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Adaptive Planning
Last Updated: 2026-03-13
Reference: Data Exploration: Prompt Examples

Reference: Data Exploration: Prompt Examples

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Summarizing Data

Summaries provide a narrative and visual overview of a specific data set.
Ineffective Prompt
Effective Prompt
“Tell me about revenue”
Why it’s ineffective:
  • Too vague.
  • Lacks details about what aspect of revenue to summarize.
"Summarize 4100 Product Revenue by Product Line and Region for North America over Q1 2024, highlighting the top 3 contributors"."
Why it’s effective:
  • Specifies:
    • Action (Summarize)
    • Account (4100 Product Revenue)
    • Dimensions (Product Line, Region)
    • Location or level (North America)
    • Time (Q1 2024)
  • Focuses on top contributors for actionable insights
"Summarize expenses"
Why it’s ineffective:
  • Too vague.
  • Lacks details about what aspect of expenses to summarize.
"Summarize Operating Expenses for Marketing by Account and Month for the last 6 months"
Why it’s effective:
  • Specifies:
    • Account (Operating Expenses)
    • Dimensions (Account, Marketing, Month)
    • Time (last 6 months)
  • Anchors the summary to a specific organizational level and provides a clear rolling time horizon.

Comparing Values

Comparisons allow you to view different versions, accounts, or dimension values side-by-side.
Ineffective Prompt
Effective Prompt
“How do actuals compare?”
Why it’s ineffective:
  • Doesn’t clarify what to compare actuals against or the scope of the query.
"Compare Actuals to Forecasts for Gross Margin Percentage by Product Category over FY 2023."
Why it’s effective:
  • Identifies:
    • Versions (Actuals and Forecast)
    • Account (Gross Margin Percentage)
    • Dimension (Product Category)
    • Time (FY 2023)
  • Identifies the two versions, the account, and the dimension to be compared side-by-side
"Compare regions"
Why it’s ineffective:
  • Doesn’t clarify what regions to compare or the scope of the query.
"Compare North America and EMEA regions for 6000 Revenue for Jan 2026"
Why it’s effective:
  • Identifies:
    • Dimensions (North America and EMEA)
    • Account (6000 Revenue)
    • Time (Jan 2026)
  • Directly compares two specific dimension values (levels) for a single account and period.
"Compare revenue types"
Why it’s ineffective:
  • Doesn’t clarify what revenue type accounts to compare or the scope of the query.
"Compare Product Revenue to Services Revenue by Month for FY 2024"
Why it’s effective:
  • Identifies:
    • Account (Product Revenue, Services Revenue)
    • Time (by Month for FY 2024)
  • Enables an account-to-account comparison across a specific time series.
"Why is travel over budget?"
Why it’s ineffective:
  • Doesn’t specify the exact account name, the version name to compare against, or the scope.
"Analyze the variance for '7210 Travel' between Actuals and Working Budget for Q3 2025, broken down by Department."
Why it’s effective:
  • Identifies:
    • Account (7210 Travel)
    • Versions to compare (Actuals and Working Budget)
    • Time (Q3 2025)
    • Breakdown dimension (Department)
  • Enables a version-to-version comparison for a specific time period and broken down by a specific dimension.

Detecting Anomalies

Use the phrase "detect anomalies" to trigger the Agent’s outlier detection logic.
Ineffective Prompt
Effective Prompt
“Are there any issues with my data?”
Why it’s ineffective:
  • Too broad and lacks specificity about what constitutes an issue.
"Detect anomalies in Operating Expenses for the Marketing department by month over FY 2024."
Why it’s effective:
  • Pinpoints meaningful irregularities by focusing on:
    • Account (Operating Expenses)
    • Level (Marketing)
    • Granularity (monthly)
    • Time frame (FY 2024)
  • Uses the required "detect anomalies" phrase while pinpointing the specific account and granularity.

Breaking Down Data

Breakdowns decompose a total value into its contributing parts, such as sub-accounts or dimensions.
Ineffective Prompt
Effective Prompt
"Can you break down expenses?"
Why it’s ineffective:
  • Doesn’t specify the account details, dimensions, or time frame.
"Breakdown 6100 Payroll by Region for Jan 2026"
Why it’s effective:
  • Decomposes a specific account (Payroll) into its regional components for a single month.
"Show net income details"
Why it’s ineffective:
  • Doesn’t specify the granularity for the breakdown.
"Breakdown Net Income by leaf level"
Why it’s effective:
  • Requests a comprehensive breakdown to the most granular organizational level available in the hierarchy.

Analyzing Trends

Trend queries identify patterns of data changing over time, typically visualized as line charts.
Ineffective Prompt
Effective Prompt
"What are the trends in revenue?"
Why it’s ineffective:
  • Doesn’t indicate the desired breakdown or time period.
"Show ‘6000 Revenue’ trends by Product Line for North America over the past 3 years, broken down by Quarter."
Why it’s effective:
  • Specifies the account (6000 Revenue) in quotes, dimension (Product Line), region (North America), time period (3 years), and granularity (quarterly) for detailed trend analysis.
"Trend Revenue"
Why it’s ineffective:
  • Doesn’t specify the dimension by which to break down the revenue trend or time period.
"Trend Revenue by Customers for Q1 2026"
Why it’s effective:
  • Breaks down the revenue trend by a specific dimension (Customer) for the upcoming quarter.
"Show me sales trends."
Why it's ineffective:
  • Doesn’t specify the exact account for which to provide trending data or by which dimension. Also, scope isn't defined.
"Trend '4100 Product Revenue' by Product Category for North America over the last 12 months."
Why it’s effective:
  • Specifies the account (4100 Product Revenue) in quotes, dimension (Product Category), region (North America), time period (last 12 months) for detailed trend analysis.

Metric Calculation

Ineffective Prompt
Effective Prompt
"What is the headcount cost?"
Why it’s ineffective:
  • Doesn't specify account or time scope.
"What is the Revenue per Headcount for the Sales Department in FY 2024?"
Why it’s effective:
  • Requests a custom ratio calculation on the fly by combining two distinct accounts.
"How much is travel vs revenue?"
Why it’s ineffective:
  • Doesn't provide enough context.
"Show Travel Expense as a % of Total Revenue for Q3 2025"
Why it’s effective:
  • Calculates the relative impact of an account against a total, providing immediate context for spend efficiency.
"What is our efficiency?"
Why it’s ineffective:
  • Doesn't specify account or time scope.
"What is the ratio of Total Operating Expense to Total Revenue for FY 2024 at the Total Company level?"
Why it’s effective:
  • Requests an ad hoc calculation by combining two distinct accounts.