Configuration

Step 1: Customize matrix

First, customize the matrix. To do this, select Matrix in the workbench navigation. 

For each answer option in the matrix, check whether offsetting should take place with a specific product. Go through the matrix for each answer option and decide which value is used to calculate each individual product (see columns in the matrix).

In our application example, we first need to determine the number of sports seats and sports tires for a recommendation unit. In our example, a recommendation unit is a car. As you can see from the matrix, we need 2x sports seats and 4x sports tires for a recommendation unit with the vehicle equipment "Sport". In the row with the answer "Sport", a "2" is therefore entered in the column for the sport tires and a "4" in the column for the sport seats (see Fig. 1, red boxes). 

Step 2: Select recommendation method

Once the matrix has been filled in, switch to Algorithm. Here you first select the itemListRecommendation as the recommendation method.

Step 3: Fill in the table in the algorithm

Then fill in the table. A table row is created for each question relevant to the calculation.  

At Parameter , first select the answer option that you have stored as a "Number Input Field" in your questionnaire and that influences the calculation of the end product.

Then specify the operator.

Now select the relevant question in the column Questions whose values are to be offset against the parameter in the matrix. Please note that the selection options in this column can be found in the "Page Title (Topic)" in the questionnaire . The input Answer is relevant if a question is used more frequently for a calculation but relates to a different parameter or is to be offset against a different operator . For example, answer A should be multiplied by the parameter X and answer B should be added to the same parameter. Now we have to differentiate between the two calculations by selecting the corresponding Answer in this case.

Applied to our example, the completed table for a recommendation unit with the Sport vehicle configuration looks as follows:

In this example, the parameter is the user input in the "Number Input Field". Here, users specify how many recommendation units (here: number of sports vehicles) they require. Since the relationship between the equipment of the recommendation unit and the recommendation unit itself must always remain the same, we select multiplication as the operator for each question. In the column Question , we now specify the question from which the answers to the user's input are calculated.

In the following example, you can see in more detail how offsetting is ultimately carried out in this example:

Example: Item list logic

In the following example, sports equipment is selected for a vehicle:

Step 1: In the navigation bar, select the menu item Matrix .

Step 2: Now enter the appropriate values in the matrix . Example: 2x sports seats and 4x sports tires are required per vehicle with sports equipment. This information can be found in the matrix (see Fig. 1: red boxes).

Step 3: To enable the calculation in the next step, you must specify in the algorithm that the number of sports vehicles entered is to be offset against the respective car item. To do this, go to the menu item Algorithm.

Step 4: Select the itemListRecommendation as the recommendation logic.

Step 5: The table in the algorithm is then filled in with the appropriate parameters, operators, questions and answers. You can see what the table looks like in the example of the sports vehicle in Fig. 3 remove.

Assumption: A user of the vehicle selector has provided the following information in the questionnaire:

Step 6: The input from the questionnaire is now offset against the information from the matrix .

The type of calculation was previously defined in the algorithm (see above Fig. 2).

For a better understanding, we will look at the aggregation of the vehicle equipment together:

🧮 The calculation follows from this:

2 sports vehicles x 4 sports tires = 8 sports tires

The body, engine and other vehicle equipment are then calculated in the same way.

The results page for this user now looks like this: