NEW! AI Lead Scoring for HubSpot

[Forwrd_AI]

Still updating your lead scoring model manually?

HubSpot's rule-based lead scoring system is a fantastic place to start experimenting with automatic lead qualification, but it has a bunch of drawbacks:

1. Subjectivity in rule creation: The rules themselves can be biased if they are developed without considering diverse perspectives or if they reflect the biases of the rule creators. 
2. Limited variables: Rule-based scoring systems often rely on a limited set of variables to make decisions. If these variables don't capture the full complexity of the situation, it can lead to skewed outcomes.
3. Lack of adaptability: Rule-based systems are rigid and fail to adapt to changing circumstances. Features expand, new marketing experiments are launched almost daily, and ICPs and user journeys shift.

To qualify prospects accurately, you must ensure you have a dynamic scoring method that considers ALL of our critical GTM data sources, and which can remain accurate, regardless of any changes our growing business might go through.

Allow me to introduce...

AI Lead Scoring for HubSpot

A completely automatic, and ridiculously accurate lead qualification solution, by a certified HubSpot partner!

AI-powered lead scoring utilizes machine learning algorithms to autonomously analyze vast amounts of data, identify patterns, and continuously improve its predictions.

Here's how AI lead scoring outperforms traditional methods:

1. Adaptability: AI models self-learn from new data and adjust their scoring criteria accordingly, ensuring your lead scoring remains relevant and effective.

2. Accurate data analysis: AI algorithms can process and interpret complex data sets, uncovering hidden relationships and factors that influence lead conversion.

3. Minimal maintenance: Once deployed, AI models require minimal human intervention, freeing up your team to focus on other strategic initiatives.

It's no wonder B2B SaaS leaders like Jasper.ai, AppsFlyer, WalkMe (NASDAQ:WKME), and Kaltura (NASDAQ:KLTR) rely on Forwrd.ai every day to focus on their most promising leads!

Want to learn more?

Book your free consultation call, or try it for free all by yourself!

[Forwrd_AI]

🧙‍ Hey fellow HubSpot wizards, 

🌟 TLDR - Calling Marketing Ops, Sales Ops, and RevOps leaders at US-based B2B SaaS companies with 200+ employees! 📢

Will you give us feedback on our AI lead scoring solution for HubSpot? In return, you'll get a $100 Amazon gift card! 

👉 Apply here

Full message:

🤩 We're transforming how predictive lead scoring is done in HubSpot, and we need the most brilliant minds – that's you! 

🤖Our predictive lead scoring solution it's smarter than your average rule-based scoring solution and hungrier for data than a kid in a candy store. 

🔍Here's where we need your expertise. 

We want to hear from US-based companies with at least 200 employees onboard. 

Why 200?

Because our predictive model needs statistically relevant historical data like it's fuel for intergalactic travel!

So, what's in it for you? 

💸Besides our eternal gratitude and a digital high-five, we're offering $100 Amazon gift cards to qualifying participants! 

💡Ready to shape the future of lead scoring? Click below to apply for a 45-minute feedback session that's sure to leave you feeling inspired and energized.

👉 Apply here!

Places are limited, so don't miss your shot at scoring that gift card and unlocking the full potential of your leads. 

📩Questions? Hit reply and ask.

Looking forward to meeting you soon!

Cheers,

🤝Your friends at Forwrd.ai 

P.S. Feel free to share this opportunity with other HubSpot legends in your network – the more, the merrier! 🌟🌐

[SNigam]

Great.

[MiaSrebrnjak]

Hi @Forwrd_AI, thank you for sharing! Is this integration also available on the HubSpot App Marketplace? 

Thanks, 

Mia, Community Team 

[Forwrd_AI]

Hi Mia, it sure is!

You can search for Forwrd.ai on the app marketplace, or this link should also take you there.

We already have 40 installs coming just from the store, and counting 🙂 

[MiaSrebrnjak]

That's great, thanks for the link! 🙂