LiftIgniter Real-time Personalization Platform Reviews & Insights

Score7.4 out of 10

3 Reviews and Ratings

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LiftIgniter Real-time Personalization Platform Reviews

3 Reviews

Quality content recommendations, easy integration, and great support!

Rating: 8 out of 10

July 28, 2019

Use Cases and Deployment Scope

The Product & Engineering team integrated LiftIgniter into our CMS, Wordpress, and frontend. We use LiftIgniter to provide content recommendations to our readers. Our goals in integrating LiftIgniter were to increase time on site, reduce bounce rate, and resurface evergreen content.

Pros

Well documented APIs
Quality recommendations
Great support

Cons

Focus on self serve tools

Likelihood to Recommend

LiftIgniter is well suited for:

Media companies without the resources to develop their own content recommendations systems.
eCommerce companies who want to get product recommendations live onsite quickly.

LiftIgniter is less appropriate:

Organizations with a shallow content set onsite.

Jake McGraw

Co-Founder and CTO in Product Management at The Block (11-50 employees)

Vetted Review

5 years of experience

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LiftIgniter was good for recommending related content and easily implementing across 3 disparate systems.

Rating: 8 out of 10

November 29, 2018

Use Cases and Deployment Scope

We are merging 3 companies that have similar content. We implemented LiftIgniter to make content reccommendations across the content of the 3 companies. Otherwise, we would have had to implement 3 separate recommendation algorithms and numerous integration points between 3 disparate sites to support our requirements. LiftIgniter allowed us to have a complete solution that we could deploy in less than 1 month of kickoff across 3 systems.

Pros

It does a good job recommending content that is related to the current story a user is on.
It does a good job not recommending content the user has already viewed.
It does a good job being a recommendation engine for disparate sites with related content.

Cons

If the content being recommended is not related to the current story we are seeing a smaller click through. This scenario can be turned or improved.

Likelihood to Recommend

Friend, you are not going to build a recommendation engine in less than 2 years. The basis of the LiftIgniter platform is proven and their solution is easy to integrate with.

Derek Liddell

Vice President in Product Management at Maven (11-50 employees)

Vetted Review

1 year of experience

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LiftIgniter and AI driven Article Recommendations

Rating: 10 out of 10

November 7, 2018

Use Cases and Deployment Scope

We (LegalZoom.com) have over 6000 articles across our site to help our potential customers make product decisions. Liftigniter's AI driven article recommendation does a great job at recommending related articles that help inform our visitors to the point where they are ready to make a buying decision.

Pros

Simple integration using HTML page tags
Relevant results are achieved (CTR, Conversions) without the need to manually teach the system.

Cons

Manually controlling certain undesired results is not straight forward and seems to often result in a lower CTR or conversion rates.
The LI Dashboard has limited features.

Likelihood to Recommend

Our products are somewhat complex and require potential customers to educate themselves. That's why we've created thousands of articles that help educate our visitors and help them make the right buying decision. LiftIgniter's AI driven article recommendation engine is the perfect solution for this type of UX scenario.

Christian Neeser

SEO Director in Marketing at LegalZoom (501-1000 employees)

Vetted Review

1 year of experience

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