Build a Auto ML Experiment

Chanty4u — Wed, 18 Mar 2026 16:18:52 GMT

Hi All,

i have one dataset attached to build a AutoML experiment its historical data and i dont have target column we need to derive

below is the ask : based on order pattern we need to predict .

" use historical order patterns to predict what a customer is most likely to buy next (Cross-sell/Up-sell)."

can someone guide me the steps and ideas ?

Re: Build a Auto ML Experiment

igoralcantara — Mon, 23 Mar 2026 18:30:50 GMT

Hey my fellow MVP,

This is a classic recommendation problem, or a Market Basket. Since you do not have a target column yet, the solution is in how you prepare the data. You will need to work more on the data preparation to create a target column. If I can summarize in steps, I would say this:

1. Create your Target

You need to define a target by using your historical data. Split your data into two time periods. Use the first period (the past) to build your customer features, and use the second period (the future) to identify what they actually purchased. That future purchase becomes your Target Column.

Qlik Predict needs a specific outcome to learn from. You should transform your data so each row is a unique customer. Use a "Point-in-Time" split:

The Past: Aggregate their activity (total spend, frequency, last category) up to a specific date.
The Future: Look at what they actually bought after that date. This becomes your Target Column (e.g., "Next_Product_Category").

2. Engineering Features in Qlik

To give the model the best chance, calculate these attributes for each customer in your script:

Recency: Number of days since their last transaction.
Frequency: Total number of distinct orders.
Monetary: Average or total spend.
Last Purchase: The specific category or item from their most recent order.

3. Running the Experiment

Once your table is ready with the features and the Target Column, load it into Qlik Predict. Select your "Next Purchase" column as the target.

If the data is very simple, you can also use Market Basket Analysis (Association Rules) directly in Qlik using set analysis to identify items that are frequently bought together.

Count({<OrderID = P({<ProductName = {'$(vAnchorProduct)'}>} OrderID)>} Distinct OrderID)

topic Re: Build a Auto ML Experiment in Qlik Predict

Build a Auto ML Experiment

Re: Build a Auto ML Experiment