Automated customer personalization at scale,
powered by the world’s most intelligent recommender system

Galahad’s Scalable Recommender System Solution
Helps Clients Realize the Value of Personalization

We work with clients in these industries:

Banking

Insurance

Wealth Management

Healthcare

Retail

CPG

Travel

Entertainment

Non-profit

What We Deliver

• Acceleration Plan

– Based on discovery with key stakeholders, Galahad will document the business requirements for the personalization strategy including priority use cases, data, predictive analytics, channels and measurement

– Best practice recommendations will be detailed in an action-oriented “Blueprint” for the areas of customer experience, marketing strategy, digital, data, analytics/data science, channel and technology.

Deliverable: Personalization Strategy & Best Practice Blueprint

• Implementation Roadmap

– Based on client’s current capabilities and investment budget, a prioritized implementation plan will be created to set up, test and rollout personalization tactics and supporting data, insights and technology.

– The roadmap will be created with the objective of creating a self-funding process that maximizes investment returns. The customized Recommender System can be expanded beyond the initial version to incorporate additional features.

– A detailed Test and Measurement Plan will also be provided for potential use in a proof-of-concept campaign prior to the full solution setup.

Deliverable: Roadmap Timeline, Test & Measurement Plan

• Rapid Start Predictive Customer Intelligence

– We assess each client’s inventory of predictive intelligence including customer segmentation and models. These can be quickly integrated into the recommender system solution. In cases where clients do not have the existing intel needed, Galahad’s Customer Cube insights for customer growth, retention and price elasticity can be used as the quick start intelligence to deploy the recommender system.

– The system uses a robust set of offline and online data including purchases, profitability, RFM, demo/life stage, email engagement and digital activity.

Deliverable: Ready-to-use intelligence data including segment, profitability, growth potential and attrition risk

• Next Best Action Recommendations

– The automated, scalable recommender system is ‘The Brain’ that orchestrates data-driven personalization, determining the next best action to be taken for each customer and the optimal channel to interact with that customer at any point in time. It is the engine under the hood that powers a great personalization program.

– Next best actions can include product offers, transactional updates, reminders, informational and educational communications. Channels include both inbound and outbound interactions.

– Minimum viable product of the initial version recommender system can be tested using a few key actions and channel examples prior to deployment.

– Hands-on setup help of the initial system configurations and running test simulations to validate the appropriate message is delivered at the right time to the right customer through the right channel.

Next Best Action Recommender Engine

Overview of Recommender Engine

Features include:

• “Brain’ that determines next best action for each customer
• Dynamic offer engine for real-time decisioning
• Orchestrates & personalizes interactions across all channels
• Tailored to your business requirements and includes roadmap

– Next best actions can include product offers, transactional updates, reminders, informational and educational communications. Channels include both inbound and outbound interactions. 

– Minimum viable product of the initial version recommender system can be tested using a few key actions and channel examples prior to deployment.

– Hands-on setup help of the initial system configurations and running test simulations to validate the appropriate message is delivered at the right time to the right customer through the right channel.

Testing and Measurement Framework

• The recommender system enables advanced A/B testing experiments so that personalization parameters such as audience segments, channels, offers, creative content can be evaluated with the measurement framework.

• The measurement framework also enables multi-touch attribution by quantifying the incremental value generated by each customer interaction in a series of contacts. This information can be used to update the configuration parameters of the system to better optimize marketing spend.

Read More About Advanced Testing and Measurement

Continuous Deep Learning

– Our Continuous Learning model-based framework can be implemented so that audience algorithms can be updated autonomously as sufficient results data becomes available. Our framework is typically implemented in two stages starting with baseline self-learning capabilities and evolving to more advanced self-learning powered by Reinforcement Learning.

Read more about Continuous Deep Learning

Please contact us to learn more about our Recommender System Solution.

For qualified prospects, we will share a live demo of our Recommender System using synthetic data.

Contact Us