Quick answer. To build a media database frontend in Lovable AI, prompt it to create an internal tool where you can add, search, and filter journalist records — name, outlet, beat, email, location, and notes — with a clean list view and detail pages. Lovable generates the interface and backend; you refine it by conversation. Because it holds contact data, keep it internal and access-controlled, and do not paste in third-party contact lists you do not have the right to store.
What a media database frontend gives you over a spreadsheet
A spreadsheet stores the data. A frontend makes it usable:
Search — find a journalist by name or outlet instantly, instead of scrolling
Filters — pull every reporter on a beat, in a region, or at a tier of outlet, in one click
Clean records — each journalist as a readable profile, not a cramped row
Notes that surface — relationship history and pitching notes visible where you need them
A real interface — something the whole team can use without breaking the formatting
The data may be the same. The usability is not — and usability is what determines whether the team actually works from the database or works around it.
The prompt template
Paste this into Lovable and adjust the fields to how your team works:
> Build an internal media database tool. Let me add journalist records with these fields: name, outlet, beat or topic, email, location, tier (Tier 1 / Tier 2 / Trade), last contacted date, and notes. Show all journalists in a clean list view with a search bar that searches name and outlet. Add filters for beat, location, and tier. Each journalist has a detail page showing all their fields and notes. Let me add, edit, and delete records. Clean, fast, easy to scan. This is an internal tool.
Lovable will generate the interface and set up the backend that stores the records.
Refine it by conversation
Once the first version exists, shape it:
"Add a column to the list view showing the last contacted date."
"Let me sort the list by outlet and by last contacted date."
"Add a filter for journalists not contacted in the last 90 days."
"Add a field for the journalist's recent articles or links."
"Make the detail page show notes more prominently."
Each instruction updates the tool. Build it to fit how your team actually pitches.
Useful extensions
Once the core database works, these additions earn their place:
Pitch tracking — log which journalists were pitched on which campaign, and the outcome
Tags — group journalists into ad hoc lists for a specific campaign without restructuring the database
A "needs follow-up" view — surface relationships going cold
Import — a way to bring in records from your existing spreadsheet (clean the data first)
The privacy line — important
A media database holds personal contact information, so treat it accordingly:
Keep it internal and access-controlled. This is not a public-facing tool. Restrict it to the team that needs it.
Only store contacts you have a legitimate basis to store. Do not paste in purchased lists or third-party databases you do not have the right to hold.
Get a security review. Any tool holding contact data should be reviewed before the team relies on it, and respect applicable data-protection rules.
Keep it accurate. Journalists move outlets and beats constantly. A media database is only useful if it is maintained.
The tool makes the database usable. It does not make you exempt from handling personal data responsibly.
The takeaway
A media database frontend turns the spreadsheet every PR team tolerates into the working system every PR team needs — searchable, filterable, usable. Built in Lovable, it takes an afternoon and no developer. Keep it internal, keep it accurate, handle the contact data responsibly — and the team will finally work from the database instead of around it.
Continue:
