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Customer Insights with Qdrant, Python and Information Extractor

by Jimleukadapted from n8n official workflow galleryUpdated Aug 2026
RequiresCCodeDDefault Data LoaderEmbeddings OpenAIEmbeddings OpenAIGoogle SheetsGoogle SheetsHTMLHTMLHTTP RequestHTTP RequestOpenAI Chat ModelOpenAI Chat ModelQdrant Vector StoreQdrant Vector StoreRecursive Character Text SplitterRecursive Character Text Splitter
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MaWhen clicking ‘Test workflow’When clicking ‘…SeZip EntriesHtExtract ReviewsSOReviews to ListDDDefault Data LoaderDefault Data Lo…TSRecursive Character Text SplitterRecursive Chara…Embeddings OpenAIEmbeddings Open…SeSet VariablesHRGet Payload of PointsGet Payload of …SOClusters To ListOpenAI Chat ModelOpenAI Chat Mod…FiOnly Clusters With 3+ pointsOnly Clusters W…SeSet Variables1HRFind ReviewsSePrep Output For ExportPrep Output For…Export To SheetsHRClear Existing ReviewsClear Existing …EWTrigger InsightsSePrep Values For TriggerPrep Values For…EWExecute Workflow TriggerExecute Workflo…HRGet TrustPilot PageGet TrustPilot …VSQdrant Vector StoreQdrant Vector S…CoApply K-means Clustering AlgorithmApply K-means C…IECustomer Insights AgentCustomer Insigh…123456789101112
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STEPS · 12
Run manually by an operator

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Customer Insights scenario where Trustpilot reviews can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, marketers can save days and even weeks of work breaking down their own or competitor reviews and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vQ6ipJnXWXgr5wlUJnhioNpeYrxaIpsRYZCwN3C-fFXumkbh9TAsA_JzE0kbv7DcGAVIP7az0L46_2P/pubhtml How it works Trustpilot reviews are scraped for a particular company using the HTTP request node. Reviews are then inserted into a Qdrant collection carefully tagged with the question and Trustpilot metadata. Reviews are fetched and put through a clustering algorithm using the Python Code node. The Qdrant points are returned in clustered groups. Each group is looped to fetch the payloads of the points and feed them to the AI agent to summarise and generate insights for.

Tags

n8nreference-onlydocument-default-data-loaderembeddings-open-aigoogle-sheetshtmllm-chat-open-aitext-splitter-recursive-character-text-splittervector-store-qdrant
Connects
CCodeDDefault Data LoaderembeddingsopenaiEmbeddings OpenAIsheetsGoogle SheetshtmlHTMLWHTTP Request
CategoryAI Automation
Triggermanual
Complexityadvanced
Nodes24
AddedAug 5, 2024

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