Auto Insights can help finance teams monitor and analyze revenue performance, maximize profitability and uncover new opportunities. You can read more here on our website.

This article will cover:

  • Example insights from this use case

  • Recommended data structure for this use case

What sort of insights can Auto Insights help me uncover?

We've outlined some example questions which Auto Insights can help answer through a combination of its proactive insights, Search, and What caused this? analysis:

Analyze revenue, team & product performance

  • Revenue by product category

  • Monthly percentage growth of profit by sales office

  • Worst performing sales offices for Q1 FY20

  • Highest revenue by account manager last month

Maximize profitability

  • Best performing products for FY19

  • Worst performing products for Q1 FY20

  • Profit by country and product

  • Worst performing channel

  • Quarter on quarter profit compared to the previous comparable period for Q1 FY20

Uncover new opportunities

  • Growth by channel last quarter?

  • Best performing product category month on month?

  • Profit by channel and product category

  • Percentage growth for revenue by product name last financial year

How do I structure my data?

  • Auto Insights requires structured, transactional data, with at least 1 measure (e.g. profit) and 5 segments (e.g. product names). In addition, we recommend at least 7 months of data (at monthly or daily granularity) so you can take full advantage of Auto Insights' Unexpected Changes feature.

  • Auto Insights can connect to databases and .csv files. For this type of use case, we recommend a direct database connection.

Example data structure

Please click on the picture to download a larger copy of the image.

Refer to this article for more information about data structure.

Segments

Here are some of the typical segments we find in revenue data. A segment is a qualitative value, like names or categories:

  • Customer attributes: Customer name, salesperson name, customer size, etc.

  • Product attributes: Product category, product sub-category, product type, product name, etc. 

  • Other attributes: Channel, sales office location (in natural language, e.g. Sydney, Melbourne, etc.)

Measures

A measure is a quantitative, numeric value. Some of the typical measures include profit, revenue, margin, quantity sold, etc.

Related material
What type of data can be used in Auto Insights?
Options for ingesting data into Auto Insights
Quick guide to Auto Insights

If you have any questions, please contact us at support@hyperanna.com. 

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