Use Tags
Tag Products and Keywords to organize your catalog and target dashboards, Alerts, and Sherlock at any slice.
A tag is a label you attach to a product or a keyword, like Top Performer or cat:HomeCare. Once tagged, you can filter dashboards, scope Alerts, and group Sherlock signals by that label instead of picking items one by one. An item can carry as many tags as you need.
To tag products from your connected Seller Central or Vendor Central account, use the Product Tags source on the Sources page. You don't need product tracking to tag a product. The Products source adds products to tracking and counts against your tracked product limit.
Why use tags?
Tags pay off as soon as you have more than a handful of products or keywords. With them, you can:
- Filter dashboards to a meaningful slice, for example only your
Top Performerproducts or onlycat:HomeCarekeywords. - Scope Alerts to a group, so you're pinged when your premium SKUs lose the Buy Box, not for every product.
- Slice ad performance by your own categories, without restructuring anything in Amazon Seller Central.
- Get context in Sherlock: when you triage an anomaly, tags show which part of your catalog is affected.
Tagging vs tracking
Tagging and tracking are separate. Tagging only labels a product. Tracking makes DataHawk collect that product's page data every day. Pick the right source on the Sources page before you start:
| Your catalog (connected accounts) | Tracked products | |
|---|---|---|
| What it is | Your own products, from your Seller Central or Vendor Central account | Products DataHawk monitors daily, yours or competitors' |
| Source to use | Product Tags | Products |
| Needs product tracking in your plan | No | Yes |
| Counts against your tracked product limit | No | Yes |
| How to tag | Product Tags CSV upload | While adding the products, or later with Product Tags |
If you only want to group your catalog in dashboards, use Product Tags. Track a product only when you need its daily product page data (see Track Products). The same applies to keywords: you can tag keywords you don't track, for example to filter Brand Analytics SQP data by your own groups.
Add tags
Most people tag in bulk with a CSV file. Pick the tab that matches your situation.
Best for tagging your catalog, or retagging dozens or hundreds of items at once.
Open the tags importer
Go to Sources. Find the Product Tags (or Keyword Tags) row and click + Add.
Don't use the Products row. It adds products to tracking, not tags.
Download a template
- Template CSV: a blank file. Use it the first time you tag.
- Product/Keyword Catalog & Tags CSV: pre-filled with the items you've already tagged. Use it to update existing tags. It doesn't include untagged items.
For a first upload, start from your own product list, for example an export from Seller Central.
Fill in the template
Use one row per product or keyword. Put its tags in the Tags column, separated by semicolons (;). Tags are case-sensitive.
Upload and fix errors
Upload the file. DataHawk checks every row and flags errors. Use the in-app Find and replace to fix them quickly.
Choose the import mode
| Mode | What it does |
|---|---|
| Add New Only | Adds the tags in your file. Tags already on each item stay. The safe default. |
| Replace Matching | For items in your file, replaces their tags with the ones in the file. Items not in the file keep their tags. |
| Replace All | Wipes all existing tags, then applies your file. Destructive: be sure before you use it. |
Confirm
Click Add Product Tags or Add Keyword Tags.
Large file? See Uploads & bulk imports if your upload hangs or times out.
When you add products or keywords to tracking, you can tag them in the same flow:
- URL or ASIN entry: fill in the Tags field in the last step, before you click Add.
- CSV import: add an optional Tags column, with multiple tags separated by semicolons (
;). Tags are case-sensitive.
See Track Products or Track Keywords for the full flow.
Handy when you're looking at a single tracked SKU and want to add an On Watch or cat:NewSegment tag on the fly.
Open the items list
Go to Sources → Products or Sources → Keywords.
Edit the tags
Click the item's row. Type new tags or pick one from the suggestions.
Save
Click Save.
How long until tags show up?
Tags don't apply instantly. DataHawk processes tag uploads every 3 hours, and each run takes about 40 minutes. Your tags reach your data (Snowflake or BigQuery) within 3 hours 40 minutes at most. Dashboards show them after their next refresh.
Types of tags
You'll see three kinds of tags in DataHawk. They can sit side by side on the same item.
| Type | Who creates them | When they're attached |
|---|---|---|
| Automated | DataHawk | Automatically, based on what DataHawk knows about the item. You can't add or remove them. |
| Preset | DataHawk, as a starter list | When you pick one from the suggestions |
| Custom | You | Whenever you add or edit a product or keyword |
Name your tags so they scale
A flat list of tags gets hard to filter after a few dozen. Each tag is a single text value, but you can build structure into the name.
Add a prefix for each dimension. Use the dimension:value format, so every tag says what it describes:
- Product category:
cat:HomeCare - Product group:
pg:Vacuum Cleaner - Product color:
color:Red
Then search cat: to see all category tags, pg: for all product groups, and so on.
Use / for sub-levels. Use the dimension:level1/level2 format:
cat:HomeCare/Allcat:HomeCare/Accessorycat:HomeCare/Vacuum/Cordless
Follow a few formatting rules:
- Always include the prefix (
cat:,pg:,color:). - Keep prefixes lowercase.
- Don't put spaces around
/. - Remove leading and trailing spaces.
- Pick a casing convention and stick to it. Tags are case-sensitive:
HomeCareandhomecareare two different tags. Lowercase prefixes with PascalCase values (cat:HomeCare) work well.
Manage tags
To manage tags across your workspace, click View Tags in the Sources header. From there you can:
- Add a tag without attaching it to anything, to set up your naming in advance.
- Rename a tag. Every item with the old name follows the rename, with no re-import needed.
- Remove a tag from the workspace.
Where tags show up
Once applied, tags are available across DataHawk:
- Dashboards (Power BI, Looker Studio): every standard dashboard has a Tags filter.
- Alerts: target items by tag instead of one ASIN at a time.
- Sherlock: signals are grouped by tag, so you see patterns across your catalog.
- Your data (Snowflake, BigQuery): see For analysts below.
Tags belong to one workspace and aren't shared with your other workspaces. If you have several, upload the same tag file to each one.
FAQ
For analysts: tags in your data warehouse
Product tags live in the REFERENTIAL schema, in two tables:
| Table | What it holds | Use it to |
|---|---|---|
REFERENTIAL.REFERENTIAL_PRODUCT_TAG | Current product and tag pairs (PRODUCT_KEY, TAG_NAME), updated every 3 hours | Filter or group data by tag. Power BI dashboards read this table. |
REFERENTIAL.DATAHAWK_TAGS_SOURCE | Each uploaded tag, with TAG_NAME, MARKETPLACE_KEY, CHANNEL_PRODUCT_ID, and TAG_CREATION_DATE | Check that a specific upload landed |
To check an upload, count the tags created on the upload date:
SELECT COUNT(*) AS TAGS_CREATED
FROM REFERENTIAL.DATAHAWK_TAGS_SOURCE
WHERE TAG_CREATION_DATE::DATE = '2026-09-24'Replace COUNT(*) AS TAGS_CREATED with TAG_NAME, MARKETPLACE_KEY, CHANNEL_PRODUCT_ID, TAG_CREATION_DATE to list them instead.
To group your data by tag, join on PRODUCT_KEY. The Google Sheets examples include a full query.
Where to go next
Track Products
Set up product tracking and tag products as you add them.
Track Keywords
Set up keyword tracking and tag keywords as you add them.
Uploads & bulk imports
Fix tag uploads that hang, time out, or don't show up.
Alerts
Scope alerts to tagged items so you only get pinged on what matters.
Sherlock
Use tags to group anomalies by the catalog slice they affect.
Brand Analytics (SQP)
Filter Search Query Performance data by your own tags.