai/webinars/7-deadly-revenue-traps): Bhaskar Sunkara and Sasha Pilch on the hidden revenue gaps that slow teams down, and how AI helps teams move from what happened to how to fix. Watch on demand.
- [Everything’s working. So why are we losing money? | Bicycle AI Webinar](https://bicycle.ai/webinars/everythings-working): Bhaskar Sunkara and Greg Howard walk through three true ecommerce stories where the site was up, the dashboards were green, and revenue was still leaking. Watch on demand.
- [How Retail Revenue Leaks (And How AI Stops Them in Real Time) | Bicycle AI Webinar](https://bicycle.ai/webinars/how-retail-revenue-leaks): Bhaskar Sunkara shows how a 24x7 AI Analyst helps retail teams catch revenue leaks from out-of-stock gaps, payment friction, promos and fulfillment in real time. Watch on demand.

## Newsroom

Research, product updates and company news, by edition.

- [Newsroom · Bicycle](https://bicycle.ai/newsroom): The Bicycle newsroom: research, product updates and company news, collected by edition. Newest first.
- [Newsroom: Edition 01, September 2026 · Bicycle](https://bicycle.ai/newsroom-edition-01): Edition 01 of the Bicycle newsroom: new benchmark research, a clip from the Everything's working webinar, and connecting Bicycle to Snowflake or BigQuery.
- [Newsroom: Edition 02, October 2026 · Bicycle](https://bicycle.ai/newsroom-edition-02): Edition 02 of the Bicycle newsroom: why analytics accuracy comes from the definitions, not the model, the KPIs it applies to, and a walkthrough of Bicycle on BigQuery.

## By role

Role-specific views, scoped by industry.

- [Payments Analytics for Approval & Acquiring · Bicycle](https://bicycle.ai/payments-role-analytics): Bicycle turns recurring approval-rate investigations into governed agents your team validates once and reuses every time the rate moves on an acquirer.
- [Data Engineering for Payments · Bicycle](https://bicycle.ai/payments-role-data-engineering): Data engineering analytics for payments that separate real KPI movement from data noise, catch the artifact before it reaches the board, and route the fix.
- [Merchant Operations Analytics, Payments · Bicycle](https://bicycle.ai/payments-role-merchant-operations): Merchant operations analytics that flag chargeback spikes by merchant, separate config drift from routing anomalies, and recommend the fix before it compounds.
- [Payment Operations Analytics for Payments · Bicycle](https://bicycle.ai/payments-role-payment-operations): Payment operations analytics that catch PSP success drops, separate issuer degradation from gateway latency, and recommend the reroute before conversion dips.
- [Risk & Approval Analytics, Payments · Bicycle](https://bicycle.ai/payments-role-risk-approval): Risk and approval analytics that catch approval-rate shifts after a model deploy, separate segment shift from model effect, and recommend the next step.
- [Interchange Analytics for Payments · Bicycle](https://bicycle.ai/payments-role-scheme-interchange): Interchange analytics that catch downgrade-rate moves, separate card-mix from routing-rule drift, and recommend the fix before settlement closes.
- [Analytics Engineering for Retail · Bicycle](https://bicycle.ai/retail-role-analytics-engineering): Analytics engineering for retail that separates business movement from data noise and catches the artifact before it triggers a false-alarm panic.
- [BI & Data Analytics for Retail · Bicycle](https://bicycle.ai/retail-role-bi-analysts): BI and data analytics for retail that rank revenue's real driver with proof, so you answer the exec's question before it is asked, on a governed definition.
- [Category Analytics for Retail · Bicycle](https://bicycle.ai/retail-role-category-managers): Category analytics that explain why margin moved, separate promo depth from mix shift, and recommend the fix before your category review.
- [Digital & Product Analytics for Retail · Bicycle](https://bicycle.ai/retail-role-digital-product-analytics): Bicycle turns recurring retail checkout-completion investigations into governed agents your team validates once and reuses every time the funnel moves.
- [Ecommerce Analytics for Retail · Bicycle](https://bicycle.ai/retail-role-ecommerce-analysts): Bicycle turns recurring retail search-conversion investigations into governed agents your team validates once and reuses every time a KPI moves.
- [Site Merchandising Analytics, Retail · Bicycle](https://bicycle.ai/retail-role-ecommerce-merchandising): Site merchandising analytics that tell you whether a conversion drop is stock, search, or checkout, rank the cause, and recommend the fix.
- [Marketplace Account Analytics, Retail · Bicycle](https://bicycle.ai/retail-role-marketplace-accounts): Marketplace account analytics that explain a merchant GMV drop, separate listing quality from a broken feed, and recommend the fix before the QBR.
- [Merchandise Planning Analytics, Retail · Bicycle](https://bicycle.ai/retail-role-merchandise-planning): Merchandise planning analytics that catch fill-rate slips, separate demand spikes from late POs, and recommend the fix before the shelf empties.
- [Shopify Commerce Analytics & ShopifyQL · Bicycle](https://bicycle.ai/shopify-role-commerce-analytics): Bicycle turns recurring Shopify variant-revenue investigations into governed agents your team validates once and reuses every time a SKU moves.
- [Shopify Post-Purchase & WISMO Analytics · Bicycle](https://bicycle.ai/shopify-role-commerce-operations): Shopify post-purchase analytics that catch WISMO and late-delivery spikes early, rank the cause, and recommend the proactive fix for commerce ops.
- [Shopify Marketing Analytics & Attribution · Bicycle](https://bicycle.ai/shopify-role-marketing-analytics): Govern every campaign-to-revenue answer on Shopify Plus. Bicycle ties ads, discounts, landing pages, and Klaviyo to revenue with lineage your team can defend.
- [Conversion Recovery for Revenue & Marketing · Bicycle](https://bicycle.ai/shopify-role-revenue-marketing): Conversion recovery analytics for Shopify revenue and marketing: catch stalled promoted styles, rank the leak, and recommend the recovery flow while live.
- [Booking Operations Analytics, Travel · Bicycle](https://bicycle.ai/travel-role-booking-operations): Booking operations analytics that unblock the funnel, separate promo-validation blocks from gateway handoffs, and recommend the fix before the day slips.
- [Data Analytics for Travel · Bicycle](https://bicycle.ai/travel-role-data-analytics): Bicycle turns recurring travel bookability investigations into governed agents your team validates once and reuses every time a KPI moves.
- [Travel Product Analytics · Bicycle](https://bicycle.ai/travel-role-product-analytics): Bicycle turns recurring booking-funnel investigations into governed agents your team validates once and reuses every time conversion moves on a route.
- [Revenue Management Analytics, Travel · Bicycle](https://bicycle.ai/travel-role-revenue-management): Revenue management analytics that catch underpriced routes, separate competitor moves from stale fare feeds, and recommend the reprice before yields slip.
- [Search & Funnel Analytics for Travel · Bicycle](https://bicycle.ai/travel-role-search-funnel-analytics): Bicycle turns recurring travel search and funnel investigations into governed agents your team validates once and reuses every time look-to-book moves.
- [Supplier Operations Analytics, Travel · Bicycle](https://bicycle.ai/travel-role-supplier-operations): Supplier operations analytics that catch rejection spikes, separate allocation caps from API errors by route, and recommend the right throttle fast.

## By segment

Sub-industry views, scoped by industry.

- [Card Network Analytics · Bicycle](https://bicycle.ai/payments-sv-card-networks): Card network analytics that flag interchange, scheme fee, and chargeback leaks before month close, rank the cause, and recommend the next action.
- [Payment Gateway and PSP Analytics · Bicycle](https://bicycle.ai/payments-sv-gateways-psps): Payment gateway and PSP analytics that surface authorization, decline, and settlement leaks, rank the cause, and recommend the fix.
- [Payment Orchestration Analytics · Bicycle](https://bicycle.ai/payments-sv-orchestration-platforms): Payment orchestration analytics that surface routing, failover, and PSP auth leaks, rank the likely cause, and recommend the next action.
- [Fashion Specialty Revenue Analytics · Bicycle](https://bicycle.ai/retail-sv-fashion-specialty): Fashion specialty analytics that catch sell-through, return, and markdown leaks before the season closes, rank the cause, and recommend the fix.
- [Marketplace Revenue Analytics · Bicycle](https://bicycle.ai/retail-sv-marketplaces): Marketplace analytics that surface seller GMV, listing quality, take rate, and fulfillment SLA leaks, rank the cause, and recommend the fix.
- [Quick-Commerce Revenue Analytics · Bicycle](https://bicycle.ai/retail-sv-quick-commerce): Quick-commerce analytics that surface zone order rate, delivery SLA, and dark-store availability leaks, rank the cause, and recommend the fix.
- [Airline and Hotel Direct Analytics · Bicycle](https://bicycle.ai/travel-sv-airline-hotel-direct): Airline and hotel direct analytics that catch conversion, loyalty, and rate-parity leaks before OTAs do, rank the cause, and recommend the fix.
- [Car Rental Analytics · Bicycle](https://bicycle.ai/travel-sv-car-rental): Car rental analytics that catch fleet utilisation, rate yield, and depot availability leaks early, rank the cause, and recommend the fix.
- [Global OTA Revenue Analytics · Bicycle](https://bicycle.ai/travel-sv-global-otas): Global OTA analytics that surface search-to-book, cancellation, and supplier availability leaks, rank the cause, and recommend the fix.
- [Metasearch Revenue Analytics · Bicycle](https://bicycle.ai/travel-sv-metasearch): Metasearch revenue analytics that surface revenue-per-search, feed, and bid leaks before they compound, rank the cause, and recommend the fix.

## Optional

Company and legal pages. Lower priority for understanding what Bicycle does.

- [About Bicycle · Agentic Analytics for High-Velocity Teams](https://bicycle.ai/about-us): About Bicycle: agentic analytics that help high-volume retail, payments, and travel teams turn real-time data into action. Our mission, team, and offices.
- [Bicycle AI Webinars | Agentic Analytics for Retail, Payments & Travel](https://bicycle.ai/webinar): Join Bicycle AI webinars to learn how agentic analytics helps retail, payments, and travel teams reduce revenue leakage and act in real time.
- [Privacy Policy · Bicycle](https://bicycle.ai/legal-privacy): How Bicycle collects, uses, shares, and protects your personal information, and the rights you have under GDPR, UK GDPR, and the CCPA.
- [Subprocessors · Bicycle](https://bicycle.ai/legal-subprocessors): The Subprocessors Bicycle has engaged to provide processing activities on Customer Data as defined in the Bicycle Data Processing Agreement.