Lookalike audiences 2023-04-03
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Qualifyed.AI - Lookalike Audiences

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Audience targeting prediction for businesses.
Generated by ChatGPT

Qualifyed's AI Predictive Audiences tool uses machine learning and artificial intelligence to help businesses target and convert cold prospects into customers by identifying audiences who share similar characteristics with existing customers.

The tool ingests a file of 1st party data of US consumers, runs these seed files against marketing databases including credit bureaus to pre-score 96% of US adults on their likelihood to convert before they even hear of the business.

These attributes are mostly offline data attributes, cookie-less, and immune to any future changes of third-party cookies. Qualifyed then applies the machine learning algorithmic model of existing customers to pre-score different US populations.

This audience is then ingested into the businesses' ad account, via LiveRamp as a hashed email list, for creating new, highly targeted audiences for the campaigns.

The technology used by Qualifyed is used by Fortune 500 companies that pay six figures per year, but the company has democratized the technology, bringing it to small and medium businesses at a fraction of the cost and no long-term contracts.

By using AI Predictive Audiences, businesses can unlock their potential customer base's cold audience, exactly like their target customers, with maximum accuracy to get higher return on ad spend (ROAS).

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Qualifyed.AI - Lookalike Audiences was manually vetted by our editorial team and was first featured on April 11th 2023.
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Pros and Cons

Pros

Targets cold prospects
Predicts audience characteristics
Uses 1st party data
Runs data against databases
Pre-scores conversion likelihood
Offline data attributes
Cookie-less operations
Immunity to cookie changes
Algorithmic model application
Ingests into ad account
Hashed email list integration
Available to small businesses
Targets specific US populations
Dramatically increases ROAS
Deals with IOS 14.5 changes
Uses non-tracking user data
Maximizes use of first-party data
ML system inspection
Continuous data modeling
Targets high potential prospects
Ingests Personally Identifying Information
Runs data across 3400 attributes
Algorithmic buyer model training
Pre-scores 96% of US adults
Affordable solution
No long-term contracts

Cons

Only US focused
Requires high-quality 1st party data
Depends on credit bureaus
Limited to offline data attributes
Limited to LiveRamp hash integration
Possibly expensive for small businesses
No data on latency and processing speed
No information on data security
No plug-and-play, requires setup
No long-term contracts, possible instability

Q&A

What is Qualifyed.AI?
How does Qualifyed.AI use machine learning and artificial intelligence?
What is the purpose of Qualifyed's Predictive Audiences tool?
What is the process of using 1st party data with Qualifyed.AI?
How does Qualifyed.AI use marketing databases and credit bureaus?
What does it mean to pre-score 96% of US adults?
What effect do future changes of third-party cookies have on Qualifyed.AI?
How does Qualifyed.AI use a machine learning algorithmic model?
How are new audiences ingested into an ad account?
What is LiveRamp and how is it involved with Qualifyed's AI Predictive Audiences tool?
Is Qualifyed.AI suitable for small and medium businesses?
How can Qualifyed's AI Predictive Audiences tool help increase return on ad spend (ROAS)?
How does Qualifyed.AI help businesses unlock their potential customer base?
What impact did iOS 14.5 privacy changes have on lookalike audiences?
How does Qualifyed.AI use existing 1st party data?
How does Qualifyed.AI deal with cookie and pixel data?
Why is the term 'AI' considered a buzz word on Qualifyed?
What are the advantages of using 1st party data with Qualifyed.AI?
What happens after training a machine learning algorithmic model on Qualifyed?
How does Qualifyed.AI's machine learning system inspect sales?

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