5 Ways You Can Improve Your Form Conversions
Discover tips and tricks on how to improve your forms for the highest conversions.
Don’t Make Me Choose!
Learn how choice overload is affecting your customer experience and impacting your sales on your website.
Website Natural Selection
Find out how websites can evolve via natural selection to its strongest, most optimal form for conversions.
Steering the Way to Conversion Success
Learn how forward-thinkers in the automotive industry are using AI to steer their online experiences towards conversion success.
Ascend Case Study: HR GO plc
Find out how Sentient and Space Between helped HRGO boost job applicant conversions by over 150%.
Case Study: Laanebanken
Learn how Ascend and 44Pixel helped Laanebanken boost the conversion rate for loan applications by 6%.
Biometrics & CRO Explored
In this webinar, learn how Space Between used biometrics to develop hypotheses and set up multivariate experiments for one of their flagship clients, HR GO.
How to Measure Element Importance in Website Testing
Sentient Data Scientist David Staub (PhD) and Content Marketing Manager Cristina McComic uncover how to measure each website element in terms of its potential impact on conversion rates,…
How to Drive Up Conversions Across Your Entire Funnel Using Ascend
Sam Nazari, Sr. Solutions Engineer at Sentient, shares best practices and ideas for using Ascend to increase conversions across your entire website funnel.
The 2018 Digital Travel Benchmark Study
Learn how the digital travel industry personalizes their booking experience through multi-channel optimization.
Conversions in Bloom: Sentient, Online Dialogue, and Euroflorist
In this webinar, conversion expert Ton Wesseling of Online Dialogue discusses how AI is making an impact in the world of testing and optimization.
eTail: Improving Customer Engagement
How do you stack up against industry benchmarks? Download our free 2018 report based on survey responses from over 100 ecommerce industry leaders to find out.
The Road to Complete Personalization (Eye for Travel 2017)
Sentient's Gurmeet Lamba discusses personalization and AI at Eye for Travel 2017.
Getting Started with Full-Funnel Optimization
This paper explores how Sentient Ascend automates the process of improving conversions across a funnel, with tips and examples of different ideas you can test in your own…
Being Right When You Think You Are Wrong
Dr. Neil Iscoe, Chief Technologist of Sentient Ascend, covers some basic tips for how you can look at your experiment data to understand where your opportunities to increase…
Hill Climbing: How to Get to the Highest Peak
"Always be testing” is a process—a series of steps that take you to your goal. This webinar covers the systematic, scientific ways to take those steps and help…
Evolutionary Optimization with Sentient Ascend
Learn why AI-powered conversion optimization beats legacy solutions by giving you the power to test more ideas, faster.
The Big Book of Ascend Ideas
AI-powered conversion optimization solutions let you do more. Learn how, plus get 27 real ideas for your site.
The Big Book of Ascend Ideas – Live
Join Ascend testing guru Sam Nazari in this free webinar as he walks through some AI tests from our Big Book of Ideas.
Case Study: Nexway
Find out how Nexway improved a client's conversions by 17% in less than a month with one simple test.
2017 State of Conversion Optimization
Sentient has partnered with the ConversionXL Institute to survey industry professionals on the state of conversion optimization.
Conversion Optimization & Financial Services: What You Need to Know
Financial services site have complex funnels and valuable customers. Ascend excels at handling both.
Conversion Optimization & Travel: What You Need to Know
Ascend works out of the box with single-page applications, making it an ideal CRO solution for travel sites of every stripe.
The Digital Marketer’s Guide to AI-Powered CRO
AI testing is different that A/B testing. Learn what to test and how to set up your first experiment with Ascend in this free guide.
Case Study: ABUV Media
Find out how testing 380,000 widget combinations increased signups by 45%, all in under two months.
How Ascend Works
What does testing 380,000 combinations look like? Watch this short video to find out.
Case Study: Cosabella
Learn how a few small, counterintuitive changes helped a luxury lingerie brand improve their conversions by 38%.
Case Study: Classic Car Liquidators
Find out what happened when Classic Car Liquidators used Sentient Ascend to test nearly 30,000 potential designs in a month.
Lets Talk Growth – Jonathan Epstein on How AI is an Emerging Tool for Growth
In this talk, you'll learn how genetic algorithms and artificial intelligence give growth hackers the ability to get bigger lift than traditional A/B tools.
How ABUV Media Improved Conversion 45% in 8 Weeks Using Sentient Ascend
Learn why ABUV media switched from legacy A/B testing solutions to a AI-powered optimization with Sentient Ascend.
What, Why and How to Multivariate Test with AI
Top Conversionista conversion specialist Patrik Matell leads a conversation with Sentient’s Jon Epstein about how AI can be your new advantage in conversion rate optimization.
Machine Earning: The Results Are In
Watch this webinar featuring Brian Massey, one of the world’s most influential conversion rate optimization experts, to learn how his team used Sentient Ascend to massively increase lead…
The Case for Massively Multivariate Testing
In this webinar, you'll learn about AI-powered conversion rate optimization and discover the five factors that will determine whether or not people will convert on site.
The Power of Localization for Efficiently Learning Linear Separators With Noise
Citation: Awasthi, P., Balcan M. F., and Long, P. M (2017). The power of localization for efficiently learning linear separators with noise. arXiv:1307.8371v8.
Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System
Citation: Shahrzad, H. and Hodjat, B. (2015). Tackling the Boolean multiplexer function using a highly distributed genetic programming system. In Riolo, R., Worzel, W. P., and Kotanchek, M.,…
Surprising Properties of Dropout in Deep Networks
Citation: Helmbold, D. P. and Long, P. M. (2016). Surprising properties of dropout in deep networks. arXiv:1602.04484.
Massively Distributed Simultaneous Evolution and Cross-validation in EC-Star
Citations: Hodjat, B. and Shahrzad, J. (2016). nPool: Massively distributed simultaneous evolution and cross-validation in EC-star. In Riolo, R., Worzel, W. P., Kotanchek, M., and Kordon, A. editors,…
Maintenance of a Long Running Distributed Genetic Programming System for Solving Problems Requiring Big Data
Citation: Hodjat, B., Hemberg, E., Shahrzad, H., and O'Reilly, U.-M. (2014). Maintenance of a long running distributed genetic programming system for solving problems requiring big data. In Genetic…
Learning Decision Lists with Lags for Physiological Time Series
Citation: Hemberg, E., Veeramachaneni, K., Wanigasekara, P., Shahrzad, H., Hodjat, B., and O'Reilly, U.-M. (2014). Learning Decision Lists with Lagged Physiological Time Series. In Workshop on Data Mining…
Latent Geometry and Memorization in Generative Models
Citation: Feiszli, M. (2017). Latent Geometry and Memorization in Generative Models. arXiv:1705.09303.
L-SR1: A Novel Second Order Optimization Method for Deep Learning
Citation: Ramamurthy, V. and Duffy, N. (2016). L-SR1: A Novel Second Order Optimization Method for Deep Learning. (+ supplement). In NIPS 2016 Workshop on Nonconvex Optimization for Machine…
Introducing an Age-Varying Fitness Estimation Function
Citation: Hodjat, B. and Shahrzad, H. (2013). Introducing an age-varying fitness estimation function. In Riolo, R., Vladislavleva, E., Ritchie, M. D., and Moore, J. H., editors, Genetic Programming…
Estimating the Advantage of Age-Layering in Evolutionary Algorithms
Citation: Shahrzad, H., Hodjat, B., and Miikkulainen, R. (2016). Estimating the advantage of age-layering in evolutionary algorithms. In Proceedings of the Genetic and Evolutionary Computation Conference...
Distributed Probabilistic Rule Evolution for Time-Series Classification
Citation: Hodjat, B., Shahrzad, H., Miikkulainen, R., Murray, L., and Holmes, C. (in press). PRETSL: Distributed probabilistic rule evolution for time-series classification. In Genetic Programming Theory and Practice…
Discovering Evolutionary Stepping Stones Through Behavior Domination
Citation: Meyerson, E. and Miikkulainen, R. (2017). Discovering Evolutionary Stepping Stones through Behavior Domination. In Proceedings of the Genetic and Evolutionary...
Conversion Rate Optimization Through Evolutionary Computation
Citation: Miikkulainen, R., Iscoe, N., Shagrin, A., Cordell, R., Nazari, S., Schoolland, C., Brundage, M., Epstein, J., Dean, R. and Lamba, G. (2017). Conversion Rate Optimization through Evolutionary…
A Massive-Scale, Hub and Spoke, Distributed Genetic Programming System
Citation: O'Reilly, U.-M., Wagy, M., and Hodjat, B. (2013). EC-Star: A massive-scale, hub and spoke, distributed genetic programming system. In Riolo, R., Vladislavleva, E., Ritchie, M. D., and…