AI & Machine Learning

Take advantage of powerful AI and machine learning capabilities within the Alterian Real-Time CX Platform

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Journey AI

Customer journeys are complex and are as unique as each individual in your customer base. Collectively customers create billions of data points across their interactions, purchases, feedback and products usage. Understanding what key journeys are, how to improve them and tackling the complexity of orchestrating journeys requires the right tools and practices.

Traditional approaches often appear to work well for initial Journey analysis and orchestration as they require little gathering of customer data. Effectively scaling and adapting to an ever-changing consumer world can be a challenge. Journey AI is a powerful tool that can accelerate insights and scale across all of your customer journeys.

Journey AI allows you to:

Scale and adapt at every moment without manual intervention
Understand customer journeys that you didn’t even know existed
Implement the right personalized journeys in real-time
Increase revenue with minimal effort and without large team resources

Alterian provides a clear and simple way to understand how AI and Machine Learning is put into place with simple use cases, and once success and confidence are proven in these controlled and simple use cases, more complex use cases are deployed. This builds confidence within brands that AI and Machine Learning is a better approach to managing journey complexity.

Machine Learning

Alterian Journey AI

Alterian Journey AI is embedded into our existing orchestration and analytics tools to help you answer key questions that have previously been difficult to answer. It then makes it easy to scale and gives brands that ability to act on these questions in real-time interactions with customers:

What are the key customer journeys that I don’t already know and what do I need to do to improve them?
What are the most significant interactions in a journey and how do I make the most of these opportunities?
How do micro level journeys group together, and can they be optimized better when synthesized together?
What path is each customer taking organically and how will my interventions with their journey change their future path?

Alterian’s Journey AI does the heavy lifting for you. It constantly learns and tunes itself based on customers’ real-time interactions, discovering new journeys and automatically optimizing journey paths as customer behavior and touchpoints change.

This means as a brand you can spend more time defining what success looks like and have a better ability to target new opportunities for revenue growth with the assistance of Journey AI.

Alterian's AI Power and Functionality

Extend Journey Visualization with predictions of the paths customers are most likely to follow.
Enhance and orchestrate a large number of journeys with AI automation.
Supercharge Alterian’s own AI journeys with external predictive and AI models.
Allows business users to maintain journey control while AI decisions handle the complexity.
Continually optimize both AI and Business logic based decisions to generate the best results for your customer and business KPIs.

Journey AI Use Cases

Journey AI can increase productivity over 10x. The following example use cases show the difference Journey AI can make.

Use Cases	With Journey AI	Without Journey AI
Predicting which path a customer is likely to take in the future.	Automatically available as a journey visualization and as a real-time prediction. This improves effectiveness with more accurate targeting.	Bespoke project through data science team, plus a custom development in each channel to use in customer interactions.
Detect previously unknown journeys that significantly impact customer and business goals.	Continually apply deep learning techniques to surface potential new journeys that can be categorized by business and enhanced through journey orchestration. This improves scale and efficiency by removing manual intervention.	Only identifies journeys that are obvious to the human eye though manual analysis of reports and journey flow visualizations. Large amount of effort and resources required.
Recognizing and acting on key moments in each customer’s journey.	Automatically orchestrate real-time micro journeys in the moment depending on a customer’s behavior across all touchpoints.	Journeys will be defined manually and triggered based on an action but not in true real-time causing a delay or break within the customer journey.
Optimize and group parallel journey paths to provide a better experience across the customer lifecycle.	Deep learning will spot and group journeys that appear to follow the same trends. Ensure the customer gets an in-the-moment personalized journey.	A team of analysts will need to model and pull groups together to achieve maximum optimization. This will not occur in real-time.