March 2025

Hi everyone, March was huge, exciting, and funny! We shipped a lot of stuff.

Here’s a quick summary of what we did for you in March:

Released a new out-of-the-box feature – Run Status column
Integrated our first CRM - Datablist is now connected with PipeDrive
Shipped a new data source - Instagram follower scraper
Integrated 5 new LLMs - Claude, Perplexity, Gemini, DeepSeek, and Mistral
Updated the LinkedIn scraper - Scraping and converting now: LinkedIn URLs and Sales Navigator IDs

The Highlights of March

Run Status Column – Get More Context

Do you remember a moment where having more context on what’s happening with your enrichments ever hurt you? Me neither.

How Was It Before

Before we implemented this, you had no chance to know what was happening behind the scenes. For example:

The costs of each row for usage-based enrichments
The types of errors
What was causing the errors
Where the data inconsistencies were

And as many of you were a bit frustrated since you were left in the dark about what's happening with your enrichment runs, we designed this feature to be insightful and easy to grasp.

Why This Matters

The Run Status Column gives you:

Transparency and efficiency in your workflow.
Instant visibility into what's happening with each enrichment

Which allows you to:

Re-run enrichments with 3 mouse clicks
Understand issues & errors faster
Optimize your processes
….

By understanding where and why things might go wrong, you can make more data-driven decisions to improve your enrichment strategy.

These are the statuses you might see:

Success & number of credits consumed
Invalid data
Missing data
Rate limit notifications
HTTP notifications

What You Can Do With It

Reconfigure enrichments more easily
See how many credits each row consumed
Get more details on errors
Fix prompting errors faster
Re-run enrichments easier

First CRM Integration: PipeDrive CRM

If you use PipeDrive, you probably know how often duplicates can end up in your list, and you have to manually remove them after you try it with PipeDrive's native deduplication features, and it doesn’t work.

And it's not only PipeDrive; most CRMs have a big problem with data quality features. Yes, they all have a built-in duplicate finder, but this comes with huge limitations, such as:

You can't search for duplicates across different Pipelines.
You can only delete duplicates, not merge them.
Duplicate searching is limited to some properties—it won't work with websites, email, or phone numbers.s
The duplicate detection uses exact matching only, so it misses records with simple typos.
There's no merge history or changelog to track changes.
You have no control over which records to keep or delete, risking important data loss.
There's no way to process duplicates in bulk.

Not trying to say that PipeDrive is bad. I am just saying that its deduplication features are limited because they have another focus, which is why we built this integration for you.

How It Works

Import data from Pipedrive automatically.
Clean the data inside of Datablist.
Merge records in Pipedrive by ID (Merge one ID with another).
Update and sync cleaned data with Pipedrive by copy-pasting your API key.

Related Resources

How to deduplicate and clean a PipeDrive CRM

New Features & Improvements

New Data Source: Instagram Follower Scraper

We had a user on a call asking for a way of scraping Instagram followers to monitor competitors and search for patterns across their followers, and since we want to help with the things that matter to our community, we were excited to build this feature quickly.

Want us to build something for you? Tell us about it here!

How It Works

Give us the profiles
Set a limit of followers you want to scrape

That’s it. Datablist does the rest

How To Use It

Create a collection
Click on “See all sources.”
Select “Instagram follower scraper.”
Paste a list of line-separated profiles.
Set a limit on the number of followers to scrape
Click on “Continue to outputs configuration.”
Click on the ⊕ icons to add a new column for each output
Click on “Import now.”

Related Guide: How To Scrape Instagram Followers

New Processors: Expanded LLM Choice

First days of March, sunny day in Nantes, Florian receives an email from a semi-upset customer saying: “I don’t want to be limited in my choice of the LLM, why don’t you integrate other models too?”

We heard that feedback and promptly expanded our AI capabilities by integrating five new powerful language models.

How Was It Before?

Our previous LLM options were limited to OpenAI models, which meant:

Fewer choices for specific use cases
Less flexibility in model selection
Limited optimization options

Why This Matters

With Claude, Perplexity, Gemini, DeepSeek, and Mistral now available, you have more options to choose the right AI model for your specific needs, ensuring better results and more efficient processing.

What You Can Do With It

Choose the best model for your specific use case
Optimize for cost vs performance
Access cutting-edge AI capabilities
Compare results across different models

LinkedIn Profile Scraper - Normalize URLs & More Input Formats

Our LinkedIn Scraper now also allows Sales Navigator IDs as input and gives the normalized LinkedIn URL as output!

Some LinkedIn sequencer and message personalization tools don’t allow Sales Navigator URLs as input, which makes it impossible for some people to proceed with their workflows, so we made an update to our LinkedIn scraper

Why We Did It

Funny story, if we think about it for a moment: Someone who wasn’t even a customer needed to convert Sales Navigator IDs to LinkedIn Profile URLs, so we started looking for solutions.

2 Days later, we found the solution, implemented it, and reached out to that prospect, telling him, “Yo {{first_name}}, we found a solution and implemented it for you. Wanna try it out?

This was his answer: “Yo Habib, thanks so much, but I've found a solution.”

Do we regret it? No, quite the opposite, since other users also find their use in this improvement.

That’s it, see y’all next time!

P.S. If you have any feature ideas you'd like us to build for you PITCH ME HERE ⟸ ⟸