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Personalized Customer Support: A Look Inside Intelligent Data Synchronization

During a customer support call, don’t make your customers tell your agents information that you should already know.

It seems like a simple mandate, but many companies are still struggling to make support delivery a painless, personalized experience that gets customers to resolution as fast as possible.

In my blog post from October, Make Your CRM More Effortless with Embedded, Contextual Support, I wrote about how real-time, contextual guidance doesn’t have to mean multiple 3rd party apps pulling up specific customer or product information for agents to read through and manually analyze before appropriately directing the customer.

Rather than an overloaded CRM interface with embedded applications, you can integrate a one-stop tool like Cloud that serves up advanced, tailored support knowledge and even on-screen agent scripting using intelligent data synchronization.

But how is this “intelligent data synchronization” – called Dynamic Decision Points – different from regular branching logic? How do Dynamic Decision Points actually work? And what do software developers need to know about this feature?

What are Dynamic Decision Points?

First, they’re called Dynamic Decision Points because they’re taking the decision tree branching logic of Decision Points to the next level. They automate the manual process behind Decision Points, where agents choose among several options that determine which way the support interaction flows, based on customer answers – i.e. Mac or PC? Software version 1.3 or 1.4?

How Do They Work?

Now, Dynamic Decision Points actually work by allowing developers to configure Guided Path steps, which can, at run time, interact and operate on REST/JSON HTTP request APIs or execute custom client-side JavaScript code to do multiple things:

1) Update state data (the data stored in the object that determines the current properties of the object); i.e. if you have an “Account” object, the user of the account and the status of the account represent the state of the account

2) Initiate an activity within an environment like a CRM or ticketing system, like executing a macro within Zendesk® or sending an email to the customer with information on the support request

3) Glean an answer based on the response, and use the answer in the Decision Point to navigate to the next appropriate step in the support workflow

What Developers Need to Know

Developers can configure Dynamic Decision Points within the Admin user role of the Cloud interface:


Dynamic Decision Points can refer to several types of actions:

Request Actions allow developers to specify the URL to send a request to, the request method, request headers, and request data

Script Actions allow developers to add custom JavaScript code to run on the client-side and to execute during Dynamic Decision Point processing

Dynamic Actions can be Request Actions (REST/JSON HTTP request call) or Script Actions (custom client-side JavaScript code)

With Dynamic Actions, developers must define:

• The input variables for the request

• The output values for evaluating rule conditions defined in the Dynamic Decision Point

Output of previously executed Dynamic Actions can combine with Cloud session data, user device data, data from an IoT (Internet of Things) platform’s event bus and other existing customer data to act as input for another Dynamic Action.

Once out of the development phase, Dynamic Decision Points are readily available to Cloud users assigned to the Designer role.

Designers can implement them at any time during the design phase by dragging and dropping into a Guided Path, thus configuring next-level Decision Points that do not require support agents to perform manual selections based on available answer options.

2nd-manage-picture Cloud makes it easy to prevent your customers from having to repeat information to support agents that you should already know. With minimal development work, you can create reusable Dynamic Decision Points for a variety of issue resolution scenarios within multiple Guided Paths.

Get started today and help make your support delivery a personalized experience that gets customer problems resolved as quickly and as painlessly as possible.

Personalized Customer Support: A Look Inside Intelligent Data Synchronization
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Personalized Customer Support: A Look Inside Intelligent Data Synchronization
During a customer support call, don’t make your customers tell your agents information that you should already know.
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Kim Lambert

Kim Lambert is Senior Product Marketing Manager at, where she owns product messaging, sales enablement, and marketing content for Cloud. Kim joined in January of 2016, bringing with her a passion for technology and a background in helping companies like Verizon, Intel, and Yahoo! build their brands and market a superior customer experience. Kim holds a Bachelor of Business Administration from Virginia Tech and an MBA from Duke University’s Fuqua School of Business.

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