How to Get Started With Predictive Routing


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Guillaume Calot of Genesys discusses the benefits of installing predictive routing in your contact centre, while offering his guidance on where to get started.

Artificial intelligence (AI) has hit critical mass across every industry. Organizations of all sizes are incorporating AI applications into their customer experience to improve their business models and strategies.

Yet a fundamental challenge with this promising and evolving technology is leveraging it to develop deeper ties with customers while gaining greater operational efficiencies.

Participants of the recent Genesys webinar “How to successfully implement AI-driven predictive routing” conveyed this challenge.

When polled, these participants identified that their top two challenges for an AI project implementation were determining a clear AI strategy and identifying applicable use cases.

Customers clearly want low-friction digital interactions and quick resolutions to their needs; AI can be a critical component to make this happen — addressing customer needs the moment they happen, and sometimes even earlier.

However, the key is being able to successfully incorporate AI technology to achieve this level of customer experience.

Taking the First Step

Data is the fuel of AI; it creates endless possibilities for innovation. And real-time customer interaction data is a gold mine when it’s used to predict, analyse and optimize the customer journey — and to meet and exceed changing customer expectations.

However, the only way to keep up with this innovation is in the cloud, where you gain true agility and competitive differentiation. This begs an important question: How do we turn an AI transformation challenge into an actionable, transformational plan?

The plan starts with defining and prioritizing high-impact use cases to drive technology innovation use and investment decisions.  This includes predictive routing, which is a practical application of AI that predicts the best match between customers and agents to deliver a specific business outcome.

Unlike queue-based or skills-based routing, AI-driven predictive routing fuels actionable transformations that:

  • Focus on business outcomes by creating high impact through complex problem solving
  • Are based on a strong foundation that augments the routing logic and uses all available data
  • Improve operational control, enabling full visibility to create and execute an agile customer experience strategy

During the webinar, participants named efficiency and customer satisfaction as the two top strategic business KPIs they want to optimize first. And predictive routing definitely can help.

In fact, companies that already use predictive routing as part of their AI transformation are seeing measurable results, including increased Net Promoter Scores and first contact resolution, with decreased customer churn and average handle time.

Defining a Predictive Routing Use Case

The first step in successfully leveraging predictive routing is to define a use case that can optimize these three parameters:

  • Type of service
  • Channel
  • Specific KPI

Interestingly, when one KPI is optimized, there often is a much wider positive impact on other KPIs, and ultimately on business outcomes. For example, fewer transfers can improve customer satisfaction and retention while reducing costs.

This blog post has been re-published by kind permission of Genesys – View the original post

To find out more about Genesys, visit their website.

Published On: 15th Jul 2019 - Last modified: 16th Jul 2019
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