Genesys Predictive Engagement (CE37) for GenesysEngage-cloud

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This topic is part of the manual Genesys Engage cloud Use Cases for version Public of Genesys Use Cases.
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Use machine learning powered journey analytics to observe website activity, predict visitor outcomes, and proactively engage with prospects and customers via agent-assisted chat, content offer or chatbot.

What's the challenge?

It’s challenging to identify the right individual, the best moments, and the optimal ways to offer assistance online. Companies want to shape their customers’ journeys and drive them towards desirable outcomes, but it’s hard to utilize all of the available data in a way that is meaningful and actionable. In addition, consumers expect fast answers, but it's expensive to always engage an agent.

What's the solution?

Proactively lead customers to successful journeys on your website. Apply machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via a web chat or help content screen-pop.

Story and Business Context

For customers seeking service or support, a company’s website is often the first point of contact, even if it is only to find a phone number to call. But companies are challenged with making sense of and learning to utilize all of the data generated by their website in a way that is both meaningful and actionable in real-time. As a result, the intentions and needs of individual consumers are overlooked, and we lose the ability to shape the journey in the moment and identify the customers who need help the most. As a result, customers either end up calling into the contact center (an expensive support channel) or get frustrated with your business because they can’t find the help they need. Genesys monitors website behavior, applies machine learning to determine audience segments and predicted outcomes in real time, and then uses that information to guide customers to a successful outcome – starting with an effective self-service offer of a chatbot to those customers who need the most help. Companies have lots of rich data within their CRM, marketing automation, contact centers and websites, and Genesys enables companies to unlock that data in real-time to engage customers proactively, thereby eliminating the need for a voice call or contact without context.


Examples of how the customer experience can be optimized by using context include:

  • A customer who is recognized to be having trouble submitting a loan application is prompted with a chatbot to automate a conversation about the loan application.
  • A customer needs to activate their new mobile phone, goes to the website, and searches for "device activation". A proactive chatbot is offered to help the customer walk through the steps.
  • A customer is planning a trip abroad and needs to notify their credit card company. They go to the company's website and based on a search related to "travel alert", a chatbot is offered to assist to prevent the need to call the contact center.
  • A customer is proactively offered self-help options to assist with a transaction, for example providing a link to a video to help with a Return Merchandise Authorization (RMA).

Understanding and leveraging knowledge of online activities and behaviors can provide context to better handle a follow-up digital or voice interaction. This engagement intelligence can also be utilized for converting service requests to sales opportunities for cross-sell or up-sell. Genesys uses artificial intelligence to track the progress of website visitors towards defined outcomes – service requests, pending transactions, application status - and allows the business to define rules to trigger intervention only at the points when it is needed most.

Use Case Benefits

Use Case Benefits Explanation
Improved Customer Experience Offer assistance only when needed to reduce customer annoyance.
Reduced Administration Costs Improve self-service rates by providing customers with the right information at the right time or proactively offering a chatbot to automate the conversation and prevent contact with an agent.
Reduced Handle Time When the engagement requires escalation from self-service to assisted service, the agent is provided context of the journey.

Summary

Genesys monitors each and every individual customer journey on your company website and applies machine learning, audience segments and outcome probabilities to identify the right moments for proactive engagement via a chatbot. If the consumer needs to interact with an agent, the agent has the customer journey information at their fingertips.


Use Case Definition

Business Flow

Main Flow

Business Flow Description

  1. The customer starts browsing the company website.
  2. Genesys determines whether the customer is new or returning to the website, and associates data from previous journeys.
  3. The combination of segment and variations in outcome score can trigger an offer to chat with a chatbot while the customer is browsing the website.
  4. If the customer accepts the invitation for chat, a registration window pops up where the customer can enter his data and the conversation with Genesys Blended AI Bots (CE31 Use Case) will start. In the registration form, customer can either manually enter his contact details (name, email) or contact details will be pre-filled if already known to Genesys.



For more details

For additional details, contact your Genesys Sales Representative by filing out the form or for immediate assistance call us: 1-888-Genesys.