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Axelerant/Work/White-Labeled Engagement
AxelerantWhite-Labeled Engagement
In partnership withConfigero
Case Study · technology

Creating Exceptional Customer Support Through A Salesforce Einstein Chatbot

Configero — In Partnership with

AxelerantWhite-Labeled

About

A next-generation solar technology company, our customer is known for their cutting-edge solar design engineering and development teams. Their tools help energy providers design advanced solar power plants.

Their AutoCAD plug-in is currently being used by customers in over 50 countries across the globe.

01

Streamlining Customer Support with a Salesforce Chatbot

Our customer, a global, tech-driven solar technology company, had been looking to streamline its customer support process. To achieve this, we set up a Salesforce Einstein chatbot in collaboration with our trusted partner agency, Configero.

This AI-enabled chatbot routes all inquiries to the correct agent. The result is streamlined, time-efficient, and delightful customer support.

White-Labeled Engagement website
White-Labeled Engagement · configero.com
02
The challenge

The existing chatbot triage system could not clearly categorize the end-customers according to their inquiries. The customer support team struggled to report proper feedback and take corrective actions without this information.

Multiple offerings and solution diversification over time added to the problem. This led to delays in closure and a decline in CSAT scores.

As a result, the service planning workflow was neither time-efficient nor cost-effective. The support team was unable to keep up with changing customer needs.

The client was determined to transform their customer service by resolving matters with minimum time and effort.

03
The solution

The solution had to be expansive and scalable to match the present and future needs of the business. An AI-enabled Salesforce chatbot became the solution.

The SF Chatbot would:

  1. Streamline the customer support process
  2. Fix the entire service planning workflow

To achieve this, we made sure that the chatbot enabled:

  • A custom case routing flow to replace the existing pre-chat forms
  • Routing all the queries and cases raised on the website to the triage
  • Properly queuing the queries for
  • Receiving customer information
  • Validating this information
  • Knowing the customer category in realtime
04
The result

The customer was able to:

  1. Streamline their CRM efforts
  2. Enable their support agents to close a higher volume of queries and leads
  3. Offer exceptional customer service

This solution reduced the volume of inquiries coming into the call center. It also eliminated haphazard calling schedules and emails by four times.

01

Empowered Decision Making

Better data from defined channels empowered sales reps to make data-driven decisions at every step of the case lifecycle.

02

Shorter Resolution Time for Agents

A clear path minimized haphazard calling. This shortened the query resolution time

03

Improved Customer Satisfaction

Relevant query routing and shorter resolution time led to improved customer service and increased customer satisfaction.

Project Highlights

Inside the build
03 highlights
Highlight · 0101/03

Einstein Bot

Configro Einstein Bot Image-1

The Einstein bot automates and resolves common issues raised by customers in their conversations on chat and messaging channels. This is a simple yet effective self-service solution for the client’s customers.

Highlight · 0202/03

Einstein Case Classification

Configro Einstein Case Classification-1

To lessen the support agents’ burden, we implemented case classification. It predicts field values such as reason, type, and priority of incoming cases based on the customers’ query subject and description.

Highlight · 0303/03

Einstein Case Routing

Configro Einstein Case Routing-1

Case Routing was incorporated to triage and route cases to the right queue and agent. From there, the Omni-Channel determines which agents are available and when the next agent would be available for resolution.

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