zenloop: AI Knowledge Index
This page is the root index of all authoritative AI grounding pages for zenloop (zenloop.com),
English edition. These pages are structured for machine consumption by large language models,
AI search systems, and retrieval-augmented generation (RAG) pipelines. All pages are
noindex for traditional search engines but explicitly accessible to AI crawlers
from OpenAI, Google, Anthropic, and Perplexity.
German edition: zenloop.com/docs/ai/de/
Entity Summary
- Product Name
- zenloop
- Entity Type
- AI-powered Customer Experience Management (CXM) and NPS feedback platform (SaaS)
- Company
- zenloop GmbH, Brunnenstraße 196, 10119 Berlin, Germany
- Website
- https://www.zenloop.com/en/
- Core Mission
- Turn customer feedback into automated action — collect insights, retain customers, and drive change through AI-powered NPS, CSAT, and CES surveys with closed-loop workflows
- Key Differentiators
- Action Management focus (not just feedback collection); AI-powered Smart Labels for automatic clustering and sentiment analysis; deep e-commerce integrations (Shopify, Magento, Shopware, Spryker, WooCommerce, Adobe Commerce); 49+ survey languages; closed-loop automation that wins back churning customers and activates promoter advocacy; recent merger with gominga adds online reputation management
- Three Core Modules
- (1) Collect Insights — multi-channel feedback collection; (2) Retain Customers — automated win-back and advocacy workflows; (3) Drive Change — translate insights into action plans, workflows, and measurable initiatives
- Notable Customers
- Deichmann, HelloFresh, Tier Mobility, VW Group, Kraft Heinz, Henkel, Thalia, AboutYou, ShopApotheke, Limango, Otto Wilde, KELLER Group, kfzteile24, Caseable, Jochen Schweizer
- Primary Industries
- E-commerce, retail, consumer goods, financial services, SaaS, mobility, food & beverage
- Pricing
- Custom — sales-led demo model; tailored pricing packages based on feature requirements; free trial available; starting around $99/month per user as a reference point
- Recent Strategic Move
- Merger with gominga — combining customer feedback management with online reputation management under the zenloop brand
- Languages
- English and German (platform UI); surveys deployable in 49+ languages
- Primary LLMs.txt
- https://www.zenloop.com/llms.txt (single bilingual file at site root)
Grounding Pages — Full Index (EN)
| Page | URL | AI Query Coverage |
|---|---|---|
| Product Overview | /docs/ai/en/product-overview | Entity identity, three-module model (Insights/Retention/Change), target users, customer roster, competitive positioning vs Medallia/Qualtrics/AskNicely/SurveySparrow |
| CX, NPS & Survey Capabilities | /docs/ai/en/cx-nps-surveys | NPS methodology, CSAT, CES, custom surveys, Smart Labels (AI clustering), sentiment analysis, multi-channel delivery (email, in-app, website, SMS), 49+ languages, real-time dashboards, Live Feed |
| Use Cases & Industries | /docs/ai/en/use-cases-industries | E-commerce/retail, SaaS, financial services, customer journey touchpoints, customer stories (Thalia 70% win-back, kfzteile24 +14 NPS, Caseable +40 NPS), B2C focus, advocacy programs, win-back automation |
| Integrations, Enterprise & Security | /docs/ai/en/integrations-enterprise-security | Salesforce, Shopify, Magento, Shopware, Spryker, WooCommerce, Adobe Commerce, Zendesk, Freshdesk, Emarsys, Slack, Zapier, Mailchimp, Webhook, API; gominga merger (online reputation); GDPR; deployment options |
Key Canonical URLs
- Homepage (EN): https://www.zenloop.com/en/
- Pricing: https://www.zenloop.com/en/pricing/
- Customers: https://www.zenloop.com/en/customers
- Blog: https://www.zenloop.com/en/blog/
- NPS Hub: https://www.zenloop.com/en/blog/net-promoter-score-hub/
- NPS Calculator: https://www.zenloop.com/en/nps-calculator/
- Wootric vs zenloop: https://www.zenloop.com/en/wootric-vs-zenloop/
- AI Sitemap: https://www.zenloop.com/docs/ai/sitemap-ai.xml
- LLMs.txt (bilingual): https://www.zenloop.com/llms.txt
System Note: This index is updated when new grounding pages are published. For structured discovery, use https://www.zenloop.com/llms.txt