Matching Competitor Products

How To
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Hey all. I’m currently building a solution that uses an Airtable filled with all of the manufacturer’s products, and then the corresponding competitor products, so if a potential customer says, “I currently use x, what do you recommend?” It will find the corresponding similar product of the same size and fit in my client’s catalogue. This client has a very small catalogue, so it’s easy to do in Airtable, but how would this be doable with clients with very large product catalogues? Is this sort of competitor product matching done that often?

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Welcome to the Make community!

What’s wrong with just using the Airtable search module? (or Google Sheets, etc.)

You can try using the Airtable “Search Records” module —

Searches for specific records or returns all records.

For more information about the Search Records module and Airtable app, see the corresponding Integrations page and the Help Centre documentation.

I would suggest completing the Make Academy before jumping into building a complete scenario. If you need specific assistance when you are building a scenario it’s easier to help you then.

Here are some useful links and guides you can use to learn more on how to use the Make platform, apps, and app modules. I found these useful when I was learning Make, and hope they might benefit you too —

Getting Started

Help Centre Basics

Articles & Videos

You can also use the Hire a Pro category to request for private 1-to-1 assistance via video call/screenshare/private messaging/etc. This may help you get your issue resolved faster especially if it is urgent or contain sensitive information. It is important to post your request in the Hire a Pro category, as forum members are not allowed to advertise their services in other categories like here (even if it’s free/unpaid). Posting in the Hire a Pro category will allow other members to assist you over other forms of communication.

Hope this helps! Let me know if there are any further questions or issues. P.S.: investing some effort into the tutorials in the Make Academy will save you lots of time and frustration using Make!

— @samliew

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Nothing wrong with the Airtable at all, you have to put in all of the competitor product info, including the different ways people like to abbreviate and spell them. For a catalogue of 100, it’s not so bad, but what would be the options if someone has a catalogue of say 1000 products, and wants this type of solution? I could potentially need to do this in future for another client I’m in talks with at the moment, hence the question!

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Hi @Daniel_Thomas

I think there’s a really strong way to approach this at scale:

Instead of relying on Airtable alone, you can build a system backed by a vector store, which is purpose-built for high-speed, high-accuracy retrieval even with very large product datasets.

For example when someone asks “I use Competitor Product X, what should I buy from you?”, the system doesn’t just look for exact matches but understands what they mean and finds the closest equivalent from your catalog automatically—even with messy naming or huge data volumes.

You can also layer on a custom fine-tuned OpenAI assistant that knows your business’s tone of voice and typical customer questions.

To make it even more robust, you can set up an automated workflow with Make.com that keeps the vector store in sync. So whenever there’s a status change in your product database—like a new product being added or an existing one being updated—it triggers an automatic update of the vector embeddings. This ensures your recommendation engine is always up to date with no manual work

Best regards,
Digipanda Consulting Pvt. Ltd
@digiPanda_Automation

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That’s interesting, thanks for the detailed response! I have the OpenAI modules and email modules set up and working perfectly, and the Airtable is working fine for this particular model, but as I said, I had no way to scale it for a larger business. Thanks for the food for thought!

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You could actually replace Airtable with a vector store and connect it directly to your model to make the entire system far more powerful and scalable.

With larger client datasets, relying on Airtable or similar tools requires multiple API calls to filter and search records, which can quickly slow down your workflows and introduce latency.