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Salesforce ANC-201 Exam - Topic 3 Question 38 Discussion

Actual exam question for Salesforce's ANC-201 exam
Question #: 38
Topic #: 3
[All ANC-201 Questions]

A customer has a dataset consisting of over 300 unique product names. They request a prediction model with the product names included.

Which action should the CRM Analytics consultant take?

Show Suggested Answer Hide Answer
Suggested Answer: C

by Becky at Jun 29, 2024, 09:10 PM

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Angelo
3 months ago
Default variables might not capture all the nuances of the products.
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Winfred
3 months ago
Wait, over 300 product names? That sounds like a lot to manage!
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Hollis
3 months ago
Splitting into multiple models could complicate things.
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Alton
4 months ago
I disagree, product names are important for context!
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Lonna
4 months ago
Option C makes the most sense, SKU numbers are clearer.
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Bulah
4 months ago
I feel like we had a similar question in our last practice session, and I think splitting the analysis was the recommended approach then too.
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Essie
4 months ago
Using SKU numbers sounds like a good idea for clarity, but I wonder if that would lose some context from the product names?
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Evan
4 months ago
I'm not really sure about the default variables. I think we practiced a question where using specific attributes was more effective, but I can't recall the details.
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Bambi
5 months ago
I remember we discussed how too many unique categories can complicate the model, so maybe splitting it into multiple models could help?
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Ahmed
5 months ago
Okay, I've got a strategy for this. I think using SKU numbers instead of product names is a smart move. That should help simplify the model and make it more clear. I'm going to go with option C on this one.
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Burma
5 months ago
I'm a bit confused on this one. Using the default variables in the Product object seems like it could work, but I'm not sure if that's the best approach with so many unique product names. Might need to think through the pros and cons of each option.
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Johnna
5 months ago
This seems like a tricky one. I'm not sure if I should split the analysis or try to run the model with all the product names. Might need to do some research on handling large datasets with many variables.
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Darrin
5 months ago
Hmm, I think option A is the way to go here. 300 unique product names is a lot to include in a single model. Breaking it down into smaller models with fewer products would probably work better.
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Charlesetta
5 months ago
Hmm, I'm a bit confused by the wording of the question. I'll need to re-read it a few times to make sure I understand what they're asking.
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Leonor
10 months ago
I'd go with option A. Splitting the analysis into multiple models is like cutting a giant pizza into smaller slices - it's easier to handle and you can still enjoy the whole pie!
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Lashandra
10 months ago
Wow, 300 unique product names? That's a lot to work with! I hope the CRM Analytics consultant has a big cup of coffee ready for this one.
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France
9 months ago
That's a good idea, using SKU numbers would definitely make things easier to manage.
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Michel
9 months ago
C) Use SKU numbers rather than product names to increase clarity.
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Ronny
9 months ago
A) Split the analysis into multiple models with each having fewer products.
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Francesco
10 months ago
Using SKU numbers instead of product names is an interesting idea. It could help increase clarity and potentially simplify the model, but I wonder if it might lose some important product-specific information in the process.
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Kimberlie
9 months ago
I agree, using SKU numbers could simplify the model but we might lose important product-specific information.
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Joni
9 months ago
C) Use SKU numbers rather than product names to increase clarity.
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Mary
9 months ago
A) Split the analysis into multiple models with each having fewer products.
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Barrett
10 months ago
Using the default variables in the Product object might be the easiest option, but I'm not sure if it will capture the nuances of all 300 unique product names. It's worth considering if the default variables are sufficient.
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Ashley
9 months ago
A: Agreed, we need to consider the best approach to accurately predict with such a large dataset.
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Alonso
9 months ago
C: It's important to ensure the model captures the nuances of all 300 unique product names.
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Gayla
10 months ago
B: Using SKU numbers might make it easier to handle the large number of unique product names.
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Royal
10 months ago
A: I think splitting the analysis into multiple models could be a good idea.
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Marti
11 months ago
Splitting the dataset into multiple models seems like a reasonable approach to handle the large number of products. That way, the model can focus on a smaller subset of products and potentially improve performance.
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Delpha
10 months ago
That sounds like a good idea. It can help with managing the large number of products in the dataset.
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Domitila
10 months ago
A) Split the analysis into multiple models with each having fewer products.
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Bette
11 months ago
I agree with Mira, splitting the analysis would make it more manageable and accurate.
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Rodrigo
11 months ago
I disagree, using SKU numbers would be more clear and efficient.
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Mira
11 months ago
I think we should split the analysis into multiple models with fewer products.
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