Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Appian ACA100 Exam - Topic 5 Question 38 Discussion

Posted by Reuben on Jun 17, 2026 at 12:53 AM

An organization wants to automate identification of its dissatisfied customers based on the ticket description and assign the appropriate team to provide a quick resolution.

What is the best way to auto-classify the dissatisfied customers as part of processing?

Suggested Answer: A

The organization aims to automate the identification of dissatisfied customers based on the ticket description. To achieve this, leveraging natural language processing (NLP) capabilities is the most efficient method. Appian provides connected systems that allow integration with external NLP services. These services can analyze text data (such as ticket descriptions) to determine the sentiment or classify the text into predefined categories (like 'dissatisfied customer').

Natural Language Connected System:

Appian can integrate with third-party NLP platforms such as Google Cloud Natural Language, AWS Comprehend, or Azure Text Analytics via connected systems.

These services analyze the text provided in the ticket description to detect sentiment, keywords, or specific categories indicating dissatisfaction.

Based on the analysis, the system can automatically assign the appropriate team to handle the case.

Why Not Other Options?:

B . Decision Table: While decision tables are useful for rule-based decisions, they are not suitable for interpreting unstructured text like ticket descriptions.

C . Image Analysis Connected System: This option is irrelevant as the task involves text processing, not image analysis.

D . SAIL Form: SAIL forms are primarily used for user interface creation and are not intended for text analysis or classification.

Implementation in Appian:

Create a connected system to integrate with the chosen NLP service.

Configure the NLP service to analyze the text data and return the sentiment or classification results.

Based on the results, use process models to route the ticket to the appropriate team for resolution.

References:

Appian Documentation on Connected Systems: Appian Connected Systems

Appian Community Success Guide: Appian Delivery Methodology

Third-Party NLP Services Integration: Google Cloud NLP Documentation


Get Premium ACA100 Questions as Interactive Web-Based Practice Test or PDF Real Exam Format Detailed Explanations Instant Access Get Your Practice Test
12 comments · newest first
GI
Gianna 2 months ago
B could work too, but it’s less flexible than A. Decision tables might miss nuances.
DO
Doug 2 months ago
I agree with A. It understands context and sentiment well.
OL
Ollie 2 months ago
I think A is the best choice. Natural language processing can analyze ticket descriptions effectively.
AN
Annamae 2 months ago
Totally agree with A)! Natural language processing is key!
KA
Kara 2 months ago
D) sounds too complicated for this task.
BE
Becky 2 months ago
Wait, C) for image analysis? That seems off.
SA
Sage 3 months ago
I think B) could work too, but not as efficiently.
AL
Alonzo 3 months ago
A) is definitely the way to go!
LI
Linsey 3 months ago
This reminds me of a practice question where we used NLP to classify customer feedback. So, I'm leaning towards option A as well.
DA
Daryl 3 months ago
I feel like image analysis isn't relevant here, so I would rule out option C. But I can't recall what a SAIL form is.
SH
Shelba 3 months ago
I'm not entirely sure, but I remember something about decision tables being useful for classification tasks. Could that be option B?
FA
Fatima 4 months ago
I think option A makes the most sense since natural language processing can analyze ticket descriptions effectively.
0/2000 characters

Save Cancel