Messy scraper exports when you sell to furniture stores
Does your scraper export have columns called field1, field2 and field3? Here is how people who sell to furniture stores fix it.
Does your scraper export have columns called field1, field2 and field3?
Browser scrapers and directory exports produce files with odd column names, several URL columns and a lot of noise. Turning that into a usable list takes work.
It hits harder when you sell to furniture stores. Furniture stores include independent showrooms, specialist sofa and bed shops, and regional chains. Owners or buyers choose ranges, delivery partners and finance options, and big ticket sales make service and delivery a key concern.
Raw exports stay unused on your desktop. The time you saved by scraping is lost again on cleaning.
From raw export to clean records in one import.
Riftjaw reads CSV with comma or semicolon and Excel .xlsx files. You map each column to a field and, when there are several URL columns, you pick which is the website and which is something else. Records start as concepts, so you can review before publishing, and an import can be deleted.
- Fields that fit furniture stores, such as categories
- Email prefixes that fit, like info@, sales@, showroom@ and enquiries@
- Status, tags and a segment on every record
How to fix it in Riftjaw
- Upload the export. Drop in the CSV or Excel file straight from your scraper.
- Name the columns. Map each column and choose which URL column is the website.
- Review the concepts. Check the records, then publish or delete the import.
Other walls when prospecting furniture stores
Premium and budget stores need different ranges and messages.
A price level field and a saved filter for each tier keep offers relevant.
Chains list every branch separately.
Use the website as the key field so branches are flagged as duplicates on import.
Buyers want to see products, so email is only the first step.
Tag contacts for a showroom visit and keep notes on what they liked.
Fields worth recording for furniture stores
Record these and you can split the list later, write sharper mails and see who fits your offer.
| Field | Why it helps |
|---|---|
| Company name | The key field. Duplicates are checked on it or on the website. |
| Website | Needed to derive an email when the export has none. |
| Categories | Sofas, beds, dining or office furniture each need different suppliers. |
| Showrooms | The number of showrooms shows scale. |
| Price level | Budget and premium stores stock very different ranges. |
| Delivery | Whether they deliver themselves or outsource it. |
| Online sales | Stores selling online need photography and product content. |
Questions people ask
Add a price level field and fill it from their website. Then save a filter for each level and send a matching campaign.
Yes. Update the status, add a tag such as visited and write a note on the contact.
If your file has an email column, that wins. If it only has websites, tick the prefixes you want, such as info@, sales@, showroom@ and enquiries@, and Riftjaw derives addresses from each domain. Derived addresses are good guesses, not verified, so start with small batches.
Yes. The Free plan runs the whole pipeline on one list with small campaigns, and you do not need a credit card. Move to Pro when you want more lists, segments and bigger campaigns.
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