Test and Learn: An AI-powered experimentation platform on Azure to design experiments & exploit winning ideas
The objective is to develop an end-to-end experimentation solution for designing and executing experiments in marketing, digital, and retail, reducing the time spent on designing, executing, and measuring experiments from weeks to hours.
Meet TALP (Test & Learn Platform) by Tredence. It is a lightweight, configurable platform on Azure for designing marketing innovation experiments and obtaining holistic 360-degree performance. It augments the decision-making of campaign owners, store managers, product managers, and marketing managers by providing a 360-degree view of experiment performance by highlighting critical metrics, analyzing lift, and providing cross-sectional insights.
These insights are used to improve campaign design and audience selection processes, as well as new product feature launches, promotional plans, and so on.
Design your new experiment: proactive system recommendations ML techniques help you build the optimal experiment design, test it, and match it with the control. Measure tests & their impact across variables. Enable a full 360-degree real-time view into experiment performance across all key measures, such as sales, profit, shopper response, traffic, etc. Learn from the adjacent experiments. Utilize adjacent learning to drive enterprise-wide insight adoption and a virtuous cycle of experiment improvement.
The implementation uses native Azure components: CI/CD Tools: The Azure CI/CD suite, consisting of ADO repos, ADO pipelines, etc., is used for code repository and automated deployment. Solution lifecycle management is governed using Azure App Insights and Logic Apps. Security restrictions and access privileges for users are managed using Azure Active Directory and Azure Key Vault.
Outcome: TALP allows organizations to harness and build a culture of experimentation and encourages organizations to run multiple marketing, digital, and store experiments for launching and testing new strategies.
Implementation Plan: Weeks 1-2 (Discovery) Weeks 3-4 (Design) Weeks 5-6 (Experimentation for key pilot campaigns) Weeks 7-8 (Deployment & Testing)