Listings in agents' networks & Predicted (starred) contacts who listed

listings_proof.rb

# 1. given a brokerage (or all users), how many listings did each agent have?
# 2. from those listings, how many did First "predict"?
    # 3 star over the last 12 months = predicted

def show_listings_proof(brokerage_name=nil, since_date=Time.now.beginning_of_year)
    show_listings_counts_per_agent_for_brokerage(brokerage_name, since_date)
end

def show_listings_counts_per_agent_for_brokerage(brokerage_name, since_date)
    if brokerage_name.nil?
        users = User.not_admin.live_customers
        brokerage_name = "All Users"
    else
        users = User.where(brokerage: brokerage_name)
    end
    puts "name,listings_count_for_user,three_star_count,two_star_count,one_star_count,three_star_hit_rate_user,two_star_hit_rate_user,one_star_hit_rate_user"
    brokerage_summary = {
        one_star: 0,
        two_star: 0,
        three_star: 0,
        total_listings: 0,
    }
    users.each do |u|
        user_summary = {
            one_star: 0,
            two_star: 0,
            three_star: 0,
            total_listings: 0,
        }
        listings_found_in_network = 
            u.contacts
                .of_interest
                .joins(preferred_person_match: {property: {address: :pre_mover_records}})
                .where("date(pre_mover_records.created_at) > ?", since_date)
        num_listings_found_in_network = listings_found_in_network.select("people.id").distinct.count

        listings_found_in_network_by_person =
            listings_found_in_network
                .group("people.id")
                .select("people.id as contact_id, min(pre_mover_records.pub_date) first_premover_record_pub_date")

        user_summary[:total_listings] = num_listings_found_in_network 
        brokerage_summary[:total_listings] += num_listings_found_in_network
        listings_found_in_network_by_person.each do |c|
            star_rating = show_star_rating_for_contact_listing(c)
            if star_rating == 1
                user_summary[:one_star] += 1
                brokerage_summary[:one_star] += 1
            elsif star_rating == 2
                user_summary[:two_star] += 1
                brokerage_summary[:two_star] += 1
            elsif star_rating == 3
                contact = Person.find(c.contact_id)
                user_summary[:three_star] += 1
                brokerage_summary[:three_star] += 1
            end
        end
        listings_count_for_user = user_summary[:total_listings]
        three_star_count = user_summary[:three_star]
        two_star_count = user_summary[:two_star]
        one_star_count = user_summary[:one_star]
        three_star_hit_rate_user = (1.0 * three_star_count / listings_count_for_user).round(4)
        two_star_hit_rate_user = (1.0 * two_star_count / listings_count_for_user).round(4)
        one_star_hit_rate_user = (1.0 * one_star_count / listings_count_for_user).round(4)
        if listings_count_for_user == 0
            three_star_hit_rate_user = 0
            two_star_hit_rate_user = 0
            one_star_hit_rate_user = 0
        end
        puts "#{u.full_name},#{listings_count_for_user},#{three_star_count},#{two_star_count},#{one_star_count},#{three_star_hit_rate_user},#{two_star_hit_rate_user},#{one_star_hit_rate_user}"
    end
    listings_count_for_brokerage = brokerage_summary[:total_listings]
    three_star_count = brokerage_summary[:three_star]
    two_star_count = brokerage_summary[:two_star]
    one_star_count = brokerage_summary[:one_star]
    three_star_hit_rate_brokerage = (1.0 * three_star_count / listings_count_for_brokerage).round(4)
    two_star_hit_rate_brokerage = (1.0 * two_star_count / listings_count_for_brokerage).round(4)
    one_star_hit_rate_brokerage = (1.0 * one_star_count / listings_count_for_brokerage).round(4)
    if listings_count_for_brokerage == 0
        three_star_hit_rate_brokerage = 0
        two_star_hit_rate_brokerage = 0
        one_star_hit_rate_brokerage = 0
    end
    puts "#{brokerage_name},#{listings_count_for_brokerage},#{three_star_count},#{two_star_count},#{one_star_count},#{three_star_hit_rate_brokerage},#{two_star_hit_rate_brokerage},#{one_star_hit_rate_brokerage}"

    return nil
end

def get_stars(percentile)
    return unless percentile.present?
    if percentile >= 90
        return 3
    elsif percentile < 90 && percentile >= 85
        return 2
    elsif percentile < 85 && percentile >= 77
        return 1
    else
        return 0
    end
end

def show_star_rating_for_contact_listing(contact_listing)
    contact_id = contact_listing.contact_id
    date_end = contact_listing.first_premover_record_pub_date # - 2.months
    date_start = contact_listing.first_premover_record_pub_date - 1.year
    results = Person
        .where(id: contact_id)
        .joins(preferred_person_match: [property: {address: [address_seller_scores: :predictive_model]}])
        .where("predictive_models.created_at > ?", date_start)
        .where("predictive_models.created_at <= ?", date_end)
        .group("people.id")
        .select("people.id AS id, MAX(address_seller_scores.percentile) AS max_percentile")
    
    return unless results.present? 
    return get_stars(results.first.max_percentile)
end

# This shows listings info for ALL USERS
show_listings_proof(nil)

show_listings_proof('@properties')
show_listings_proof('Ansley')
show_listings_proof('Beverly-Hanks')
show_listings_proof('C21 Advantage Gold')
show_listings_proof('C21 Results')
show_listings_proof('Climb')
show_listings_proof('Dwellings')
show_listings_proof('Hometown Advisor')
show_listings_proof('KY Select')
show_listings_proof('Moving The Mitten')
show_listings_proof('One South')
show_listings_proof('Savvy + Co.')
show_listings_proof('Warburg')
show_listings_proof('West + Main')