01
Structured data stays disconnected from chat.
Product names, prices, use cases, and availability live in rows while customer conversations happen somewhere else.
Import the structure into the product layer behind the answer.
Google Sheets chatbot
Turn the rows your team maintains into useful product answers.
Import structured product data from Google Sheets, map the columns, and use the resulting catalog inside support and sales conversations.
Store catalog
Google Sheets · imported source
Product
Best for
Price
Status
2
Calm Duo
Dry + sensitive
$42
Active
3
Daily Gel
Oily + combo
$24
Active
4
Barrier Cream
Dry + mature
$28
Low stock
5
Mineral SPF
All skin
$26
Active
CatalogFAQsDelivery
Column mapping
ProductName
Best forRecommendation context
StatusAvailability
Question → matched row
Which moisturizer is best for dry, sensitive skin?
The Calm Duo is the closest match in the imported catalog: it is tagged for dry and sensitive skin and is currently active.
Matched: Calm Duo · row 2Use answer
Sheet import
Start from familiar rows
Column mapping
Turn headers into product fields
Catalog answers
Use structured product context
Ops-owned source
Re-import when the sheet changes
The spreadsheet gap
The product answer exists. It is trapped in a row.
Sheets are easy for teams to maintain, but customers cannot ask a spreadsheet a buying question and support agents should not scan columns mid-conversation.
02
A header means different things to different teams.
One sheet says “best for,” another says “use case,” and the destination needs a clear field mapping.
Make column meaning explicit before importing products.
03
The source changes after the import.
A sheet can remain familiar to operations while the chatbot keeps using an older imported version.
Give updates a visible re-import routine and owner.
From sheet to conversation
Connect, map, import, answer.
Google Sheets is the authoring surface; the imported BoundBot catalog is the operational source used to match product questions.
Live decision path
Connect
Authorize Google Sheets read access.
Connect the Google account used to read the spreadsheet you want to bring into the product catalog.
A lightweight catalog pipeline
Keep editing simple without making the answer vague.
Operations can maintain a familiar sheet while BoundBot turns a deliberate import into structured products the conversation can search.
Use one clear header row and consistent values for the fields you plan to import.
Map the columns customers actually ask about, not every spreadsheet detail.
Assign a re-import owner whenever product data changes in Google Sheets.
Sheet import stack
Sources the team can maintain
Google connection
Read-only Sheets access
Spreadsheet URL
Selected product source
Column mapping
Headers to product fields
Product catalog
Conversation-ready records
Useful structure, visible control
Make the sheet part of a real product workflow.
The value is not a chatbot inside the spreadsheet. It is a clean path from rows to structured product answers and recommendations.
01
Google Sheets product import
Connect a Google account and import product rows from a spreadsheet URL into BoundBot.
02
Structured catalog matching
Use product fields and descriptions to support catalog search, comparison, and guided discovery.
03
Reusable across customer channels
Let WebChat and connected messaging channels draw from the same imported product catalog.
Prepare the first spreadsheet
A clean import starts with a clean header row.
Keep the initial sheet narrow, validate the product fields, and test the customer questions those rows should answer.
Choose one product sheet.
Use a spreadsheet with a single clear header row and product records underneath it.
Connect Google and paste the URL.
Authorize the Google account, then provide the spreadsheet URL in the product import flow.
Validate the imported catalog.
Review names, descriptions, prices, availability, and other fields before relying on them in chat.
Test real product questions.
Ask about fit, availability, price, or comparison and improve the sheet where the answer lacks useful detail.
What does the Google Sheets integration import?
BoundBot can read rows from the first sheet in the connected spreadsheet and turn valid structured data into product catalog records.
Does BoundBot need edit access to the spreadsheet?
The integration uses read-only Google Sheets access for importing product data; your team continues editing the source in Google Sheets.
Are sheet changes automatically reflected in the catalog?
Treat the current flow as an import. When the sheet changes, re-import and validate the updated product records before using them in customer answers.
Can the imported products power more than website chat?
Yes. The resulting catalog belongs to the BoundBot workspace and can support product conversations across connected customer channels.
Continue exploring
Related BoundBot routes
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Feed structured CSV data into a chatbot workflow for product questions, repetitive support answers, and quick imports.
Product Catalog Chatbot
Use a product-aware chatbot to answer catalog questions, availability questions, and buying questions from structured product data.
AI Sales Chatbot
Handle pre-sales questions, product discovery, and lead capture with a grounded chatbot that can still escalate to a human.
Put the rows to work
Import one clean sheet. Answer one real product question.
Turn familiar spreadsheet data into a structured catalog your customer conversations can actually use.