Lead rejection
Avoid buying leads that won't convert — using LinkedIn Ads
You’ll need a Faraday account to use this template. It’s free to sign up and you can use sample data to start.
In today's competitive landscape, many brands—especially those in home and financial services—buy leads from third-party sources. These leads are often purchased through a process called ping-post, where lead bids are placed in real time.
Unfortunately, many of these leads don't convert into customers, leading to wasted marketing spend. But what if there were a way to ensure you're only purchasing leads with the highest potential to convert?
The Challenge
Brands face a common challenge when buying leads: the inability to distinguish good leads from bad ones. Without clear insight into the likelihood of a lead converting, brands often waste money purchasing low-quality leads. The inefficiency of this process is a huge financial drain.
Faraday's Lead Rejection Solution
This is where Faraday steps in. Our AI platform can optimize your lead buying process by predicting the probability of each lead converting. Here’s how it works:
- Scoring Leads in Real Time: Faraday scores your eligible population, which often includes a broad “everybody cohort,” on their likelihood to become customers.
- Real-Time API Integration: When a lead becomes available for purchase, your brand can request a conversion score using Faraday’s real-time Lookup API. This score allows you to make an informed decision about whether to buy that lead, ensuring you're only investing in leads with strong potential.
How to Implement Faraday's Lead Rejection Strategy
You can seamlessly integrate Faraday’s lead rejection solution into your current lead management system (LMS). Here’s a simple three-step approach:
- Set a conversion probability threshold based on Faraday's score.
- In your LMS’s ping-post facility (like LeadConduit), set up a rule to automatically reject any lead that falls below that threshold.
- Enjoy better quality leads without lifting a finger.
The Benefits of Rejecting Bad Leads
By using Faraday to automatically reject poor-quality leads, your brand will:
- Save Money: Stop wasting your budget on low-probability leads.
- Improve Conversion Rates: Focus on high-quality leads that are more likely to convert, increasing your overall success rate.
Take Control of Your Lead Buying
Faraday empowers you to take control of your lead purchasing process, ensuring that your money goes to leads that are truly worth it. With our AI-driven lead rejection solution, you can optimize your marketing spend and improve your customer acquisition strategy.
- Step 1
Connect your data sources
Use the link below to connect LinkedIn Ads to Faraday. You can also skip this step and use CSV files to get started instead. - Step 2
Ingest your data into event streams
This allows Faraday to understand what your data means. These links will guide you through ingesting the data necessary to power this template. - Step 4
Declare your prediction objectives
With your cohorts defined, it's easy to instruct Faraday to predict the necessary behaviors. Follow the docs with the link below. - Step 5
Define your lead scoring pipeline and deploy to LinkedIn Ads
Finally, deploy your prediction with the link below. - Step 6
Deploy to LinkedIn Ads
Create a deployment target using the LinkedIn Ads connection you created above. Or, get started by simply deploying to CSV.
Deploy your lead rejection predictions to . . .
Aurora (MySQL)
AWS Aurora Postgres
Azure SQL
BigQuery
Facebook Custom Audiences
GCS
Google Ads
Google Cloud SQL (MySQL)
Google Cloud SQL (Postgres)
Google Cloud SQL (SQL Server)
HubSpot
Iterable
Klaviyo
LinkedIn Ads
MySQL
Pinterest Ads
Poplar
Postgres
RDS (MySQL)
RDS (Postgres)
RDS (SQL Server)
Recharge
Redshift
Redshift Serverless
S3
Salesforce
Salesforce Marketing Cloud
Segment
SFTP
Shopify
Snowflake
SQL Server
Stripe
The Trade Desk
TikTok
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