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Free ANC301 Exam Braindumps (page: 4)

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Universal Containers (UC) builds three Einstein Discovery models in Salesforce to predict and maximize its revenue per customer. The models are for every region UC has a business: EMEA, AMER, and APAC.
How should a consultant help UC deploy the three Einstein models to Salesforce?

  1. Filter the account data per region and deploy the same model to all segments.
  2. Segment the account data per region and deploy the appropriate model for each segment.
  3. Deploy the same mode! to all accounts and use an Apex trigger to segment the prediction.

Answer(s): B

Explanation:

In deploying Einstein Discovery models that are tailored to different regions (EMEA, AMER, and APAC), the best approach is to segment the account data by region and apply the specific model designed for each segment. This method ensures the following:
Relevance and Accuracy: Each model can be specialized to understand and predict based on regional dynamics, which may differ significantly across geographies in terms of market behavior, customer preferences, and economic conditions.
Efficiency: Deploying region-specific models avoids the dilution of predictive power that might occur if a single model were used across all regions, which could lead to less accurate predictions. Scalability: This approach is scalable as UC can further refine each model as more regional data becomes available or as regional market conditions evolve.



A company wants to create a timeline chart to visualize the evolution of its Closed Won opportunities.



What are the required parameters to build a lens that displays output similar to the image shown?

  1. 1 measure, 0 groupings if trellis Is disabled, or 0-2 groupings If trellis is enabled
  2. 1 measure, 1-2 groupings if trellis is disabled, or 1-4 groupings if trellis is enabled
  3. 1 measure, 1 grouping by a date field, and either 0-1 groupings groupings by a dimension if trellis is disabled, or 0-2 groupings if trellis is enabled

Answer(s): C

Explanation:

To create a timeline chart similar to the one shown, the following parameters are typically required:
1 Measure: This could be the count of Closed Won opportunities or any other relevant metric that needs to be tracked over time.
1 Grouping by a Date Field: This is essential to plot the timeline effectively. The date field would typically be the close date of the opportunities.
Additional Groupings: Depending on the complexity and the detail needed, additional groupings can be added. For example, grouping by region or product line can provide more insights into the timeline. If trellis is used, it allows for the creation of multiple smaller charts within the main chart, each representing a slice of data based on the additional groupings. This setup helps visualize the evolution of Closed Won opportunities over time, making it easy to spot trends, seasonal patterns, or other relevant insights.



A CRM Analytics consultant at Cloud Kicks wants to create a new dashboard that uses custom

GeoJSON to display data; however, they are unable to upload the file via the user interface (UI).
Which action should the consultant take?

  1. Add the system permission "Manage Analytics Custom Maps" to the permission set used.
  2. Enable Custom maps with GeoJSON"" in the analytics settings.
  3. Upload the GeoJSON via the API because it is NOT a function in the UI.

Answer(s): C

Explanation:

If a consultant at Cloud Kicks needs to use custom GeoJSON files for dashboard visualization and cannot upload the file via the CRM Analytics user interface (UI), the recommended action is to use the API for this purpose. Here's why this approach is suggested:
Functionality Limitation in UI: Currently, the CRM Analytics UI does not support direct uploads of GeoJSON files, which necessitates an alternative method. API Flexibility: The API provides a more flexible route for uploading custom GeoJSON files, allowing consultants to integrate more complex or larger datasets that are not supported through standard UI functionalities.
Customization and Control: Using the API also offers greater control over how GeoJSON data is handled, processed, and utilized within CRM Analytics, catering to more advanced customization needs.
This method ensures that the consultant can fully utilize CRM Analytics' capabilities for creating highly customized geographic visualizations, thereby enhancing the analytical value of the dashboards.



A company realizes it has a lot of rich information around its cases, but unfortunately, most of this is unstructured/textual dat

  1. The company is exploring how to include some of this information in its case prioritization.
    Which option within CRM Analytics should a consultant leverage?
  2. Bucket transformation in Recipes
  3. Cluster transformation in Recipes
  4. Detect Sentiment transformation in Recipes

Answer(s): C

Explanation:

For a company with a wealth of unstructured textual data in their cases, the "Detect Sentiment" transformation within CRM Analytics Recipes is a crucial tool. This transformation analyzes the sentiment of the text data--whether it's positive, neutral, or negative--and this insight can be highly valuable in case prioritization processes. Here's why this transformation is useful:
Insight into Customer Sentiments: By detecting sentiment, the company can prioritize cases based on the urgency and emotional tone expressed in the text, which might indicate customer dissatisfaction or urgency.
Automation and Efficiency: Automatically categorizing cases based on sentiment can streamline workflows and ensure that critical cases are handled promptly.

Enhanced Customer Service: Responding to negative sentiments swiftly can improve customer satisfaction and potentially mitigate issues before they escalate.






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