time-date data

“We must use time as a tool, not as a couch.” – President John F. Kennedy

While this quote came from a speech made to the National Association of Manufacturers in 1961 and wasn’t talking about using timestamps but rather the time given, the sentiment still holds. In the case of data analysis, you can proactively use your time-date data to better understand and serve your customers.

The Seasonality You Know and the Seasonality That’s Hidden

You already know your seasonality; it exists in every industry, even healthcare. Maybe summers are slow, fall is busy, and if you’re B2C, the holiday season is your biggest time of the year. However, there are likely patterns hiding within your seasonality, and machine learning can help you uncover them. Using a feature engineering process, AI can extract specific pieces of data from the timestamp and use those distinct data points to find hidden insights into behaviors and seasonality. If there are patterns of statistical significance to the outcome, then the AI can apply them in predicting future behaviors. 

Armed with information, your marketing, sales, and customer success teams can plan their strategies accordingly to best serve your customers and drive revenue for your business. 

Feature Engineering on Time-Date Data

Squark’s advanced featuring engineering automatically takes the column with the timestamp and creates ten additional columns with the following distinct pieces of data information that the machine learning algorithms can use to find patterns and insights into customer behavior. 

Here are the additional columns created by Squark: 

  1. Day of Month
  2. Month
  3. Year
  4. Day of Week
  5. Week of Month
  6. Week of Year
  7. Quarter
  8. Hour
  9. Minute 
  10. Second

Squark’s algorithms will tell you which date-time factors both positively and negatively impact your data set, both at the summary level and at the individual row level. 

Ready to uncover the hidden date-time patterns in your data? Schedule a call with one of our experts today. 

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