about_hero_bg.png

Our work

Headline goes here for case studies

Our team of data strategists have deep practical, and industry knowledge and understand how to effectively harness and apply insights to your businesses strategy, operations, marketing, and customers. We will help drive meaningful and transformational changes in how you succeed and win business. We are technologically agnostic and will work with existing systems or help integrate platforms, systems, and ways of working within your organization.

homepage_case_bg_1a_2x_edited.jpg
homepage_case_bg_1b_2x.png

Driving application growth with Machine Learning

Situation

A large multi-national financial service provider had seen new enrollments for one of their flagship credit cards gradually decline for over a year, with channel data showing that the decline was primarily driven a rapid reduction in the effectiveness of their targeted marketing campaigns.

 

Solution

A new targeting strategy was devised by firstly sourcing third-party data to significantly enhance our understanding of each customers financial profile and preferences and then secondly building and training a machine learning model to find customers who look like the top existing card holders, using both legacy and the  new data acquired.

Impact

4% Increase in new card enrollments within the first 3 months of execution.

homepage_case_bg_2a_2x.png

Situation

The e-commerce platform for a national loyalty program had seen stagnant growth for a number of years, despite significantly increasing it’s offering from a breadth, depth and partnerships angle.

homepage_case_bg_2b_2x.png

Recommendation engines to drive personalization

 

Solution

A Singular Value Decomposition (SVD) recommendation engine was selected as most relevant to the situation, given the volume of data and planned application. The Recommendation Engine would provide a list of the top 5 sub-categories or brands of product that each customer was most likely to be interested in, based on previous web, purchase and profile data. This was then used to personalize website content on their profile and basket checkout pages on the website, as well as in targeted email marketing, leveraging subject lines and dynamic content blocks in the emails.

Impact

The e-comm website saw a 5% increase in revenue in the subsequent month when the website changes were applied and an additional 10% increase once regular personalized emails were implemented to help drive incremental traffic to the site.

 

homepage_case_bg_2b_2x_edited.jpg

Organizing data around people

homepage_case_bg_3b_2x.png

Situation

A large multi-national financial service provider had seen new enrollments for one of their flagship credit cards gradually decline for over a year, with channel data showing that the decline was primarily driven a rapid reduction in the effectiveness of their targeted marketing campaigns.

 

Impact

The e-comm website saw a 5% increase in revenue in the subsequent month when the website changes were applied and an additional 10% increase once regular personalized emails were implemented to help drive incremental traffic to the site.

 

Solution

A Singular Value Decomposition (SVD) recommendation engine was selected as most relevant to the situation, given the volume of data and planned application. The Recommendation Engine would provide a list of the top 5 sub-categories or brands of product that each customer was most likely to be interested in, based on previous web, purchase and profile data. This was then used to personalize website content on their profile and basket checkout pages on the website, as well as in targeted email marketing, leveraging subject lines and dynamic content blocks in the emails.

contact_form_bg.png

Got a question? We’d love to hear from you!

Contact us