Toronto, ON (Jan. 24, 2018) – To improve customer experience and maximize dollars spent on customer acquisition, Kanetix Ltd underwent an aggressive push to implement a highly sophisticated Conversion Rate Optimization program in 2017. The program was designed to run tests on an accelerated basis across all brands within Kanetix Ltd. Hypothesis were evaluated for the shortest time possible in order to determine statistical significance, typically at 95% confidence levels.
These tests used a variety of A/B and multivariant designs on Kanetix.ca, incorporating several techniques, from visual hierarchy to psychological principal based theories. By running weekly tests on the majority of the customer base, Kanetix.ca saw a lift of 37% in conversion from completed auto quotes to connected leads, over 36 of such tests.
Leveraging this Conversion Rate Optimization program, Kanetix.ca is now using Artificial Intelligence and Machine Learning to help determine customers to target on an ongoing basis. The goal is not to focus on users on either end of the use case spectrums, those who are unlikely to convert or those who are more likely to convert, but those in the middle and ‘on the fence’.
To accomplish this next test, our AI partner was provided with a large set of customer data showing which consumers had and had not converted to leads. Based on this dataset, a model was built to be able to predict which customers were likely to convert, those that were less likely to convert, and those who were in the middle, ‘fence sitters’. Customers within this middle group were identified as part of the regular site rating call process and then presented different treatments of the conversion page to nudge them to connect with Kanetix based on the recommendations of the Machine Learning algorithm. This nudge treatment was then split into a standard A/B test model to determine whether this nudge was successfully resulting in more leads. The quote data and customer behaviours were then fed back into the Machine Learning algorithm to help improve the overall accuracy of the model going forward.
The AI variation group showed a 10% stronger conversion rate than the control group, indicating that the treatment was a success. Additionally, the test group converted at a 65% higher conversion rate than the lower converting segments identified by the AI algorithm.
Based on the success of the program, Kanetix Ltd will be rolling this out to other areas of the business, to continue to enhance the overall customer experience for all business lines.
About Kanetix Ltd.
Kanetix Ltd. is Canada’s largest digital customer acquisition platform for insurance and financial services. With over 8 million shoppers visiting their five consumer-facing brands yearly, Kanetix Ltd. works directly with the country’s top insurers, financial institutions and brokers. Kanetix Ltd.’s mission is to help every Canadian make better money decisions.
Integrate.ai is a leading platform for large enterprises to train AI-enabled solutions that drive customer engagement and revenue growth. At integrate.ai, the mission is to build a future in which AI enriches people’s lives while creating better, more valuable businesses.
Founded by Steve Irvine, former leader of Facebook’s global partnership teams, Integrate.ai is based in Toronto, Canada at the centre of an exciting AI ecosystem. Irvine has built his Integrate team with top-tier talent – former Fast Forward Labs President Kathryn Hume from New York City, former Airbnb executive Jason Silver, and more.
SOURCE: Kanetix Ltd.Tags: Artificial Intelligence (AI), ICTA nomination, InsurTech, Kanetix