Predictive Model

[Feras95p]

Dear all, 

I would like to ask you how can I build a predictive model that predict the sales of the next year with respect to the data provided of 2017,2018 and 2019. I would like also to filter out the customers who have the high probability to order again, for this I have the phones number of the customers that are ordered in 2017, 2018 and 2019. I have attached the sample excel sheet of the data that I have and according to this data I want to build the predictive model. So, any help in that please?

 Note that: The data that I want to predict the sales of it it's from C column to N column.

I delete the phones number of the customer because of the privacy.

Thanks in advance for your kind support.

[echuong1]

Take a look at the tool mastery page for the linear regression tool:

https://community.alteryx.com/t5/Alteryx-Designer-Knowledge-Base/Tool-Mastery-Linear-Regression/ta-p...

Other types of models can be found in the index: 

https://community.alteryx.com/t5/Alteryx-Designer-Knowledge-Base/Tool-Mastery-Index/ta-p/84593

[wdavis]

Hi @Feras95p 

There is also an excellent article here - https://community.alteryx.com/t5/Data-Science-Blog/Champagne-Analytics-A-Time-Series-Tutorial/ba-p/4... which documents how you can use the Time Series tools in Alteryx.

Thanks

Will

[RolandSchubert]

Hi @Feras95p ,

I think you have to build two different model:

1) Predict sales based on history: In my opinion, you should aggregate the values for columns C-N on a daily level and use one of the Time Series tools to create a predictive model (ETS, ARIMA). You'll have to build one model for each column.

2) Predict probability for customers: You have to identify the most important variables for customers to return - e.g. frequency (number of visits) and recency (last visit), period between visits.Maybe it's possible to build a regession model based on these (probability for return of customer).

What do you think?

Best,

Roland

[Feras95p]

1- The values of columns C-N are already in daily level, but I don't know how I can build the predictive model so, if you can explain for me the steps for one model and I will do for the other it will be much appreciated.

2- I have already identified how many each customers return to order again but I don't know how I can estimate the avg time that they took to return, so I want to guide me on how I can do that. 

[afv2688]

Hello @Feras95p ,

Check the ETS and ARIMA modles in the designer. There are many articles whithin the community that can help you to configure them:

https://help.alteryx.com/2018.2/ETS.htm

https://help.alteryx.com/current/ARIMA.htm

Edit:

You can also check these examples:

https://community.alteryx.com/t5/Data-Science-Blog/Expand-Your-Predictive-Palette-III-I-Sales-Foreca...

https://community.alteryx.com/t5/Data-Science-Blog/Champagne-Analytics-A-Time-Series-Tutorial/ba-p/4...

If this post helps, then please consider Accept it as the solution to help the other members find it more quickly.

Regards

[afv2688]

Hello @Feras95p ,

I edited my previous post with two examples that may give you a better insight.

Regards

[RolandSchubert]

Hi @Feras95p ,

I've added a sample workflow to calculate time between visits, number of visits, total sales volume (I would prefer the last one weighted by price as monetary value) and days since last visit. This should be a foundation to classify customers.

For the sales forecast using ARIMA and ETS, I think @afv2688 and @wdavis already pointed to helpful resources.

Best,

Roland

[Feras95p]

Hi @RolandSchubert 

Thanks a lot for your kind support, but you've chosen the XNAME which is the district name, I want to be the mobile is instead of the XNAME because from the mobile I can identify the customer not from the XNAME I tried to modify on it but I couldn't, could you please just modify that thing. Thanks again for your support.    

[RolandSchubert · Accepted solution]

Hi @Feras95p ,

I've changed the customer identifier to "mobile", if you use data containing mobile number it should work (hopefully ...). I also added the replace NULL by value 0 to solve the problem with NULL values

Best,

Roland