One thing that I make use of but don't see too many services providing is some kind of 'match level' - where the geocoder returns a code indicating how confident it is about the quality of it's result. A result of 1 might mean a building level match, while 100 might be street level etc.
IIRC Google's geocoder does something like this, but it's pretty inaccurate, overstating it's match level consistently.
As others have said, geocoding is very hard to do well, but I commend the efforts being made with Nominatim and komoot/photon.
FWIW I ran millions of addresses through PostGIS geocoders (using both TIGER as well as PAGC's normalizer functions) and found that MOST addresses geocoded with confidence level 0 or 1. 60% were 0 or 1, the other 40% were spread across ratings 2 - 100.
I don't have a great way to characterize the geographic coverage or data quality of the geocoder, but it is clear that it has a data set which must be maintained to support geocoding into the future. Soon I'll have to start figuring out how long my current data is useful, and how long it will be before the next update from the census bureau.
I'm starting to think that it's crazy for so many businesses to need reliable GIS data and have so few sources to go for it. With the right organizational structure, we could be croudsourcing it it daily.
IIRC Google's geocoder does something like this, but it's pretty inaccurate, overstating it's match level consistently.
As others have said, geocoding is very hard to do well, but I commend the efforts being made with Nominatim and komoot/photon.