> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bitscale.ai/llms.txt
> Use this file to discover all available pages before exploring further.
# Best Practices for Reliable Workflows
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## 1) Treat a workbook as a reusable template
As your usage grows, you will often end up with one workbook that acts like your master workflow.
Best practice:
1. Keep one clean workbook as the template
2. Duplicate it for day-to-day runs
3. Rename the copy so it carries context
A simple naming pattern:
* `{date} - {owner} - {purpose}`
Example:
* `13 Mar - AJ - Beijing accounts`
This makes it obvious to others:
* who created it
* when it was run
* what it was used for
## 2) Star your template grids and workbooks
Keep your original template safe.
1. Star the template workbook or grid
2. Make it a team habit that starred items are never edited directly
3. Always duplicate first, then change the duplicate
This prevents someone from accidentally modifying the “source of truth” workflow.
## 3) Use Find People for quick manual prospecting
If you are doing quick prospecting and need data immediately, you do not always need to build a full grid workflow first.
Use **Find people** to:
* enter a person’s details
* access their email
* access their phone number
This is useful when you are in a hurry and want contact data right away.
## 4) Keep one data type per grid
Bitscale supports multiple sources per grid (CSV, internal sources, CRM, and more).
Even so, a strong workflow hygiene rule is:
* keep company-level data in company grids
* keep person-level data in person grids
If you need to connect the two, use:
* export leads into a contact grid, or
* VLOOKUP across grids
This keeps your workflows clean and easier to debug.
## 5) Find People with more coverage
When you use **Find people from company**, there is a limit of 25 contacts fetched per account.
If you want more coverage:
* create multiple “Find people from company” columns
* split them by persona or location
Example setup:
* `GTM folks - US`
* `GTM folks - India`
When you build persona filters, use **Suggested titles** to automatically add relevant roles without manually typing every variation.
## 6) Keep grids clean
A common mistake is trying to store dozens of contacts inside a single company row. This may lead to confusion when the data volume increases.
Instead:
1. Use the **Export leads** option
2. Create a new target grid (contact grid)
3. Choose which company-level fields to send along
* example: company name, LinkedIn URL
4. Run the export
Now every contact becomes its own row, and you still keep company context alongside it.
## 7) Use VLOOKUP to cross-reference grids
If two grids are not directly connected, but they share a common value (like company name), you can pull columns from one grid into another.
1. Add column
2. Go to **Data toolkit -> VLOOKUP**
3. Choose the grid to match against
4. Pick the matching column (the common value)
5. Select the columns you want to fetch (example: LinkedIn URL)
6. Run for a test batch first
This is a simple way to reuse data you already enriched somewhere else.
## 8) Always validate emails and phone numbers
If your goal is outbound, validation is one of the easiest ways to reduce bounce rates.
1. Go to **Tweak**
2. Open **Validate**
3. Switch on a validator provider
If you have your own validation provider, connect it using your API key and use that.
After validation, you can focus outreach only on:
* valid emails
* valid phone numbers
## 9) Save columns as templates for faster workflows
If you find yourself recreating the same enrichment setup across grids, save it as a template.
1. Open the column
2. Go to **Tweak**
3. Click **Save as template**
4. Name it clearly (example: `US-based ICP filter`)
5. Save
Now it shows up inside the enrichment list, and you can apply it to any grid without rebuilding it.
This works for all kinds of columns:
* HTTP API calls
* research steps
* AI prompts
* email or phone waterfalls
* find people filters
## 10) Use the right AI tool for the job
### Use research agents for discovery
If you are generating content from scratch and want the system to discover context from the web, research agents are helpful.
### Avoid research agents when you already have strict inputs
If you already have specific inputs you want the copy to stick to (example: a fixed set of offers), do not ask a research agent to choose for you.
In those cases, the best approach is to use a content-focused model that follows your inputs closely.
* Example: Use Claude Sonnet for outbound content generation when you want it to stay tightly aligned to your provided context
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## Need help?
If you hit an issue or want feedback on your current setup, use the in-app support button and reach out to the team.