Rent the Runway has identified customer retention as a key strategic priority for fiscal year 2026, leveraging a proprietary retention predictive model to experiment with targeted interventions.
Filing excerpt
We leverage a retention predictive model and analytics to identify and understand the relative importance of various drivers of loyalty and prioritize the interventions that have the highest probability of improving customer retention.
What this signalsFilings often name leadership changes, deals and spending plans.
Technologies
sec-10kcustomerChurnGet every 10-K signal for Rent the Runway and the companies you sell to, in the tools you already use.
Connect Autobound to Claude, Claude Code or Cursor with MCP. Then ask: “What changed at Rent the Runway this week?”
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This page shows a preview. The full sec-10k record in the Signal API and MCP can also have these 8 fields. Some fields are empty for some signals.
Company
linkedin_urlValue in the APIindustriesValue in the APIemployee_count_lowValue in the APIemployee_count_highValue in the APIrevenueValue in the APIdescriptionValue in the APISignal
signal_nameValue in the APIassociationValue in the APIGET /v1/signals/30e3e108-4b8e-44e8-926a-f02c6bc5c964 returns this record as JSON. POST /v1/companies/enrich returns every signal for renttherunway.com.
{
"signal_id": "30e3e108-4b8e-44e8-926a-f02c6bc5c964",
"signal_type": "sec-10k",
"signal_subtype": "customerChurn",
"detected_at": "2026-04-21T07:28:39.297+00:00",
"company": {
"name": "Rent the Runway",
"domain": "renttherunway.com"
},
"data": {
"detail": "Rent the Runway has identified customer retention as a key strategic priority for fiscal year 2026, leveraging a proprietary retention predictive model to experiment with targeted interventions. This focus on reducing churn creates opportunities for vendors with solutions in customer experience, personalization, and loyalty programs.",
"metrics": {
"timeframe": "next_year"
},
"summary": "Company focusing 2026 plans on improving customer retention and acquisition",
"excerpts": "We leverage a retention predictive model and analytics to identify and understand the relative importance of various drivers of loyalty and prioritize the interventions that have the highest probability of improving customer retention.",
"relevance": 0.9,
"sentiment": "negative",
"confidence": "high",
"source_url": "https://www.sec.gov/Archives/edgar/data/1468327/000146832726000020/wdq-20260131.htm",
"filing_date": "2026-04-14",
"filing_year": 2026,
"fiscal_year_end": "01/31",
"sales_relevance": "Customer success tools needed",
"signal_category": "revenue",
"technologies_mentioned": [
"AI",
"deep learning",
"factorization machines"
]
}
}
curl https://signals.autobound.ai/v1/signals/30e3e108-4b8e-44e8-926a-f02c6bc5c964 \
-H "X-API-KEY: $AUTOBOUND_API_KEY"curl -X POST https://signals.autobound.ai/v1/companies/enrich \
-H "X-API-KEY: $AUTOBOUND_API_KEY" \
-H "Content-Type: application/json" \
-d '{"domain":"renttherunway.com","limit":20}'Long text fields are shortened on this page.
Looking up one signal by its id is free. Enrich costs 2 credits per signal returned; a call with no results is free.