Agentic analytics for marketplaces

Find the marketplace revenue leaks before sellers notice.

Bicycle watches seller GMV, listing quality, take rate, and fulfillment SLA across the segments that matter. When a number moves, it explains the likely cause and recommends the next action to the team that can fix it.

No credit card required

retail / seller GMV agentAgent live
Detect
GMV per active seller
Electronics · APAC tier-1 · last 7d
-22%vs 4-week seller average
Explain · likely causes, ranked
  • 1Listing quality dropped on the account's top-selling itemshigh
  • 2Product feed broke on the last catalogue synccontributing
  • 3Price moved outside the buy-box range on three categoriescontributing
business causetechnical cause
Act · recommended next step
Recommend to merchant success: fix the listing content and the broken feed on the affected account, with the categories, the channel, and the GMV at risk. Scoped, previewed, logged.
Evidence: listing content · feed health logs · price and buy-box history · availability · fulfilment SLA · order data

A dashboard shows the drop. Bicycle finishes the investigation and recommends the fix.

Where marketplace revenue breaks

Start with a single revenue KPI critical to your business.

Bicycle comes with marketplace industry intelligence already inside. Pick one Bicycle-recommended KPI and watch it run: the KPI it watches, the causes it checks, the action it recommends to the owner, and what it keeps.

Pick a revenue problem
Seller GMV Agent Drop
Seller GMVElectronics · APAC seller cohort −22%vs 4-week seller average
Top seller GMV drop · Electronics · APAC
D · DetectDetect · what moved
Seller GMV crossed −18% below 4-week cohort average. Triggered at 09:14 for APAC electronics segment.
Seller GMV monitor · Electronics · APAC tier-1 sellers
Alert · Seller GMVjust now
Electronics · APAC seller cohort−22%
SignalSeller GMV crossed −18% below 4-week cohort average. Triggered at 09:14 for APAC electronics segment.
Seller GMV monitor · Electronics · APAC tier-1 sellersSubscribe
E · ExplainExplain · why it moved
Price gap
Pricing svc
Top-3 competitor listings now 12% cheaper on the same ASIN; seller price not updated in 6 days
Listing suppression
Catalog svc
Two top SKUs suppressed from search results due to missing compliance attributes added last week
Buy-box loss
Buy-box engine
Seller lost buy-box on 38 SKUs after price gap exceeded the marketplace price threshold
Confidence
High
Ruled out
demand signal normal for segmentno logistics issues reportedseller inventory levels adequate
Cause summaryranked
1Top-3 competitor listings now 12% cheaper on the same ASIN; seller price not updated in 6 days
2Two top SKUs suppressed from search results due to missing compliance attributes added last week
Ruled outdemand signal normal for segment · no logistics issues reported
High confidence
A · ActAct · what to do next
Notify seller account manager with price gap and suppression evidence
Slack
auto · audit-only
Flag missing compliance attributes to catalog team for fast-track review
Catalog svc
preview · 1-click
Request seller to update pricing on affected SKUs with gap analysis attached
Seller portal
approval required
Owner: Merchant success team
PreviewApproval
Action previewMerchant success team
Notify seller account manager with price gap and suppression evidenceSlack
Flag missing compliance attributes to catalog team for fast-track reviewCatalog svc
PreviewApproval
L · LearnLearn · what the loop keeps
Accepted cause saved: Price gap and listing suppression are the two leading GMV loss drivers for electronics sellers; now auto-checked on weekly cadence. Add compliance attribute check to new-SKU onboarding gate to prevent suppression at launch.
Decision memory · routed to Merchant success team
Saved to memorysaved
Accepted causePrice gap and listing suppression are the two leading GMV loss drivers for electronics sellers; now auto-checked on weekly cadence
Next runAdd compliance attribute check to new-SKU onboarding gate to prevent suppression at launch
starts from the answer
Setup
1
Rapid activation
Seller feeds, GMV, listing, orders, fulfillment, payments, already connected. No rebuild.
2
Vertical native context
Speaks seller, SKU, GMV, category, listing quality, take rate. Answers in marketplace language.
Detect
3
Always-on KPI intel
Watches GMV at seller and category level. Surfaces concentration risk before the weekly review.
Explain
4
Multi-factor cause
Checks listing quality, price, availability, fulfillment SLA, feed health, and demand signal together.
5
Defensible answers
Every finding names the seller, the SKU, the root cause, and the source. No guessing.
Act
6
Governed actions
Routes to merchant success or partner ops with the driver evidence attached.

A marketplace problem not listed here? Book a demo and we will map it.

The cost of finding out late

A dashboard shows the drop. It never finishes the investigation.

Before Bicycle

Seller GMV drops on a key account. The manual chase begins.

The dashboard shows the drop. The team still checks listings, feeds, pricing, and fulfilment by hand, across four tools, while the QBR gets closer.

  1. Account team pulls the merchant's category cuts
  2. Catalogue checks listing content by hand
  3. Engineering checks whether the feed ran
  4. Pricing compares against the buy box
  5. Nobody can answer it before the QBR
Hours to days. Revenue keeps leaking.
With Bicycle

Bicycle starts the investigation the moment the KPI moves.

It detects the drop, ranks the affected keywords and cities, tests business and technical causes in parallel, attaches the evidence, and routes the issue to the owner with the next step.

  1. Detect the movement, ranked by impact
  2. Test business and technical causes together
  3. Attach the evidence, rule out the rest
  4. Route the safe action to the owner
  5. Learn the accepted cause for next time
Minutes. The owner gets the cause and the move.
Capabilities · purpose-built for retail

Trained on the KPIs, patterns, and root causes of retail.

Six capabilities, set up once and run continuously. Business teams move faster, analysts keep governance, everyone trusts the number. Pick one to go deeper.

Multi-factor cause analysis

"What caused this?" turns into a three-day Slack thread across data, product, ops, and engineering, and the answer still arrives without evidence.

What Bicycle does

1

Open the cause summary. Ranked business and technical causes. The likely driver is named, with confidence and impact.

2

See the evidence. Logs, deploys, pricing changes, supplier behavior, and search relevance, with the data attached.

3

Know what was ruled out. The negative findings close the debate before it starts.

What it looks like for your team

In practice

"Mobile checkout dropped 4% on iOS." Cause: Apple Pay button failing since 9:42am, release v4.18.2. Ruled out: pricing, inventory, promo, weather.

Capabilities work together in one continuous loop. Detect → Explain → Act → Learn.

Who runs this in retail

Business teams need answers fast. Analysts ensure conclusions are trustworthy.

Same governed intelligence underneath. The retail agent for the teams who own the number, the controls for the team who owns the data.

Business teams · act on it

See what changed, why, and what is safe to do.

The move finds you, ranked by revenue impact, with the cause and the next step attached. No dashboard hunt, no three-day ticket.

Data & Analytics · keep it trusted

Govern the definitions, evidence, and safe actions.

Analysts review first-pass causes instead of rebuilding them. Leaders give the business self-service inside one governed boundary.

What Bicycle becomes for your retail operation

The agentic analytics layer on top of your stack.

Your stack stays the system of record. Bicycle turns retail signals into alerts, triage, stories, dashboards, chat, and governed actions on top of it. No rip-and-replace.

Bicycle the agentic layer
Surfaceswhat business teams touch
AlertsTriageStoriesDashboardsChatActions
Governancethe self-serve safety rail
access · approved definitions · evidence · audit · rollback
AgentsAI · your business analyst

Frames the question, orchestrates the investigation, writes the story, recommends the next step. It reasons.

Search conversionInventory availabilityPromo profitabilityReturn spikeCheckout friction
IntelligenceAutoML · your data analyst

Detects movement, ranks drivers, computes confidence, forecasts. The numbers are calculated, not generated.

Pattern EngineCause EngineDriver TreesForecastingImpact Ranking
Business modelthe semantic layer
SKUCategoryStoreCitySearch termBasketOrderInventoryPromo
Connectorsthe bridge, in and out
Signal Cause Action Knowledge
reads ↑ · acts ↓ · Bicycle sits on top
Your stack · system of record
SnowflakeBigQuerydbtEcommerce eventsOrders & catalogPricingObservabilitySlackJiraBI+ more

And the rest of what you run: warehouse · ecommerce events · catalog · pricing · observability · BI · Slack

Bicycle runs on top of your existing systems. The retail pack supplies the starting KPIs, causes, stories, and action paths.

Vibe Analytics · self-serve start

Start with one KPI in your marketplace stack.

Bring one revenue-critical KPI, connect a trusted source, and watch Bicycle turn a prompt plus your data into a marketplace analytics agent. Zero to a working agent in about 15 minutes.

Prompt + data
"Watch GMV per active seller by category and region, and tell me why it moves."
Snowflake · connected
Analytics agent
Builds the model, detects movement, tests business and technical causes.
Outputs
AnswerStoryAlert
Teams usually start withGMV concentrationListing qualityTake-rate drift

Grow into the full product when your team is ready.

Test ride Bicycle on a marketplace KPI.

Bring one KPI that matters. We will show how Bicycle detects the move, explains the cause, and recommends the next step on top of the stack you already run.

No credit card required