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Intelligent Data Insight

Intelligent Data Insight

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Best Practices for Dashboard
Best Practices for Intelligent Dashboard Interpretation and Intelligent Paragraph Formatting
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Best Practices for Intelligent Dashboard Interpretation and Intelligent Paragraph Formatting

Title module

Instruction example

Title

It is recommended to configure the title format directly within the paragraph, rather than using instructions.

Follow-up person

Generally used in combination with the subscription feature, push to the Lark group and @ someone

Display @follow-up person
Follow-up person email: someone1@bytedance.com、someone2@bytedance.com、someone3@bytedance.com
@Please output in the following format and separate entries with "、"

Hyperlink

Display link name
xxxx is: https://open.larkoffice.com/cardkit/editor?cardId=AAqxJkJYSFtoY
Output format: link name

Date

The latest date in the @date field of a chart, output in the following format:
Date format: YYYY/MM/DD
Weekday format: Chinese weekday (such as 周一, 周二)
Example: 2025/08/18 周一

Extract the month value from the @date field of a chart, display only the month without the year
For example: July, displayed in bold font

Data processing module

Instruction example

Redefine data range

Time range filtering

Filter the most recent 7 days of data in the @date field of a chart
Filter condition: business date > latest available date - 7 days (including the start date, ensuring a complete 7-day data set)
Output format: YYYY/MM/DD - YYYY/MM/DD (X days in total)
Example: 2024/08/21 - 2024/08/27 (7 days in total)

Other field filtering

Filter the data of the "Food & Beverage" industry in the @a dimension field of a chart for analysis.
Filter condition: Merchant primary industry = "Food & Beverage"
Output format: filter value, bold in blue
Example: Food & Beverage

Field mapping

Filter out the top 10 cities with the largest absolute value of month-over-month change from @detailed data, and format the results as required
Data processing steps:

  1. Calculate the absolute value of month-over-month change for each city (
  2. Sort by the absolute value of month-over-month change in descending order, and select the top 10 cities
  3. Match the person in charge of the region to which the city belongs: Central region → Wang Zhong, Southern region → Li Nan, Northern region → Zhao Bei, NKA → Zhang Hu
  4. Numeric formatting rules:
    • Previous value/current value: When the value is too large, convert sequentially to the units of "ten thousand", "million", or "ten million" (integer part > 0), keeping two decimal places.
    • Change rate: (current value - previous value) / previous value × 100, keep one decimal place, with a plus or minus sign.
  5. Style rules:
    • When the city name/change rate is positive: green text
    • When the city name/change rate is negative: red text

Output format requirements: City name @Person in charge (previous value→current value, change rate%)
Example:
Increase example (green): Shanghai @Zhang San (100,000.00→200,000.00, +100.0%)
Decrease example (red): Beijing @Li Si (200,000.00→100,000.00, -50.0%)

Secondary data analysis

Derived indicator calculation

@A certain field of a chart Calculate the growth rate indicators for each dimension.
Calculation formula: Growth rate = (current value - base period value) / base period value × 100%
Time comparison: day-on-day, week-on-week, month-on-month
Output format: current value (growth rate%)
Growth rate >10% green +📈, 0-10% orange +📊, <0% red +📉
Example: 12,340,000.00 (+15.6%📈)

Sensitive data processing

@A certain chart Perform sensitive data desensitization processing.
Desensitization rules: For merchant names, keep the first two characters +; for mobile numbers, keep the first three and last four digits.
Example: Zhang San
, 138****5678

Dimension breakdown

User dimension

@A certain field of a chart Analyze by user type dimension.
Breakdown dimension: static merchant segmentation (fill in the dimension name)
Output format: Dimension name: redeemed GMV value (proportion%)
Proportion >40% green +👑, 20-40% blue +⭐, <20% gray +📊
When the GMV value is too large, it can be converted sequentially to the units of "ten thousand", "million", or "ten million"; when converting, the integer part must be >0, and two decimal places must be kept. Proportion keeps one decimal place.
Example: Small and medium merchants: 2,456,000.00 (45.2%👑) National key clients: 1,568,000.00 (28.9%⭐)

Time dimension

@A certain field of a chart Compare performance across different time periods.
Comparison dimension: weekdays vs weekends
Calculation indicator: average value
Output format: Weekday redeemed GMV average vs weekend redeemed GMV average (difference%)
When the GMV value is too large, it can be converted sequentially to the units of "ten thousand", "million", or "ten million"; when converting, the integer part must be >0, and two decimal places must be kept.
Significant difference (>20%) is marked with ⚡
Example: 605,700.00 vs 622,700.00 (-2.73%)

Channel dimension

@some chart filters the top three provinces by month-over-month growth in verified GMV.
Output format: Province name (yesterday's value -> today's value, +xx%),

  1. Rules for unit conversion: When yesterday's value or today's value is too large, convert units sequentially to "ten thousand", "million", or "ten million". After conversion, the integer part must be greater than 0, and retain two decimal places.
  2. Rules for calculating growth rate: Retain one decimal place.
  3. Rules for color coding: When the rate of change is positive, display the province name and rate of change in green; when negative, display in red.
    Example: Guangxi (614.72 -> 1.37 ten thousand, 2121.8%), Anhui (5,237.15 -> 4.01 ten thousand, 665.2%), Gansu (8,592.01 -> 5.05 ten thousand, 488.1%)

Frontend display adjustment

Instruction example

Conditional formatting

Color DIY

@verified GMV value: original value (convert the original value unit to ten thousand, display the unit, round to integer with thousands separator, display in green and bold if greater than 0, display in red and bold if less than 0);
Display the month-over-month value of @verified GMV in parentheses; difference percentage is shown as a percentage, retain one decimal place, green if greater than 0, red if less than 0; output retains the sign, do not show ###
All need to be bolded
Format example: 10,000.21 ten thousand (-3.2%)

emoji

@verification rate use the original verification rate value, no need to display the title, only show the result value, percentage, round up, retain zero decimal places;
If the verification rate exceeds 85%, display the verification rate in green and bold, with a note in parentheses indicating overachievement 🎉;
If the verification rate is between 75% and 85%, display the verification rate in orange and bold, with a note in parentheses indicating keep pushing 💪;
If the verification rate is below 75%, display the verification rate in red and bold, with a note in parentheses indicating a sprint is needed 🏃;
Example: 76% (💪)

Data format

Dynamically adjust units

@verified GMV industry distribution Top 3 secondary industries by month-over-month growth in verification.
Display: Secondary industry name (yesterday's value -> today's value, +xx%). If yesterday's value or today's value is too large, they can be converted sequentially to "ten thousand", "million", or "ten million" units. When converting, the integer part must be greater than 0, and retain two decimal places. Growth rate retains one decimal place.
Industry name and rate of change are displayed in green text
Example: Scenic area tour (7.34 ten thousand -> 9.14 ten thousand, 24.5%)

Last updated: 2026.06.11 17:29:03