Difference between revisions of "UseCases/Current/GenesysCloud/SL09"
From Genesys Documentation
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|Offering=PureEngage | |Offering=PureEngage | ||
|SMART_Benefits={{SMART Benefits | |SMART_Benefits={{SMART Benefits | ||
| − | |UCBenefitID= | + | |UCBenefitID=Improved Sales Rep / Agent Productivity |
| − | |UCBenefit= | + | |UCBenefit=Sales reps are empowered with real time customer journey data from your website. This visibility allows them to personalize and prioritize engagements with prospective customers. Productivity is improved when sales reps interact when they have the most impact. Our software predicts which prospects are most likely to buy or abandon based on outcomes from previous customers taken guesswork out of the equations for your sales teams. |
}}{{SMART Benefits | }}{{SMART Benefits | ||
| − | |UCBenefitID= | + | |UCBenefitID=Increased Sales Conversions |
| − | |UCBenefit= | + | |UCBenefit=Accelerate sales cycles and lead conversion rates (MQL to SQL to conversion) by engaging prospects or online shoppers in real time—at the right time—as they browse your website. |
}}{{SMART Benefits | }}{{SMART Benefits | ||
|UCBenefitID=Improved Customer Experience | |UCBenefitID=Improved Customer Experience | ||
| − | |UCBenefit= | + | |UCBenefit=Improve CX and NPS scores and reduce Customer Effort by providing customers with a more timely and meaningful engagement online. |
}}{{SMART Benefits | }}{{SMART Benefits | ||
| − | |UCBenefitID=Reduced | + | |UCBenefitID=Increased Quality of Lead Conversion |
| − | |UCBenefit=Reduce customer acquisition cost (CAC) | + | |UCBenefit=Follow individual customer journeys in real time on your website. Identify the moment of struggle or moment of opportunity and launch a chat or voice interaction with a sales agent at the right time to increase lead volume, improve lead qualification and reduce customer churn. |
| + | }}{{SMART Benefits | ||
| + | |UCBenefitID=Reduced Sales and Marketing Costs | ||
| + | |UCBenefit=Reduce customer acquisition cost (CAC). Predict which prospects are most likely to buy based on successful outcomes from previous customers. Use these insights to focus marketing efforts and ad spend on a target profiles or sales sales activities. | ||
| + | }}{{SMART Benefits | ||
| + | |UCBenefitID=Improved cross-sell and up-sell (Increase Customer Lifetime Value) | ||
| + | |UCBenefit=Retain customers by increasing customer satisfaction with faster and more personalized service. Improve the ability to up-sell and cross-sell existing customers with data based on their current interests, online journeys and prior purchasing behavior. | ||
}} | }} | ||
| − | |UCOverview= | + | |UCOverview=One of the biggest challenges for the modern business is learning to utilize all of the data available to them in a way that is both meaningful and actionable. The data generated by a website is often left unexplored, and as a result, the intentions and reactions of individual customers and prospects can be overlooked. Focus is often placed on the broad strokes–key metrics such as the number of page views this month–and we lose the ability to identify the potential customers who need engagement most. As a result, prospects who may be on the verge of signing up for a trial, completing a checkout, or any other desirable outcome, fall through the cracks. |
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| + | The high volume of website traffic makes it challenging to identify the right individuals, best moments, and optimal ways to engage in real time. Expectations for time-to-respond are increasing but growing your inside sales staff is costly. Marketing dollars are spent on a wide range of demand generation activities but it is difficult to connect the dots from lead to contact to opportunity to closed. | ||
| + | Genesys Predictive Engagement uses machine learning to track the progress of website visitors towards defined outcomes–purchase completion, requesting a quote–and enables the business to define rules to trigger intervention only at the points when it is needed most. | ||
| − | + | With Genesys Predictive Engagement, you can predict and prioritize high-value leads for your sales team to engage and proactively offer chat to better utilize your staff and reduce your costs. Genesys Predictive Engagement uses machine learning to track the progress of website visitors towards defined outcomes–purchase completion, requesting a quote–and enables the business to define rules to trigger intervention only at the points when it is needed most. | |
|UCSummary=<span>Genesys Predictive Engagement monitors individual customer journeys on your company website. It applies machine learning, dynamic segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer through chat. When the visitor interacts, the sales rep has the customer journey information at their fingertips.</span> | |UCSummary=<span>Genesys Predictive Engagement monitors individual customer journeys on your company website. It applies machine learning, dynamic segmentation, and real-time outcome scoring to identify the right moments for proactive engagement with the right customer through chat. When the visitor interacts, the sales rep has the customer journey information at their fingertips.</span> | ||
|Description=Predictive Engagement monitors individual customer journeys on a company website and applies machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via chat. It can instantly notify sales reps about hot leads and their behaviors. When the consumer interacts, the sales rep will have the customer journey information at their fingertips. | |Description=Predictive Engagement monitors individual customer journeys on a company website and applies machine learning, dynamic personas, and outcome probabilities to identify the right moments for proactive engagement via chat. It can instantly notify sales reps about hot leads and their behaviors. When the consumer interacts, the sales rep will have the customer journey information at their fingertips. | ||
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This diagram details the routing that takes place before and during the chat. | This diagram details the routing that takes place before and during the chat. | ||
|BusinessImage=https://www.lucidchart.com/documents/edit/38673dbe-49ce-47b8-aba2-4a876d0d4fd7/0 | |BusinessImage=https://www.lucidchart.com/documents/edit/38673dbe-49ce-47b8-aba2-4a876d0d4fd7/0 | ||
| − | |BusinessFlowDescription=# Genesys routes the interaction to a sales rep based on the skills, priority, language and queue set in Genesys Predictive Engagement. | + | |BusinessFlowDescription=# Genesys routes the interaction to a sales rep based on the skills, priority, language and queue set in Genesys Predictive Engagement (target expression and virtual queue). |
# Sales rep and prospect are in conversation. The sales rep has access to full visitor context such as segment, journey information, and outcome score. The sales rep can also see attributes of the visitor such as device type, operating system, location and browser type. | # Sales rep and prospect are in conversation. The sales rep has access to full visitor context such as segment, journey information, and outcome score. The sales rep can also see attributes of the visitor such as device type, operating system, location and browser type. | ||
| − | # After the conversation ends, the sales rep agent sets a wrap up code record the outcome of the conversation. | + | # After the conversation ends, the sales rep agent sets a wrap up code to record the outcome of the conversation. |
}} | }} | ||
|BusinessLogic=====<span class="mw-headline" id="BL1_.E2.80.93_Customer_Identification">BL1 – Customer Identification</span>==== | |BusinessLogic=====<span class="mw-headline" id="BL1_.E2.80.93_Customer_Identification">BL1 – Customer Identification</span>==== | ||
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* Attributes, such as browser type, device type, location, marketing campaign they are associated with, UTM parameters, and the referral website. | * Attributes, such as browser type, device type, location, marketing campaign they are associated with, UTM parameters, and the referral website. | ||
* Journey pattern, such as web browsing behavior, searches performed on the website, items clicked, returning users, cart abandoner, and high order value. | * Journey pattern, such as web browsing behavior, searches performed on the website, items clicked, returning users, cart abandoner, and high order value. | ||
| − | Outcomes or goals are specific tasks that you want your visitors to perform on your website. As with segments, | + | Outcomes or goals are specific tasks that you want your visitors to perform on your website. As with segments, these are configured upfront. Typical outcomes include: |
* Proceed to checkout with a shopping cart | * Proceed to checkout with a shopping cart | ||
* Submit payment | * Submit payment | ||
* Download a whitepaper | * Download a whitepaper | ||
| − | * Book a demo or appointment | + | * Book a demo or appointment |
| + | |||
| + | Genesys uses predictive analytics to evaluate in real time the probability for a specific outcome to be achieved, based on segment and visitor behavior on the website (the outcome score). | ||
====<span class="mw-headline" id="BL3_.E2.80.93_Action_Map_Configuration">BL3 – Action Map Configuration</span>==== | ====<span class="mw-headline" id="BL3_.E2.80.93_Action_Map_Configuration">BL3 – Action Map Configuration</span>==== | ||
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* User activity | * User activity | ||
* Outcome score. Typically, a drop-in outcome score for a specific segment can trigger an action. | * Outcome score. Typically, a drop-in outcome score for a specific segment can trigger an action. | ||
| − | * Invitation to chat | + | |
| + | The following actions are part of this use case: | ||
| + | * Invitation to chat | ||
====<span class="mw-headline" id="BL4_.E2.80.93_Pacing_Service">BL4 – Estimated Wait Time</span>==== | ====<span class="mw-headline" id="BL4_.E2.80.93_Pacing_Service">BL4 – Estimated Wait Time</span>==== | ||
Genesys's patented pacing algorithm automatically predicts sales rep availability based on contact center statistics. If no sales rep is predicted to be available for the requested media type, no offer to engage is sent to the visitor. | Genesys's patented pacing algorithm automatically predicts sales rep availability based on contact center statistics. If no sales rep is predicted to be available for the requested media type, no offer to engage is sent to the visitor. | ||
| − | + | ====BL5 – Customer Invite and Registration==== | |
| − | + | Genesys Widgets is used for: | |
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| − | Genesys Widgets | ||
* Invite messages for chat | * Invite messages for chat | ||
| − | * | + | * Collection of visitor's contact details |
| − | * | + | * Engagement over chat session booking |
| − | |DistributionLogic= | + | |DistributionLogic=The distribution of the interaction is determined by the target expression and virtual queue configured in the Genesys Predictive Engagement rules. |
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|CustomerInterfaceRequirements=* Used with Genesys Widgets only. Not supported with PureCloud Widget. | |CustomerInterfaceRequirements=* Used with Genesys Widgets only. Not supported with PureCloud Widget. | ||
|AgentDeskRequirements=N/A | |AgentDeskRequirements=N/A | ||
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* Visitor Activity report. See visitor historical activity. Filter by segments and outcomes. | * Visitor Activity report. See visitor historical activity. Filter by segments and outcomes. | ||
* Action Map Report. View action map performance numbers for qualified, offered, accepted, rejected, errored and timedout action. | * Action Map Report. View action map performance numbers for qualified, offered, accepted, rejected, errored and timedout action. | ||
| − | |GeneralAssumptions=Customer must use Genesys Widgets. Customer must deploy both | + | |SMART_HybridAssumptions={{SMART HybridAssumptions |
| + | |Hybrid_Assumption=v 1.0.1 | ||
| + | }} | ||
| + | |GeneralAssumptions=Customer must use Genesys Widgets. Customer must deploy both Predictive Engagement and Widgets code snippets on their website or web pages. | ||
The Genesys Chat Routing CE18 use case is not used here as it is based on PureCloud Widget, which is not used with Altocloud. However chat routing logic used with Genesys Widgets is identical to CE18 use case. | The Genesys Chat Routing CE18 use case is not used here as it is based on PureCloud Widget, which is not used with Altocloud. However chat routing logic used with Genesys Widgets is identical to CE18 use case. | ||
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}} | }} | ||
Revision as of 13:21, August 14, 2019
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Contents
Use Case Overview
Story and Business Context
Info needed.
Use Case Benefits*
The following benefits are based on benchmark information captured from Genesys customers and may vary based on industry, lines of business or Genesys product line: Info needed.
*You can sort all use cases according to their stated benefits here: Sort by benefits
Summary
Info needed.
Use Case Definition
Info needed.
Business and Distribution Logic
Business Logic
Info needed.
Customer-facing Considerations
Interdependencies
All required, alternate, and optional use cases are listed here, as well as any exceptions.
| All of the following required: | At least one of the following required: | Optional | Exceptions |
|---|---|---|---|
| None | None | None | None |
Document Version
Needs info.