Agentic analytics · for marketing analytics
Flag campaign underperformance in time to make course corrections.
When campaign-to-revenue slips, the questions land on your queue: which campaign, which creative, which landing page. Bicycle assembles the ranked causes and the lineage so the answer is defensible the first time.
Cursor multiplied what one engineer could do. Bicycle does the same for your analysts.
No credit card required
Detect
Explain
Review
The operating model is breaking
The force multiplier for your marketing analysts.
Faster onboarding, fewer repeat investigations, and decisions backed by evidence, with your team governing every definition, answer, and action.
Without Bicycle
With Bicycle
repeat
The same campaign questions come back to your queue every week
Campaign revenue slips, ROAS dips, paid-traffic conversion drops, and you re-stitch ad spend, discounts, landing pages, and Klaviyo from zero.
reuse
You build each investigation once, then reuse it
Tune the driver tree once; Bicycle reruns it every time that KPI moves, with the evidence already attached.
sprawl
Every new campaign and channel adds more to model
More campaigns, more KPI definitions, more dashboards, more ad-hoc "why is this down?" asks landing on your queue.
one model
New campaigns inherit one governed model
New campaigns and channels inherit approved KPIs, patterns, and cause paths instead of starting from a blank cut.
shadow
Revenue and Marketing build shadow analytics while they wait
Side spreadsheets and ad-hoc queries on spend and revenue, with no lineage, no review, no shared definition.
self-serve
Revenue and Marketing self-serve inside guardrails
They get answers with lineage on the campaign KPIs they own; you keep definitions, permissions, and actions governed.
blamed
You own the number but get blamed for the delay
Accountable for whether the campaign-revenue number is right and for clearing the queue, at the same time.
both
Trusted answers, delivered faster than the asks arrive
The recurring queue moves faster than the questions come in, and every published answer is defensible.
The capabilities
One governed system, six capabilities behind every answer.
Set up once, run continuously. Each capability is reviewable and governed by your team, so the business self-serves on a number it can trust. Pick one to go deeper.
Capabilities work together in one continuous loop. Detect → Explain → Act → Learn.
The playbookBuild · Tune · Govern
Your team builds the intelligence layer once. Bicycle runs it, tunes it, and lets you govern it as it scales.
Buildthe trusted foundation
→
Tunethe intelligence layer
→
Governself service and safe actions
A day in the lifeFirst pass by Bicycle · the call is yours
Retail investigation queue
The morning review starts with the first pass done.
Campaign revenue dropped on a paid-traffic push. Bicycle has already checked the segments, ranked the likely causes, attached the evidence, and kept the definition governed. Your team reviews the answer, publishes the story, and tunes what should happen next time.
Campaign revenue · Promo push · paid trafficTop segment below baseline. Affected segment and evidence already assembled for analyst review.
Queue · alerts needing review
HighCampaign revenue droppedPromo push · paid traffic2.3%-1.8pp vs baselineTop segmentPromo push · paid traffic$58Kat riskRevenue & Marketingowning team8:42 AM
MedAdd to cart rate downAll devices · Paid traffic5.6%-0.7pp vs baselineTop segmentPaid traffic · US$31Kat riskGrowth Marketingowning team8:15 AM
MedPayment success rate downAll devices · Credit cards92.1%-1.2pp vs baselineTop segmentCredit cards · US$44Kat riskPaymentsowning team7:02 AM
LowInventory in-stock droppedShoes · 3 warehouses94.3%-0.3pp vs baselineTop segmentShoes · West region$12Kat riskInventoryowning team6:55 AM
+ 4 alerts · 1 high · sorted by revenue at risk
SnoozeOpen investigationTriaged to one segment · Promo push · paid traffic
2.3% conversion
baseline 4.1% · ▼1.8pp · returning users · high volume
1 of 6 segments affected · 5 within expected range
Likely driversranked · confidence
Campaign points to an old collectionprimary82%
Collection no longer lists the SKUsecondary74%
Creative fatigueruled out
Recommended actionsscoped
Create a ticket on Jirascoped
Alert #retail-revenue on Slackscoped
Publish corrected-link flowpreview
scoped · previewed · reversible · logged
+ Detected 8:42 · first pass 8:43 · top segment Promo push · paid traffic
Adjust modelApprove & publishImpact overview
2.3%
conversion rate · -1.8pp vs baseline 4.1%
1.24Maffected users
5.83Msessions
Top affected segments
1
Promo push · paid · US
-1.8pp2
Promo push · paid · West
-1.2pp3
Promo push · returning users
-0.9ppEvidence attached
Funnel trendPDP to purchase
Channel mixpaid vs organic
Collection linkold vs current
Catalog changeSKU delisted @ 2:15 AM
Ruled out · not drivers
Price changesno overlap with window
Promo changeseligibility unchanged
Creative fatigueunchanged
New vs returningboth affected equally
Definition governed · Source read-only · sources fresh
+ Reviewed by analyst on duty · 8:51 AM
Send backConfirm evidenceYour conclusion84% confidence
Campaign revenue dropped for the Promo push on paid traffic, primarily because the campaign points to an old collection. The collection no longer listing the SKU is a secondary contributor.
Recommended next steps
1Publish the corrected-link flow to the campaign and offer.
2Monitor campaign revenue and the collection link.
3Repoint the campaign and set a collection-link guardrail.
Attach & sharegoverned
Impact summary
Evidence bundle
Next steps
Share with
Ecom leadershipEcommerce OpsGrowth Marketing+2
+ Published to Slack · #retail-revenue · 8:54 AM
Save draftApprove & publishBicycle applied your approved playbook.
Detected pattern
Old-collection impact
→
Applied playbook
campaign revenue
→
Likely driver
Old collection link
→
Recommended action
Publish corrected link
Caught 74 min earlier · 7:28 AM vs 8:42 AM on the first run
No re-investigation · pattern auto-applied, analyst review optional
+ Memory: Shopify campaign-revenue playbook · run 2
ReviewView playbookMore roles on Bicycle · same loopYour team's KPI · your screens
Different teams own different metrics. Bicycle keeps the investigation governed.
Move from this marketing analytics view to the Shopify Plus workflows around SKU and variant trust, conversion recovery, and post-purchase operations.
Vibe Analytics
Build your first governed investigation.
Start with one recurring metric in your queue: why checkout conversion, payment success, or activation moved. Bicycle watches the governed KPI, checks likely causes across the warehouse, payments, app & web, and events, and hands your team a reviewable first pass.
What to bring
A recurring investigation: checkout conversion, payment success, search conversion, or activation rate.
An approved read-only path to the relevant sources: the warehouse, event streams, app & web, payments, or ad networks.
The KPI definition, default segments, and reviewers who decide what becomes trusted.
What we do
Configure the investigation path around your KPI, segments, and evidence rules.
Monitor device, OS, channel, region, and segment movement.
Prepare a first-pass cause analysis with evidence, ruled-out paths, and governed definitions.
No credit card required · analyst-reviewed · governed from day one