Maximize Your Support Department Efficiency with Embedded Analytics
Introduction
Nowadays, many customers want to understand the products and services offered by a company before purchasing, and they want to know that they can get answers to any questions they have after purchasing. As a result, companies’ customer support departments are crucial to solving customers’ issues and keeping them satisfied with your company.
Embedded analytics boost the performance of support teams by allowing leaders to gain insight into their real-time data and address issues as they occur. In this blog, I will discuss how Bold BI helps managers in support departments make decisions based on analytics using the following subtopics:
- What is embedded analytics?
- Benefits of embedded analytics in support departments.
- How to embed analytics into support department apps.
- Bold BI’s support department dashboard examples.
What is embedded analytics?
Embedded analytics is the integration of analytical solutions and data visualization capabilities into a software application’s user interface to improve data comprehension and usability. Bold BI helps you easily embed an analytics solution into your everyday work applications using a JavaScript SDK and server application. This enables your support team to have a clear picture of their users’ preferences and how they interact with different services, letting them understand trends and make proper decisions on increasing their productivity and offerings.
Benefits of embedded analytics for a support department
Analytical tools embedded in a support department app give you a true picture of the quality of the products and services you offer, how time is used and managed by your employees, and the growth pattern of your business by visualizing metrics in a dashboard. Let us see how embedded analytics helps a support team:
- Offer better customer service.
- Increase customer retention.
- Effectively manage time.
- Easily maintain workflows.
Offer better customer service
A company’s prestige depends on the quality of their products and services. Whatever you sell, the customer support for it is one of the services that makes your customers loyal to or disappointed with your brand. With embedded analytics, the team lead in the support department can easily track metrics such as response time, satisfaction surveys for agents, and first response time versus resolution time. Through monitoring these metrics, the lead will identify patterns their customers’ feedback, queries, and opinions of their brand. Using these insights, they can offer better service to their customer in the future by working on issues causing negative feedback and adjusting methods to respond to queries quickly.
Increase customer retention rate
Improving your customer service by itself will increase the brand loyalty of your customers. By monitoring indicators such as customer retention rate, churn rate, and net promoter score, you will have a good idea of the health of that brand loyalty. Examining patterns in the feedback from customers, like common complaints or compliments, lets you know what keeps some customers with your company and what made some of them churn. Using this information, you will be able to reduce churn rate and retain more customers by solving churn rate issues such as providing clients learning materials on your products. Continued monitoring of the metrics will let you see whether your strategies to improve your products and customer service are working.
Effectively manage time
Setting timelines for activities carried out in your company is one of the most important ways to keeping it running smoothly. Embedded analytics makes this simpler by allowing you to track metrics such as average time to resolution and the created and closed incidents. By analyzing these metrics, team leads understand how much time their team members require on average to address specific kinds of incidents. They can better distribute work among the team members and draw a proper timeline, increasing efficiency and productivity.
Easily maintain workflow
Embedded analytics helps managers in support departments optimize their workflow by enabling them to track metrics such as customer satisfaction rate, ticket count over time, and ticket count versus satisfaction rate. With these insights, they can more accurately predict future workloads and plan for adequate staffing and training.
How to embed analytical tools into support domain apps
Let’s see how analytics can be embedded into support web applications. Bold BI can embed your dashboards in more than 18 web platforms, including React with ASP.NET Core, React with Go, WinForms, Node.js, Vue with Go, and Vue with ASP.NET Core. I am going to provide a walkthrough specifically on embedding dashboards in ASP.NET Core applications.
Suppose your support department has a site like the one shown in the following image.
You can embed dashboards easily using Bold BI and avoid building an analytics or BI solution yourself, saving development time. Follow these steps to embed your dashboard successfully.
Prerequisites
Deploy Bold BI in your local machine and create an enterprise-grade dashboard.
Step 1: Create an ASP.NET Core application.
To successfully embed a dashboard into your application, first you need to create an ASP.NET Core application. Open Microsoft Visual Studio and create a new project. Then, choose ASP.NET Core Web Application, enter the project name, and click OK.
Step 2: Configure embed properties.
After the ASP.NET Core web application is created, you need to create a model class called EmbedProperties under Models and provide the dashboard RootURL, SiteIdentifier, Environment, UserEmail, and EmbedSecret.
RootUrl : Bold BI dashboard server URL. Example: http://localhost:58094/bi.SiteIdentifier : For Bold BI, it should follow the format `site/site1`. For Bold BI Cloud Analytics Server, it should be an empty string.Environment : Your Bold BI application environment. If using Bold BI Cloud Analytics Server, you should use `cloud`. If using Bold BI, you should use `enterprise.’UserEmail : The Bold BI server will use an email address to authorize the authorization server.
Step 3: Generate embed secret.
You have to set the embed secret for authentication. You can get the embed secret from the Bold BI server. Then, navigate to the Settings icon on the left navigation bar and click the Embed tab. Turn on the Enable embed authentication option, and click the Generate Secret button. On clicking the button, a secret code will be generated. Copy the saved secret key and paste it into the application. To learn how to do this in detail, you can refer to this documentation.
Note: Save the secret key, as it cannot be retrieved again. If it is not saved, you will have to regenerate it using the Reset Secret option.
Step 4: Create authorization server.
You need to implement an authorization server in the ASP.NET Core application to get authenticated before embedding the dashboard from the Bold BI server. You can also configure a single sign-on (SSO)-based authorization server, which is an authentication endpoint that enables users to securely authenticate multiple applications using a unique embed secret. This prevents the need for the user to log into different applications separately.
Step 5: Create Bold BI instance.
Create a Bold BI instance to load the dashboard using a JavaScript file. Also, reference required script files and CSS files in HTML pages.
Step 6: Run the application for embedding the dashboard.
After successfully creating the ASP.NET Core application, you need to run the ASP.NET Core application. It will be launched with the dashboard details. Finally, you can see the dashboard from the Bold BI server is embedded into your web application.
To learn more about embedding dashboards into your applications, please refer to the blog “Integrating Dashboards into Applications with the Embed SDK.” You can also download the sample code mentioned in all these steps from our documentation.
Bold BI’s support solution dashboard examples
Incident management dashboard
Embedding an incident management dashboard like the following, which was created using the ServiceNow integration, allows you to monitor your incident details over a period of time. You have accurate information regarding average resolution time for an incident and the status of incidents based on priority and category.
Key metrics and KPIs:
Resolved and unresolved incidents: The line chart tracks resolved and unresolved incidents by date of the current month.
Average time to resolution: This doughnut chart shows the average time to resolution for one incident.
New incidents: The total number of newly created incidents by the date of current month.
New incident by category: Numbers of newly created incidents by category.
Created and closed incidents for the last six months: This shows the number of created and closed incidents in the last six months.
To learn more about the metrics and KPIs used in this dashboard example, refer to the incident management dashboard demo.
Customer Support Monitoring Dashboard
Embedding the Customer Support Monitoring Dashboard example helps to analyze your support ticket volumes over time using the Zendesk integration. Get detailed information about the volume of tickets based on priority, type, and satisfaction rate over time.
Key metrics and KPIs:
Tickets by type: The bar chart shows how many tickets are feature requests, bugs, and sales inquiries.
Ticket count vs. satisfaction rate: The spline chart displays the number of tickets and the team’s customer satisfaction rate for the current month.
Ticket by channel: The doughnut chart shows the means by which your customers created support requests and how you engaged with them. This identifies the channels your customers are mostly using.
Ticket by priority: The pie chart provides details regarding ticket response time and resolution time based on priority.
Created tickets: The number card shows tickets created by the end-user within the last 7 days.
Closed tickets (last 30 days): The number card shows the final status of tickets after the customers changed the task statuses to resolved.
Satisfaction rate: The number card shows an overall percentage of how satisfied your customers are with your products and services.
To learn more about the metrics and KPIs used in this dashboard example, refer to the Customer Support Monitoring dashboard demo.
Customer Ticket Traffic Management Dashboard
Embedding the Customer Ticket Traffic Management Dashboard example, which was created using the Freshdesk integration, in your application gives you detailed view of your customer tickets.
Key metrics and KPIs:
Customer satisfaction rate (CSAT): The radial gauge shows the percentage of customers satisfied with the product or service.
First contact resolution rate (FCR): The radial gauge measures the percentage of requests resolved during the first interaction with the customer.
Customer retention rate: The radial gauge measures the percentage of existing customers who remain customers after a given period. It enables you to identify customers that are satisfied with your company and can also signal opportunities to improve customer service.
Net promoter score: The radial gauge measures the likelihood that customers will recommend your product or service.
Churn rate: The radial gauge shows the rate at which customers stop doing business with a company over a given period of time.
Logged vs. resolved tickets by month: The spline area shows tickets logged and tickets resolved over the last six months.
Open ticket summary: The grid shows the open ticket information, including ID, subject, type, and priority.
To learn more about the metrics and KPIs used in this dashboard demo, refer to the Customer Ticket Traffic Management Dashboard example.
Agent activity dashboard
Embedding the Agent Activity Dashboard, which was created using the Freshdesk integration, helps in tracking overall ticket details.
Key metrics and KPIs:
Tickets by agent and status: This stack column chart shows the total tickets by status and agent.
Unresolved tickets by priority: This doughnut chart shows the percentage of unresolved tickets by priority.
Tickets by group: The tree map chart shows the total tickets by group.
Average response time: The number card shows the average time taken by an agent to respond to a ticket.
Response time: The bar chart shows the average time taken by an agent to respond to a customer.
To learn more about the metrics and KPIs used in this dashboard example, refer to the Agent Activity Dashboard demo.
Voice calls and SMS tracking dashboard
Embedding the Voice Calls and SMS Tracking Dashboard example helps you to gain insight from your Twilio data, such as your calls and messages over time, number of calls and messages sent and received, and much more.
Key metrics and KPIs:
Calls by date: The spline chart shows the total number of calls with statuses complete, failed, and no answer for current month.
Messages by status: This doughnut chart measures the total number of messages delivered and undelivered.
Calls by status: The doughnut chart shows the total number of calls by status: complete, failed, and no answer.
Messages by date: The spline chart measures the total number of messages delivered and undelivered by date of current month.
To learn more about the metrics and KPIs used in this dashboard demo, refer to the Voice Calls and SMS Tracking Dashboard example.
Conclusion
Bold BI integrates dashboards into your applications written in ASP.NET Core, ASP.NET MVC, Angular, ASP.NET, and Ruby on Rails. It will save you time and prevent you from doing redundant work. Click this link to explore its features. To learn more about embedding dashboards into your application, refer to this blog and our documentation.
I hope you now have a better understanding of Bold BI and how it can help a support team. You can create a dashboard any way you like with Bold BI’s 35+ widgets and 130+ data sources.
To get started with Bold BI, sign up for a free 15-day trial and begin creating interactive business intelligence dashboards. You can contact us by submitting questions through the Bold BI website or, if you already have an account, you can log in.
Originally published at https://www.boldbi.com on May 4, 2022.
