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Salesforce Exam Salesforce AI Associate Topic 4 Question 33 Discussion

Actual exam question for Salesforce's Salesforce AI Associate exam
Question #: 33
Topic #: 4
[All Salesforce AI Associate Questions]

What are the potential consequences of an organization suffering from poor data quality?

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Suggested Answer: B

The potential consequences of an organization suffering from poor data quality include revenue loss, poor customer service, and reputational damage. Poor data quality can lead to inaccurate analytics and decision-making, impacting customer interactions, marketing strategies, and financial forecasting. These issues ultimately affect customer satisfaction and could lead to financial losses and a damaged brand reputation. Salesforce highlights the importance of maintaining high data quality for effective CRM and AI applications, offering various tools and best practices to enhance data integrity. For guidance on managing and improving data quality in Salesforce, see the Salesforce documentation on data quality at Salesforce Data Quality.


by Alberto at Oct 23, 2024, 08:05 AM

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Kate
2 months ago
I'm with Tish and Tiera on this one. Option B captures the most critical consequences of poor data quality. Revenue and reputation are the lifeblood of any organization.
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Thersa
18 days ago
It's important for organizations to prioritize data quality to avoid these negative consequences.
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Filiberto
19 days ago
Poor customer service can also drive away loyal customers, leading to even more revenue loss.
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Sylvie
1 months ago
I agree, revenue loss and reputational damage can be devastating for a company.
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My
2 months ago
Haha, C reminds me of my old job. Constant technical debt and sluggish data processing - what a nightmare! Definitely not the answer though, B is the clear winner.
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Silvana
2 months ago
Hmm, I'd say A is the way to go here. Poor data quality can really hurt employee morale and make it tough to attract top talent. That's a recipe for disaster in the long run.
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Macy
1 months ago
A combination of these consequences can really hinder the overall success of the organization.
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Chantell
1 months ago
It's true, attracting top talent becomes challenging when the organization has a reputation for poor data quality.
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Ashton
1 months ago
Definitely, stock devaluation can also impact the financial stability of the organization.
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Inocencia
2 months ago
I agree, low employee morale can lead to decreased productivity and high turnover rates.
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Tiera
2 months ago
I'd have to go with B as well. Losing cusTieraers and having a tarnished brand reputation is a death sentence in today's competitive market. Not good at all!
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Jonelle
1 months ago
It's important to prioritize data quality to avoid these issues.
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Berry
1 months ago
Definitely, losing customers can have long-lasting consequences.
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Galen
1 months ago
It's true, reputational damage can be hard to recover from.
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Geoffrey
1 months ago
I agree, revenue loss and poor customer service can really hurt an organization.
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Tish
3 months ago
Option B is clearly the right answer. Revenue loss and reputational damage are the most serious consequences of poor data quality. Customers won't stick around if the service is subpar.
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Harrison
1 months ago
User 4: It's important to prioritize data quality to avoid these issues.
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Christiane
1 months ago
User 3: Poor data quality can have serious consequences for an organization.
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Annamae
2 months ago
User 2: Revenue loss and reputational damage can really hurt a company.
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Lorean
2 months ago
User 1: I agree, option B is definitely the correct answer.
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Rosalyn
3 months ago
I agree with Emilio. Poor data quality can definitely lead to those consequences, affecting the overall success of the organization.
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Emilio
3 months ago
I think the potential consequences of poor data quality are revenue loss, poor customer service, and reputational damage.
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