Fuzzy Matching Tool provides incorrect results while comparing two datasets

[AviratG]

I have a 2 datasets, 
Dataset 1 :Azure Maps dataset (containing grocery chains in the area)
Dataset 2: Top grocery stores in US.
I'm looking to Fuzzy Match the 2 datasets, since we have multiple entries (example: ShopRite of Norwalk, ShopRite of Derby, Super Stop & Shop, Stop & Shop Pharmacy) from Azure Maps so that I can get only "ShopRite" or "Stop & Shop" as the answer.

I have done the steps outlined by the documentation
1. Creating a source field

2. Adding a unique record ID

3. Union both datasets so we have the POI Name in the same column

4. Try different fuzzy matching options to get the correct config.

Issue: Rather than comparing to the new dataset, Alteryx somehow is comparing to the old dataset and finding different variations mentioned. In the screenshot attached you can see: Whole Foods is from Dataset 2, while Alteryx suggests Whole Foods Market from Dataset1, but OLA foods is from Dataset 1 while Alteryx suggests Whole Foods from Dataset 2.

I have attached the workflow and screenshot here: 

[KilianL]

 Hi @AviratG,

while I am not sure what went wrong in your workflow, it is best practice to select the record ID as the 'record ID field' in the tool settings.

There is also a way to keep the original structure and values after the fuzzy match, which might give you a better overview of the fuzzy matches. Take a look at my workflow example and see if it helps.

Let me know if this doesn't work, and if it does, please mark this as the solution to help others find solutions quicker.

Kind Regards,
Kilian
Solutions Engineer - Alteryx

[AviratG]

Hi Kilian,
I have changed the matching and used Record ID since that's the recommended best practice. Used the process shown above to group records too. However, it still doesn't seem to resolve any issues from earlier. Shop Rite of Danbury or Super stop & shop don't even show up on the matching list. 

Attached workflow after the changes.