id: 1,
name: "my group",
filters: [
  {field: "sessions", type: "greater_than", value: 5},
  {field: "email", type: "contains", value: "@example.com}
]

id: 1, email: "example@gmail.com", sessions: 5, more_meta_data..

id: 1, matching_groups: ["my group"], email: "example@gmail.com", sessions: 5  more_meta_data..

create table groups (id int, name text, filters text[]);
insert into groups values
(1, 'group1', array['sessions > 0', 'email like ''example%''']),
(2, 'group2', array['sessions > 5', 'email like ''example%''']),
(3, 'group3', array['sessions = 5', 'email like ''%gmail.com''']);

create table visitors (id int, email text, sessions int);
insert into visitors values
(1, 'example@gmail.com', 5),
(2, 'example@abc.com', 10),
(3, 'me@gmail.com', 5),
(4, 'xxx@yyy.com', 5);

create or replace function the_filter(filters text[], id int)
returns boolean language plpgsql as $$
declare
    r boolean;
begin
    execute format(
        'select %s from visitors where id = %s',
        array_to_string(filters, ' and '),
        id)
    into r;
    return r;
end $$;

select v.*, array_agg(g.name) groups
from visitors v
left join groups g on the_filter(g.filters, v.id)
group by 1, 2, 3;

 id |       email       | sessions |     groups
----+-------------------+----------+-----------------
  1 | example@gmail.com |        5 | {group1,group3}
  2 | example@abc.com   |       10 | {group1,group2}
  3 | me@gmail.com      |        5 | {group3}
  4 | xxx@yyy.com       |        5 | {NULL}
(4 rows)