Challenges with Location Data for Effective Email Scheduling

Reply.io requires city, state, country (all 3 required) for automatic timezone detection so that emails etc. are sending at appropriate times for each prospect. Clay is great but why is it so painful to make sure these 3 columns are filled in for each row? Clay returns [city, state, country] in one cell so it takes so much time splitting them - the mapbox normalise location enrichment returns more blank columns than filled in, AI prompts are great but can't generate 3 columns from one query so i need to run an enrichment for every row x3, and then splitting columns with a formula works well for some but stumbles when the location scraped by Clay is just one word or city. am i missing something here, why is it so tedious?