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Monetate

Monetate
Formerly Kibo Personalization, powered by Monetate & Certona

Overview

What is Monetate?

Monetate (formerly Kibo Personalization, powered by Monetate and Certona) is an ecommerce personalization software for consumer-facing brands. Monetate enables brands to create individualized experiences for site visitors, with the goal of improving engagement and business performance. Founded in 2008, Monetate…

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Recent Reviews

Ease of use

7 out of 10
September 05, 2023
Incentivized
I think Monetate is very useful for testing. No issues with the system. Clear and easy to use with support and manuals
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Quick overview

8 out of 10
April 18, 2023
Incentivized
We've been able to use Monetate to support personalisation across different customer segments on site, as well as run a number of AB tests …
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Monetate Review

10 out of 10
February 28, 2023
Incentivized
We use Monetate to create different user journeys for different customers we target. Doing A/B testing we get to see which experience will …
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Awards

Products that are considered exceptional by their customers based on a variety of criteria win TrustRadius awards. Learn more about the types of TrustRadius awards to make the best purchase decision. More about TrustRadius Awards

Reviewer Pros & Cons

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Pricing

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What is Monetate?

Monetate (formerly Kibo Personalization, powered by Monetate and Certona) is an ecommerce personalization software for consumer-facing brands. Monetate enables brands to create individualized experiences for site visitors, with the goal of improving engagement and business performance. Founded in…

Entry-level set up fee?

  • Setup fee optional

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

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Product Details

What is Monetate?

Monetate (formerly Kibo Personalization, powered by Monetate and Certona) is an ecommerce personalization software for consumer-facing brands. Monetate enables brands to create individualized experiences for site visitors, with the goal of improving engagement and business performance. Founded in 2008, Monetate services Adidas, Lufthansa, Office Depot, Reebok, Wolseley, and other companies.

Monetate is open, and designed to work across the user's marketing stack. It is real-time too, with machine learning capabilities to help deliver 1-to-1 personalization, through to testing & experimentation, and product recommendations at scale.

In October 2019 Monetate and Certona personalization technologies were acquired by Kibo Software. Kibo Personalization included capabilites from these solutions. Monetate was spun off from Kibo in October of 2022.

Monetate Features

  • Supported: Testing
  • Supported: Segmentation
  • Supported: Machine Learning
  • Supported: Data Integration
  • Supported: APIs

Monetate Technical Details

Deployment TypesSoftware as a Service (SaaS), Cloud, or Web-Based
Operating SystemsUnspecified
Mobile ApplicationNo
Supported LanguagesEnglish

Frequently Asked Questions

Monetate (formerly Kibo Personalization, powered by Monetate and Certona) is an ecommerce personalization software for consumer-facing brands. Monetate enables brands to create individualized experiences for site visitors, with the goal of improving engagement and business performance. Founded in 2008, Monetate services Adidas, Lufthansa, Office Depot, Reebok, Wolseley, and other companies.

Adobe Target, Optimizely Web Experimentation, and Dynamic Yield are common alternatives for Monetate.

Reviewers rate Implementation Rating highest, with a score of 9.1.

The most common users of Monetate are from Mid-sized Companies (51-1,000 employees).
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Comparisons

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Reviews and Ratings

(159)

Attribute Ratings

Reviews

(1-3 of 3)
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September 05, 2023

Ease of use

Score 7 out of 10
Vetted Review
Verified User
Incentivized
I think Monetate is very useful for testing. No issues with the system. Clear and easy to use with support and manuals
  • Ease of use
  • banners
I think it's great for AB testing, when you may not have other systems that can use this. In my experience, the Support team are very helpful.
  • ROI - can see what variants run best and make changes
I think support is very helpful
lots of training manuals and online support
In my experience, account managers make it easy
great for AB testing, can see where to improve, good to use as a base for other projects
Score 7 out of 10
Vetted Review
Verified User
Incentivized
We primarily use Monetate for A/B testing and PDP personalization. We have found Monetate helpful in testing new layouts on our home pages.
  • Customer Segmentation and Targeting.
  • Very Customizable in its capabilities.
  • High-level reporting.
  • Very HTML-heavy in some aspects.
  • HTML module selector is not always accurate.
  • Masking can be difficult to figure out.
Monetate is great if you already have an understanding of HTML and CSS. In that case, it can be very useful and customizable on a brand-by-brand base. However, it is a bit tricky for those who do not have previous HTML and CSS experience to pick up.
  • Improvement in bounce rate.
They are great and super helpful any time there are questions. Our rep understood that many team members were not comfortable with the tool, so he found a way to use a budget for training hours. Very responsive and have not had any issues with customer support.
Very good - a little inconvenient as those who did our training lived in the UK so time for training was not very open, however, the training was very high level and they were able to give suggestions on use cases on our website.
Some personalization is still very HTML heavy so it can be tricky depending on what you are trying to test. For basic A/B testing, it is pretty easy to use.
The vendor was very easy to work with. Our customer support rep reached out to us when he realized we were not using the product to it's full capability due to lack of knowledge of the product. He this offered to us some of our support hours to go towards training sessions so that we could get better value out of the products. The support hours were very helpful and allowed us to gain a better understanding on the benefits of the product
We primarily used Monetate for A/B testing. The impact was very beneficial towards out web design process. It allowed us to test different versions of our homepage and PDPs to see which version drove sales with our consumers and how they were interacting with each version.
Score 8 out of 10
Vetted Review
Verified User
Incentivized
We use Monetate to drive our A/B testing program that helps us test customer-centric hypotheses. Landing page optimization and personalization recommendations are the top priorities. The long-term roadmap is to create a more dynamic and real-time personalization using Monetate
  • Segment user for AB testing
  • Personalized recommendation
  • Inject campaign based creatives
  • Scope for Automation and real-time integration with Web
  • Masking can be difficult to figure out
  • Need a longer learning cycle for users to leverage all the capabilities available in the suite
It is very easy to set up AB tests based on the overall population and can use improvements in setting up personalized and dynamic segmentation. Audience segmentation is relatively painless. They provide a robust way to granularly target visitors by device type, location, weather, demographics, etc.
  • landing page optimization leading to higher conversion
  • Utilizing Monetate has enabled us to test and measure the incremental revenue achieved through our segmentation initiatives
  • Increase in CVR from product recommendations
We have a single point of contact for everything related to Monetate and they are very approachable. However, we have seen quite a few turn over on the Monetate side making it difficult for us to keep a strong relationship with the POC
We leverage in house SMEs
It does not have the flexibility to personalize the variables that we have identified as important during our internal discussions. Most of the time the personalization engine cannot identify a single variable as significant. This makes it very difficult for us to keep using this capability
we have a quarterly meeting set up
Monetate allows us to compare and test different variations of content, layouts, or offers
Monetate's A/B testing functionality is incredibly useful for optimizing my campaigns. I can effortlessly set up and run experiments to compare different variations of content, layouts, or offers. The platform then provides detailed performance data, allowing me to identify winning variations and refine my strategies accordingly. Monetate's seamless integration with other marketing tools, such as CRM systems or email marketing platforms, streamlines my workflow. I can easily synchronize customer data, leverage past interactions, and create cohesive cross-channel experiences that deliver consistent messaging throughout the customer journey.
  • Monetate's A/B testing functionality is incredibly useful for optimizing my campaigns. I can effortlessly set up and run experiments to compare different variations of content, layouts, or offers.
  • One standout feature of Monetate is its robust targeting capabilities. I can easily segment my audience based on various criteria, such as demographics, browsing behavior, or purchase history
  • Monetate's user-friendly reporting dashboard is a game-changer. It provides me with clear visualizations and actionable insights on key metrics,
  • Limited personalization options - when aiming to implement advanced personalization strategies that require intricate rule-based targeting or dynamic content manipulation.
  • Determining statistical significance within Monetate experiments often requires additional manual analysis or the use of external statistical tools. While the platform provides basic reporting on experiment performance, obtaining more advanced statistical analysis or detailed insights may require relying on external resources or performing manual calculations.
  • Automated personalization experiences do not return a significant result most of the time and the factors used to segment the traffic is also hidden in case on insignificant result. This makes it difficult to improve the experiment in the following iteration
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