Strategies For Cloud Contact Center Platform API Management


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A happy and satisfied customer base can be worth its weight in gold—which is why organizations are investing in cloud contact center platforms to ensure that their online customer interactions are handled effectively.

Cloud contact centers have become the cornerstone of modern call centers. They advance the concept of customer centricity while equipping agents with a unified interface for handling inbound and outbound communications. 

At the same time, a typical cloud contact center also provides features you won’t always find with on-premises call centers. 

To optimize customer experience, cloud contact centers juggle many application program interfaces (APIs) to handle tasks that facilitate positive online interactions. This is why API management is critical for cloud contact center success.

What Is a Cloud Contact Center?

A cloud contact center is a cloud-native platform built for omnichannel and multichannel communications between an organization and its customers. It is an omnivorous communication hub that includes Voice over Internet Protocol (VoIP) capabilities, as well as email, chat, social media, and SMS.

Cloud contact centers mainly operate as software-as-a-service (SaaS) solutions. As such, they provide cost-effective benefits to customers who only pay for what they use, therefore allowing the organization to optimize and scale its business operations. 

Additionally, cloud contact centers also eliminate the need for traditional, on-premise centers with their significant cost outlay of hardware and equipment—not to mention the need for a physical, boots-on-the-ground presence of employees.

Along with call routing, cloud contact centers provide various functions through an integrated system of APIs, including the following modules:

  • Automatic call distributor (ACD): Enhances omnichannel routing by connecting customers to the best agent or solution through behind-the-scenes routing.
  • Interactive voice response (IVR): Provides self-service automation to customers through an audible menu, boosting customer engagement by offering personalized choices through natural language processing.
  • Workforce management (WFM): Empowers contact centers to achieve productivity goals by optimizing the contact center employee and agent output. WFM engages employees, automates tasks, and meets staffing needs for different digital channels. 
  • Analytics and reporting: Turns data into actionable insights while producing the results into formatted, digestible reports. 
  • Integration with other services: Provides features such as customer relationship management (CRM) and unified communications as a service (UCaaS) that allow you to operate a holistic cloud contact center.
  • Call recording and monitoring: Measures staff performance with real-time data to maintain adequate cloud-center quality control.
  • Automation and Artificial Intelligence (AI): Uses cutting-edge technology to automate tasks and enhance the complexity of the customer journey by understanding patterns invisible to the human eye. 

In addition to providing remote access to customers, the overall objective of a cloud contact center is to provide scalability, flexibility, and a high degree of reliability to customer support operations.  

Overview of API Management in Cloud Contact Centers

APIs are vital communication tools in today’s digital ecosystem because they provide a mechanism for many systems, digital agents, and software services to communicate and share information effectively. 

This provides businesses with an abundance of integration opportunities, and it’s why we encounter APIs virtually every time we use online services. For instance, to get weather updates on your phone, weather apps will make API calls to collect data from various weather stations, including the National Weather Service (NWS) if you’re in the United States.

By playing an intermediary role, APIs provide a set of definitions and protocols that standardize how interactions like these occur. For instance, an API specifies how an application exposes its functionality to a public interface, how a request must be encoded, and how the corresponding response is formatted.

When you put it all together, API management offers a way to scale cloud contact center operations, improve performance, enforce the right policies, and analyze usage metrics. 

How APIs Are Important to Contact Centers

Since APIs play a considerable role in the vast integration capabilities of cloud contact centers, they are especially useful for maintaining an omnichannel approach—which often requires serving customers on many different platforms and devices.

To run smoothly, contact center platforms need to incorporate diverse technologies like CRM, email marketing software, and automation systems. Without these integrations, customer service agents will have to juggle a discombobulated set of services to keep track of their work. Therefore, APIs are the adhesive tape that binds a contact center’s blended architecture together. 

The Role of APIs in Personalization, Automation, and Overall Cloud Contact Center Enablement

APIs are a force for progress in cloud contact centers, allowing organizations to respond to customer requests faster while simultaneously increasing agent productivity by expanding their capacity to attend more support channels.

APIs Facilitate Personalization Opportunities

Personalization is an important strategy for cloud contact centers, and it is one of the things APIs are adept at providing. 

In addition to integrating systems and applications, APIs deliver integrated customer experiences by virtue of their ability to collate a snapshot of customer behavior over a period of time. This is ripe for personalization. 

For example, APIs provide easy ways to access, retrieve, and display information such as a customer’s name, address, and user preferences, including their billing and order history.

Thus, by drawing on an individual customer’s history, tastes, desires, and expectations, APIs provide instant opportunities to tailor the customer service experience.

Furthermore, the automatic retrieval of these data points also allows organizations to leverage APIs to offer self-service options and personalized interactions that wouldn’t have been possible otherwise. This is key for keeping customers engaged and feeling valued. 

Automation and APIs – Two Peas in a Pod

Automation is geared to eliminate manual work and reduce repetitive tasks, especially rote ones that don’t require much creativity. Automation and API often go hand-in-hand simply because APIs connect multiple systems while reducing the redundancy and duplication of efforts that are the hallmarks of automation systems. 

Strategies for the Cloud Contact Center Platform API Management Cycle

API management requires a strategic approach that outlines the goals and objectives of the users and stakeholders of the cloud contact center. 

Likewise, API lifecycle management is a process that encompasses designing, implementing, publishing/deploying, maintaining, and monitoring APIs in a secure environment. 

As a software artifact, the API lifecycle needs to be managed like any other software project; the APIs must be built and managed for resilient sustainability because service disruptions can have an immediate, negative impact on cloud contact center operations. 


Because software is complex and complicated, it’s no surprise that various approaches have evolved to tame the unwieldy beast of its development. These approaches range from waterfall and agile methodologies to DevOps systems that incorporate continuous integration and continuous deployment (CI/CD) workflows.

As a result of API being a software component, its development is also guided by the same general steps of the typical software development lifecycle (SDLC):

  • Research and information-gathering. This involves identifying the goals of the API and its intended audience. For cloud contact centers, this may require interviewing the agents who use the existing on-premises system to get their input on how things can be improved.
  • Designing the API architecture. Here is where system architects and UX designers shine in planning out a system that meets the challenges required for a cloud-based contact center. In addition to functional requirements that denote what the API can do, they must anticipate how to incorporate the less tangible goals of usability, reliability, scalability, security, and performance. 
  • Coding the API. This is where the conceptual designs are translated into functional code by developers. Although generally categorized as distinct phases, the programming phase of API development usually incorporates unit testing as well.

The development phase is generally equipped to provide clients with API-enabled resources and features for a comprehensive cloud contact center platform, such as the following:

  • Voice. This encompasses phone and the best VoIP services incorporated through cloud contact APIs.
  • Video. An in-browser video that provides high-quality rendering in a secure meeting environment without requiring an app. 
  • SMS. For bulk delivery of targeted SMS communications to a vast audience.
  • Social media messaging. For sending and receiving customer messages across various social platforms. 
  • Team messaging. Enables contact centers to build chatbots for personalized communications with notification triggers and add-ins such as team messaging.
  • Meetings. This functionality lets you leverage APIs to create online meetings, collect information, and review subsequent recordings. 
  • Webinars. Provides the ability to schedule and conduct webinars at scale, with the capability to manage up to 10,000 attendees. 
  • Data compliance. This is for businesses like contact centers to stay compliant with industry regulations when handling customer data. Organizations must ensure no regulatory violations even as they create intelligent customer experiences. 


Testing is an integral part of the API SDLC process, so development teams adopt various forms of testing to create prototypes and mockups. Incidentally, API automation is also used in the testing process itself to ensure it produces robust, resilient, and reliable software with minimal logical and functional errors. 

Generally, API tests are easier than graphic user interface (GUI) tests because they are more streamlined and efficient to maintain.  

Mocking is fundamental to unit testing because running tests on real data can be risky for compliance and privacy-related reasons. Instead, mocking removes dependencies, replacing them with objects and payloads that you can control and evaluate with increased reliability.

When testing a cloud contact center, mocking offers the following benefits and advantages:

  • It allows quality assurance (QA) teams to simulate component dependencies quickly.
  • It helps isolate the unit component under each test. 
  • It allows failures to be isolated in components or units without “contaminating” other parts of the application during testing. 
  • It doesn’t rely on real data or objects, so the testing process can run at any time.
  • It can proceed without the need to store redundant information.

There are various forms of API testing, including the following:

  1. Unit testing. This involves testing a single component or unit of functionality with respect to the overall software or API. 
  2. Validation testing. This test ensures the API generates the intended results in the proper format. It checks that the input parameters will yield the desired outputs. 
  3. UI testing. This revolves around the application’s user interface, evaluating whether the API can handle the UI’s inputs correctly while generating the proper output for the user. 
  4. Regression testing. This ensures that changes or updates made to the API don’t break existing functionality.
  5. Functional testing. This is a test for business logic, input/output validation, and error handling to ensure the API functionality operates according to stipulated specifications. 
  6. Load testing. This test evaluates the API’s resilience, performance, and stability under stressful environmental conditions.
  7. Runtime error detection testing. This type of testing evaluates how the API copes with runtime errors such as memory leaks, network timeouts, invalid input parameters, and so on. It’s useful to see if an app can handle errors gracefully without abruptly crashing or terminating unexpectedly. 
  8. Fuzz testing. This testing mode tries to decipher how the API handles unexpected, erroneous, and invalid inputs. It evaluates how the API responds and recovers from unexpected behavior.
  9. Penetration testing. This is essentially a security test conducted by white hat hackers to safeguard against malicious attacks. They simulate infiltration attempts on the system/API, looking for weaknesses and vulnerabilities. 


Deployment is part of the implementation phase of API development, responsible for delivering the final product to the customer—or, in this case, an API application to the cloud contact center platform. 

Deployment isn’t a one-off event because most software tends to be updated and maintained constantly. Because it is continuous, deployment mechanisms are often automated to streamline the delivery process. This is usually included in the SDLC’s integration framework and CI/CD pipeline.

In modern deployment operations, automation processes will typically oscillate between testing and production environments. This is because the automated CI/CD workflow reuses and incorporates the tests crafted during the earlier testing phase. The CI/CD pipeline also runs integration tests as a way to ensure backward compatibility with previous API versions. 

This framework provides API DevOps teams with a repeatable process that produces reliable and well-tested deployments.

Post-deployment reviews are conducted and documented for further improvements and to boost institutional knowledge of deployment best practices. 


This phase is for inspecting and evaluating the published API. Monitoring is highly proactive, enabling you to refine the API based on an iterative feedback loop that alerts you on what to improve next.

Moreover, management typically expects ongoing performance reports on the API, and monitoring provides the opportunity to provide them.

In general, monitoring involves analyzing typical API usage metrics such as response times, churn rate, number of monthly active users, monthly revenue (for monetized APIs), and other data points that help to evaluate revenue growth.


Versioning is the process whereby development teams assign unique names or version numbers to different API or software application releases. It helps expand the API’s capabilities in a stable way while keeping a historical catalog of changes. This is helpful for development teams to make regular code updates while also maintaining backward compatibility. 

Versioning offers several advantages.

  • It allows you to identify and document the resources and capabilities an API exposes.
  • It provides a means to announce and highlight changes for users. If it breaks certain other apps that rely on the API, users won’t be caught by surprise.
  • It highlights the degree of backward compatibility allowed in each version.
  • It outlines the API resources, features, and capabilities, allowing users to direct their requests with specificity.

The versioning stage is also when you start to solidify your API maintenance and management processes. For instance, you can begin to define how you will be producing documentation, SDKs, and education resources for users and other technical stakeholders to maintain the API.

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