The problem with just exposing '?productName=cupcakes' is you're assuming just one filter with simple equality. If you need to expose something even just a little more complex, i.e. "A=1 or B=2", or something other than equality like "A>1" or "B!=2", then you quickly find yourself re-implementing a little expression language, syntax for literals, etc. It is a slippery slope, which one can happily go down and succeed with a custom solution - until you then want someone other than your clients to pull data from. Then they need to build their filter in your language, which is of course different than the next guy's language, and so on and so on.
The fix for this is OData. Not all of OData - just a little bit. It lets one standardize the filter expression syntax (as much of it as you choose to support) without making any requirements on the backend.
I'm personally confident in making the claim that OData $filter doesn't require you to bind to a server implementation, because I work on a service built in Node.js and deployed on Linux in Azure that uses OData as a filter syntax and satisfies it's data requirements from three completely different backend servers, none of which is a SQL Server (not that you mentioned SQL, but it's often cited as "all that OData is good for"). One of them is Elastic Search, BTW :), the other is a proprietary aggregated metrics store, and the third is a cloud-scale columnar data store. All three of these can be queried with the same syntax, from tons of off-the-shelf OData consumers, and for clients the choice of what backend to pull data from is literally the only thing they change. From a business value perspective this is pure win, and this is due in large part to using just a little OData, at just the right spots.
I think of OData like salt in a recipe - a little bit is great; too much ruins the dish. Moderation in all things... :)