Datasets:

beamstation
/

all-restaurants-in-greeley-colorado-us-109907

beam_id string	title string	category_main_group string	category_sub_group string	category string	categories string	address string	street string	city string	state string	borough float64	neighborhood float64	postal_code int64	country string	address_verified bool	latitude float64	longitude float64	timezone string	phone string	price_level int64	census_place float64	verified_census_city bool	beam_location_name string	beam_state_code string	beam_country_code string	website_protocol string	website string	website_normalized string	website_domain string	website_domain_tld string	website_domain_age int64	website_domain_registered string	website_domain_expires string	website_domain_registrar string	emails_list string	emails_list_website_domain string	emails_count int64	emails_deliverable_count int64	description string	rating float64	reviews_total_count int64	reviews_per_rating string	service_options string	highlights string	popular_for string	accessibility string	offerings string	dining_options string	amenities string	atmosphere string	crowd string	planning string	payments string	children string	has_website bool	has_email string	has_social bool	has_phone bool	socials_count int64	social_profile_instagram string	social_username_instagram string	social_profile_facebook string	social_username_facebook string	social_profile_twitter string	social_username_twitter string	social_profile_tiktok string	social_username_tiktok string	social_profile_linkedin string	social_username_linkedin string	social_profile_youtube string	social_username_youtube string	social_profile_github float64	social_username_github float64	social_profile_snapchat float64	social_username_snapchat float64	social_profile_pinterest string	social_username_pinterest string	instagram_followers float64	instagram_engagement_rate float64	instagram_engagement_rate_1m float64	instagram_engagement_rate_3m float64	instagram_engagement_rate_6m float64	instagram_engagement_rate_12m float64	instagram_post_count float64	first_social_post_days_min float64	first_social_post_days_max float64	last_social_post_days_min float64	last_social_post_days_max float64	tiktok_followers float64	tiktok_video_count float64	tiktok_heart_count float64	tiktok_engagement_rate float64	tiktok_engagement_rate_1m float64	tiktok_engagement_rate_3m float64	tiktok_engagement_rate_6m float64	tiktok_engagement_rate_12m float64	menu_link string	order_links string	reservation_link string	last_updated_at string	beam_cross_social_market_penetration float64	beam_cross_velocity_quality float64	beam_cross_social_urgency float64	beam_cross_per_capita_engagement float64	beam_cross_market_saturation_lead float64	beam_cross_population_adjusted_rank float64	beam_cross_demand_gap_index float64	beam_rating_score float64	beam_review_confidence float64	beam_rating_health float64	sentiment_avg float64	sentiment_avg_30d float64	sentiment_avg_90d float64	sentiment_avg_180d float64	sentiment_avg_360d float64	sentiment_percentile_1km float64	sentiment_percentile_5km float64	sentiment_percentile_10km float64	sentiment_score_90d float64	sentiment_score_360d float64	sentiment_positive_pct_30d float64	sentiment_negative_pct_30d float64	sentiment_neutral_pct_30d float64	sentiment_positive_pct_90d float64	sentiment_negative_pct_90d float64	sentiment_neutral_pct_90d float64	sentiment_positive_pct_180d float64	sentiment_negative_pct_180d float64	sentiment_neutral_pct_180d float64	sentiment_positive_pct_360d float64	sentiment_negative_pct_360d float64	sentiment_neutral_pct_360d float64	sentiment_trend_30vs90d string	sentiment_trend_90vs360d string	sentiment_diff_30vs90d float64	sentiment_change_360d float64	sentiment_diff_90vs360d float64	sentiment_change_pct_360d float64	reviews_count_30d int64	reviews_count_90d int64	reviews_count_180d int64	reviews_count_360d int64	beam_score_overall float64	beam_popularity_percentile float64	beam_social_presence int64	beam_data_completeness int64	beam_price_value float64	beam_data_freshness float64	beam_rank_city_category int64	beam_rank_city_overall int64	beam_rank_city_reviews int64	beam_rank_state_category int64	beam_rank_state_overall int64	beam_rank_state_reviews int64	beam_rank_country_category int64	beam_rank_country_overall int64	beam_rank_country_reviews int64	beam_rank_place_global_category int64	beam_rank_category int64	beam_rank_competition_1km_category int64	beam_rank_competition_1km_total int64	beam_rank_competition_1km_reviews int64	beam_rank_competition_5km_category int64	beam_rank_competition_5km_total int64	beam_rank_competition_5km_reviews int64	beam_rank_competition_10km_category int64	beam_rank_competition_10km_total int64	beam_rank_competition_10km_reviews int64	beam_export_rank int64	total_city_category int64	total_city int64	total_state_category int64	total_state int64	total_country_category int64	total_country int64	total_category_global int64	beam_competitors_10km_competitive_strength float64	beam_competitors_10km_competitor_avg_sentiment_30d float64	beam_competitors_10km_competitor_avg_sentiment_90d float64	beam_competitors_10km_sentiment_diff_30d float64	beam_competitors_10km_sentiment_diff_90d float64	beam_competitors_1km_competitive_strength float64	beam_competitors_1km_competitor_avg_sentiment_30d float64	beam_competitors_1km_competitor_avg_sentiment_90d float64	beam_competitors_1km_sentiment_diff_30d float64	beam_competitors_1km_sentiment_diff_90d float64	beam_competitors_5km_competitive_strength float64	beam_competitors_5km_competitor_avg_sentiment_30d float64	beam_competitors_5km_competitor_avg_sentiment_90d float64	beam_competitors_5km_sentiment_diff_30d float64	beam_competitors_5km_sentiment_diff_90d float64	beam_competitors_10km_competitor_count int64	beam_competitors_1km_competitor_count int64	beam_competitors_5km_competitor_count int64	beam_competitors_1km_rank_by_score int64	beam_competitors_1km_rank_by_rating int64	beam_competitors_1km_rank_by_reviews int64	beam_competitors_1km_score_percentile float64	beam_competitors_1km_rating_percentile float64	beam_competitors_1km_reviews_percentile float64	beam_competitors_1km_health_percentile float64	beam_competitors_1km_sentiment_percentile float64	beam_competitors_1km_competitor_avg_score float64	beam_competitors_1km_competitor_avg_rating float64	beam_competitors_1km_competitor_avg_reviews int64	beam_competitors_1km_competitor_avg_health float64	beam_competitors_1km_competitor_avg_sentiment float64	beam_competitors_1km_score_diff float64	beam_competitors_1km_rating_diff float64	beam_competitors_1km_reviews_diff int64	beam_competitors_1km_health_diff float64	beam_competitors_1km_sentiment_diff float64	beam_competitors_5km_rank_by_score int64	beam_competitors_5km_rank_by_rating int64	beam_competitors_5km_rank_by_reviews int64	beam_competitors_5km_score_percentile float64	beam_competitors_5km_rating_percentile float64	beam_competitors_5km_reviews_percentile float64	beam_competitors_5km_health_percentile float64	beam_competitors_5km_sentiment_percentile float64	beam_competitors_5km_competitor_avg_score float64	beam_competitors_5km_competitor_avg_rating float64	beam_competitors_5km_competitor_avg_reviews int64	beam_competitors_5km_competitor_avg_health float64	beam_competitors_5km_competitor_avg_sentiment float64	beam_competitors_5km_score_diff float64	beam_competitors_5km_rating_diff float64	beam_competitors_5km_reviews_diff int64	beam_competitors_5km_health_diff float64	beam_competitors_5km_sentiment_diff float64	beam_competitors_10km_rank_by_score int64	beam_competitors_10km_rank_by_rating int64	beam_competitors_10km_rank_by_reviews int64	beam_competitors_10km_score_percentile float64	beam_competitors_1km_competitive_tier string	beam_competitors_10km_rating_percentile float64	beam_competitors_10km_reviews_percentile float64	beam_competitors_10km_health_percentile float64	beam_competitors_10km_sentiment_percentile float64	beam_competitors_5km_competitive_tier string	beam_competitors_10km_competitor_avg_score float64	beam_competitors_10km_competitor_avg_rating float64	beam_competitors_10km_competitor_avg_reviews int64	beam_competitors_10km_competitor_avg_health float64	beam_competitors_10km_competitive_tier string	beam_competitors_10km_competitor_avg_sentiment float64	beam_competitors_10km_score_diff float64	beam_competitors_10km_rating_diff float64	beam_competitors_10km_reviews_diff int64	beam_competitors_10km_health_diff float64	beam_competitors_10km_sentiment_diff float64	beam_competitors_1km_total_in_radius int64	beam_competitors_5km_total_in_radius int64	beam_competitors_10km_total_in_radius int64	beam_competitors_1km_avg_distance_m int64	beam_competitors_1km_closest_competitor_m int64	beam_competitors_1km_market_type string	beam_competitors_1km_review_share float64	beam_competitors_1km_density_per_sqkm float64	beam_competitors_1km_tier_below_40 float64	beam_competitors_1km_tier_40_59 float64	beam_competitors_1km_tier_60_79 float64	beam_competitors_1km_tier_80_100 float64	beam_competitors_5km_avg_distance_m int64	beam_competitors_5km_closest_competitor_m int64	beam_competitors_5km_market_type string	beam_competitors_5km_review_share float64	beam_competitors_5km_density_per_sqkm float64	beam_competitors_5km_tier_below_40 float64	beam_competitors_5km_tier_40_59 float64	beam_competitors_5km_tier_60_79 float64	beam_competitors_5km_tier_80_100 float64	beam_competitors_10km_avg_distance_m int64	beam_competitors_10km_closest_competitor_m int64	beam_competitors_10km_market_type string	beam_competitors_10km_review_share float64	beam_competitors_10km_density_per_sqkm float64	beam_competitors_10km_tier_below_40 float64	beam_competitors_10km_tier_40_59 float64	beam_competitors_10km_tier_60_79 float64	beam_competitors_10km_tier_80_100 float64	beam_competitors_city_competitor_avg_sentiment_30d float64	beam_competitors_city_competitor_avg_sentiment_90d float64	beam_competitors_city_sentiment_diff_30d float64	beam_competitors_city_sentiment_diff_90d float64	beam_competitors_city_competitor_count int64	beam_competitors_city_total_in_city int64	beam_competitors_city_rank_by_score int64	beam_competitors_city_rank_by_rating int64	beam_competitors_city_rank_by_reviews int64	beam_competitors_city_score_percentile float64	beam_competitors_city_rating_percentile float64	beam_competitors_city_reviews_percentile float64	beam_competitors_city_health_percentile float64	beam_competitors_city_sentiment_percentile float64	beam_competitors_city_competitor_avg_score float64	beam_competitors_city_competitor_avg_rating float64	beam_competitors_city_competitor_avg_reviews int64	beam_competitors_city_competitor_avg_health float64	beam_competitors_city_competitor_avg_sentiment float64	beam_competitors_city_score_diff float64	beam_competitors_city_rating_diff float64	beam_competitors_city_reviews_diff int64	beam_competitors_city_health_diff float64	beam_competitors_city_sentiment_diff float64	beam_competitors_city_market_type string	beam_competitors_city_review_share float64	beam_competitors_city_density_per_sqkm float64	beam_competitors_city_tier_60_79 float64	beam_competitors_city_tier_80_100 float64	beam_competitors_city_competitive_strength float64	beam_competitors_city_underserved_score float64	beam_competitors_city_competition_intensity float64	beam_competitors_state_competitor_avg_sentiment_30d float64	beam_competitors_state_competitor_avg_sentiment_90d float64	beam_competitors_state_sentiment_diff_30d float64	beam_competitors_state_sentiment_diff_90d float64	beam_competitors_state_competitor_count int64	beam_competitors_state_total_in_state int64	beam_competitors_state_rank_by_score int64	beam_competitors_state_rank_by_rating int64	beam_competitors_state_rank_by_reviews int64	beam_competitors_state_score_percentile float64	beam_competitors_state_rating_percentile float64	beam_competitors_state_reviews_percentile float64	beam_competitors_state_health_percentile float64	beam_competitors_state_sentiment_percentile float64	beam_competitors_state_competitor_avg_score float64	beam_competitors_state_competitor_avg_rating float64	beam_competitors_state_competitor_avg_reviews int64	beam_competitors_state_competitor_avg_health float64	beam_competitors_state_competitor_avg_sentiment float64	beam_competitors_state_score_diff float64	beam_competitors_state_rating_diff float64	beam_competitors_state_reviews_diff int64	beam_competitors_state_health_diff float64	beam_competitors_state_sentiment_diff float64	beam_competitors_state_market_type string	beam_competitors_state_review_share float64	beam_competitors_state_density_per_sqkm float64	beam_competitors_state_underserved_score float64	beam_competitors_state_competition_intensity float64	beam_competitors_state_competitive_strength float64	beam_competitors_country_competitor_avg_sentiment_30d float64	beam_competitors_country_competitor_avg_sentiment_90d float64	beam_competitors_country_sentiment_diff_30d float64	beam_competitors_country_sentiment_diff_90d float64	beam_competitors_country_competitor_count int64	beam_competitors_country_competitor_avg_score float64	beam_competitors_country_competitor_avg_rating float64	beam_competitors_country_competitor_avg_reviews int64	beam_competitors_country_competitor_avg_health float64	beam_competitors_country_competitor_avg_sentiment float64	beam_competitors_country_score_diff float64	beam_competitors_country_rating_diff float64	beam_competitors_country_reviews_diff int64	beam_competitors_country_sentiment_diff float64	beam_competitors_country_score_percentile float64	beam_competitors_country_rating_percentile float64	beam_competitors_country_reviews_percentile float64	beam_competitors_country_health_percentile float64	beam_competitors_country_sentiment_percentile float64	beam_competitors_country_rank_by_score int64	beam_competitors_country_competitive_strength float64	beam_competitors_country_health_diff float64	beam_competitors_country_rank_by_rating int64	beam_competitors_country_rank_by_reviews int64	beam_competitors_country_tier_40_59 float64	beam_competitors_country_tier_60_79 float64	beam_competitors_country_tier_80_100 float64	beam_competitors_country_tier_below_40 float64	beam_competitors_country_total_in_country int64	beam_competitors_city_siblings_competitor_count int64	beam_competitors_city_siblings_competitor_avg_score float64	beam_competitors_city_siblings_competitor_avg_rating float64	beam_competitors_city_siblings_competitor_avg_reviews int64	beam_competitors_city_siblings_competitor_avg_health float64	beam_competitors_city_siblings_competitor_avg_sentiment float64	beam_competitors_city_siblings_score_diff float64	beam_competitors_city_siblings_rating_diff float64	beam_competitors_city_siblings_reviews_diff int64	beam_competitors_city_siblings_sentiment_diff float64	beam_competitors_city_siblings_score_percentile float64	beam_competitors_city_siblings_rating_percentile float64	beam_competitors_city_siblings_reviews_percentile float64	beam_competitors_city_siblings_health_percentile float64	beam_competitors_city_siblings_sentiment_percentile float64	beam_competitors_city_siblings_rank_by_score int64	beam_competitors_city_siblings_competitor_avg_recommend_pct float64	beam_competitors_city_siblings_recommend_pct_diff float64	beam_competitors_city_siblings_recommend_pct_percentile float64	beam_competitors_city_siblings_total_siblings int64	beam_competitors_city_businesses_per_10k_pop float64	beam_competitors_city_population_per_business int64	beam_competitors_city_population_density int64	beam_competitors_city_reviews_per_capita float64	beam_competitors_city_reviews_per_10k_pop float64	beam_competitors_state_businesses_per_10k_pop float64	beam_competitors_state_population_per_business int64	beam_competitors_state_population_density int64	beam_competitors_state_reviews_per_capita float64	beam_competitors_state_reviews_per_10k_pop float64	beam_competitors_1km_hhi_contribution float64	beam_competitors_1km_hhi_minimum float64	beam_competitors_5km_hhi_contribution float64	beam_competitors_5km_hhi_minimum float64	beam_competitors_10km_hhi_contribution float64	beam_competitors_10km_hhi_minimum float64	beam_competitors_city_hhi_contribution float64	beam_competitors_city_hhi_minimum float64	beam_competitors_state_hhi_contribution float64	beam_competitors_state_hhi_minimum float64	beam_trends_score_30d_beam_score_overall float64	beam_trends_score_30d_rating float64	beam_trends_score_30d_review_count int64	beam_trends_score_30d_beam_rating_health float64	beam_trends_score_30d_beam_popularity_percentile float64	beam_trends_score_90d_beam_score_overall float64	beam_trends_score_90d_rating float64	beam_trends_score_90d_review_count float64	beam_trends_score_90d_beam_rating_health float64	beam_trends_score_90d_beam_popularity_percentile float64	beam_trends_competitive_1km_30d_strength_change float64	beam_trends_competitive_1km_30d_rank_change int64	beam_trends_competitive_1km_30d_percentile_change float64	beam_trends_competitive_1km_90d_strength_change float64	beam_trends_competitive_1km_90d_rank_change int64	beam_trends_competitive_1km_90d_percentile_change float64	beam_trends_competitive_5km_30d_strength_change float64	beam_trends_competitive_5km_30d_rank_change int64	beam_trends_competitive_5km_30d_percentile_change float64	beam_trends_competitive_5km_90d_strength_change float64	beam_trends_competitive_5km_90d_rank_change int64	beam_trends_competitive_5km_90d_percentile_change float64	beam_trends_competitive_10km_30d_strength_change float64	beam_trends_competitive_10km_30d_rank_change int64	beam_trends_competitive_10km_30d_percentile_change float64	beam_trends_competitive_10km_90d_strength_change float64	beam_trends_competitive_10km_90d_rank_change int64	beam_trends_competitive_10km_90d_percentile_change float64	beam_trends_competitive_city_30d_strength_change float64	beam_trends_competitive_city_30d_rank_change int64	beam_trends_competitive_city_30d_percentile_change float64	beam_trends_competitive_city_90d_strength_change float64	beam_trends_competitive_city_90d_rank_change int64	beam_trends_competitive_city_90d_percentile_change float64	beam_trends_competitive_state_30d_strength_change float64	beam_trends_competitive_state_30d_rank_change int64	beam_trends_competitive_state_30d_percentile_change float64	beam_trends_competitive_state_90d_strength_change float64	beam_trends_competitive_state_90d_rank_change int64	beam_trends_competitive_state_90d_percentile_change float64	beam_trends_sentiment_current_sentiment float64	beam_trends_sentiment_positive_ratio float64	beam_trends_sentiment_negative_ratio float64	beam_trends_sentiment_review_count int64	beam_trends_velocity_reviews_per_day float64	beam_trends_velocity_reviews_per_month float64	beam_trends_velocity_percentile_city float64	beam_trends_velocity_percentile_state float64	beam_trends_velocity_trend string	beam_velocity_reviews_per_day float64	beam_velocity_reviews_per_week float64	beam_velocity_reviews_per_month float64	beam_velocity_reviews_last_30d int64	beam_velocity_reviews_last_90d int64	beam_velocity_reviews_last_365d int64	beam_velocity_percentile_1km float64	beam_velocity_percentile_5km float64	beam_velocity_percentile_10km float64	beam_velocity_percentile_city float64	beam_velocity_percentile_state float64	beam_velocity_rank_1km int64	beam_velocity_rank_5km int64	beam_velocity_rank_10km int64	beam_velocity_rank_city int64	beam_velocity_rank_state int64	beam_velocity_trend string	beam_velocity_change_30d float64	beam_velocity_change_90d float64	beam_trends_sentiment_recommend_pct float64
L7ZE5NHK	Bowl Izakaya	Food and Drink	Restaurants	Japanese restaurant	Japanese restaurant	1130 8th Ave, Greeley, CO 80631	1130 8th Ave	Greeley	Colorado	null	null	80,631	US	true	40.420137	-104.690495	America/Denver	(970) 83-***	2	null	true	Greeley	Colorado	US	https	https://bowlizakayagreeley.com	bowlizakayagreeley.com	bowlizakayagreeley.com	com	584	2024-08-24	2026-08-24	NAMECHEAP INC	null	null	0	0	null	4.44	338	{"1": 25, "2": 7, "3": 21, "4": 27, "5": 255}	No-contact delivery, Delivery, Takeout, Dine-in	Fast service, Great cocktails	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Alcohol, Beer, Cocktails, Comfort food, Hard liquor, Healthy options, Small plates, Wine	Lunch, Dinner, Dessert, Seating, Table service	Bar onsite, Restroom	Casual, Cozy, Trendy	College students, Groups	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	High chairs, Kids' menu	true	purchase_dataset@	true	true	1	null	null	https://www.facebook.com/bowlizakaya	bowlizakaya	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	https://bowlizakayagreeley.com	null	null	2026-03-23T23:00:04.540906+00:00	0	2.7	3.7	7,609.27	699.1	121.3942	0.37	88.8	84.3	84.3	0.6776	1	0.5551	0.6264	0.5428	0.7397	0.1641	0.0835	77.8	77.1	100	0	0	79.31	17.24	3.45	81.03	13.79	5.17	75.74	19.85	4.41	improving	stable	0.4449	0.7	0.0123	0.9	2	29	58	136	71.6	57	8	67	80.2	94	167	284	266	6,839	12,419	11,174	301,361	588,211	461,425	323,571	167	303,482	54	349,908	497,686	101	375,504	646,505	95	579,087	79	320	717	13,786	28,554	724,238	1,424,284	724,238	0.1337	0.2824	0.326	0.7176	0.2083	0.6099	0.2311	0.4349	0.7689	0.0994	0.3463	0.2075	0.3981	0.7925	0.1362	94	53	100	303,482	189,008	349,908	0.581	0.7347	0.5236	0.8143	0.7397	66	4.23	434	83.4	0.5599	2.6	0.22	-101	1.3	0.1172	497,686	579,272	375,504	0.3307	0.2163	0.497	0.154	0.1641	69.7	4.06	689	75.3	0.4697	-1.1	0.39	-356	9.4	0.2074	646,505	696,607	579,087	0.1264	Average	0.0588	0.2185	0.0362	0.0835	Below Average	65.2	3.78	509	71.2	Emerging	0.4446	3.4	0.67	-176	13.5	0.2325	54	101	95	583	97	competitive	0.0143	16.87	3.8	22.6	64.2	9.4	3,386	1,035	competitive	0.0048	1.27	0	10	83	7	6,594	5,013	competitive	0.0069	0.3	5.3	24.5	58.5	11.7	0.3359	0.5192	0.6641	0.0151	100	101	171	139	196	0.5544	0.6347	0.4948	0.6451	0.6995	76.5	4.23	828	80.4	0.5975	-7.9	0.22	-495	4.3	0.0796	competitive	0.004	0.76	74	26	0.5606	0.37	7.03	0.2022	0.7992	0.7978	-0.2649	100	101	7,336	6,024	7,762	0.5275	0.6057	0.5023	0.6187	0.6953	83.1	4.69	1,661	92.6	0.7751	-14.5	-0.24	-1,328	-7.9	-0.098	competitive	0.002	0.0004	1	0.14	0.5434	0.2094	0.3682	0.7906	0.1661	828,388	62.9	3.88	394	76.6	0.4737	5.7	0.57	-61	0.2034	0.5856	0.5877	0.5804	0.6048	0.6889	340,535	0.5847	8.1	334,289	347,039	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	4.4	0.25	-109	0.1742	0.5516	0.6349	0.4921	0.6389	0.7103	114	64.87	21.12	0.6944	253	9.19	1,088	832	0.7609	7,609.27	0.17	57,737	21	0.0288	287.68	2.03	185.19	0.23	99.01	0.48	105.26	0.16	99.01	0.04	99.01	1.6	0.02	12	0.6	-0.8	null	null	null	null	null	0.1	-103,045	0.14	0.61	303,480	0.581	-0.03	45,310	-0.06	0.35	497,683	0.331	-0.02	28,323	-0.036	0.13	646,502	0.126	0.14	-426,827	0.079	0.56	171	0.554	0.08	-368,218	0.087	0.54	7,336	0.528	0.6771	100	0	333	0.63	19	1	0.896	stable	0.63	4.43	19	19	58	172	0.961	0.963	0.963	1	0.896	33,791	35,078	35,063	1	16	stable	-0.1	null	85.99
65YFY6BQ	Lunas Tacos & Tequila Windsor	Food and Drink	Restaurants	Mexican restaurant	Mexican restaurant, Bar, Brunch restaurant, Caterer, Sandwich shop	1246 Automation Dr, Windsor, CO 80550	1246 Automation Dr	Greeley	Colorado	null	null	80,550	US	true	40.466009	-104.887871	America/Denver	(970) 79-***	2	null	true	Greeley	Colorado	US	https	https://windsor.lunastacos.com	windsor.lunastacos.com	windsor.lunastacos.com	com	3,101	2017-10-03	2026-10-03	GoDaddy.com, LLC	purchase_dataset@lunastacos.com, purchase_dataset@lunastacos.com, purchase_dataset@lunastacos.com	null	3	3	null	4.71	1,028	{"1": 28, "2": 26, "3": 33, "4": 46, "5": 893}	Outdoor seating, Curbside pickup, Delivery, Onsite services, Takeout, Dine-in	Fast service, Great cocktails, Rooftop seating, Serves local specialty	Breakfast, Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Alcohol, Coffee, Happy hour drinks, Happy hour food, Quick bite, Vegetarian options	Breakfast, Brunch, Lunch, Dinner, Catering, Dessert, Seating, Table service	Bar onsite, Restroom	Casual, Cozy, Trendy	Groups, Tourists	Accepts reservations	Credit cards, Debit cards	High chairs, Kids' menu	true	purchase_dataset@	true	true	3	https://www.instagram.com/lunas.tacos	lunas.tacos	https://www.facebook.com/lunastacos	lunastacos	null	null	https://www.tiktok.com/@lunastacos	lunastacos	null	null	null	null	null	null	null	null	null	null	4,700	1.11	null	0.93	1.11	1.11	1,230	null	null	null	null	443	48	2,304	0.52	null	3.02	0.31	0.36	https://windsor.lunastacos.com/windsor-luna-s-tacos-and-tequila-windsor-food-menu	https://tables.toasttab.com/restaurants/dafad1b6-6609-4f4b-9175-0e9fb5d28759/joinwaitlist	https://tables.toasttab.com/restaurants/dafad1b6-6609-4f4b-9175-0e9fb5d28759/joinwaitlist	2026-03-22T08:35:56.767457+00:00	4.32	3.56	0.1	7,703.3	232.3	121.3942	0.37	94.2	100	91.5	0.836	1	0.9323	0.8257	0.7774	0.9556	0.1067	0.0233	96.6	88.9	100	0	0	97.14	0	2.86	92	7	1	88.26	8.1	3.64	improving	improving	0.0677	7.7	0.1549	8.7	1	35	100	247	84.8	58.8	64	83	94.9	90	55	139	67	2,444	6,282	3,401	87,069	286,828	117,206	94,608	55	81,138	6	270,839	597,444	50	613,974	707,068	62	665,926	31	320	717	13,786	28,554	724,238	1,424,284	724,238	0.0535	0.2133	0.2862	-0.2133	0.589	0.8012	0.275	0.5997	-0.275	0.2755	0.1691	0.3415	0.4179	-0.3415	0.4573	61	5	49	81,138	99,951	270,839	0.8873	0.8564	0.631	0.8518	0.9556	71.7	4.37	488	84.3	0.692	9.9	0.32	498	6.9	0.1437	597,444	654,138	613,974	0.198	0.121	0.1784	0.1163	0.1067	66.4	3.92	409	74.3	0.4402	15.2	0.77	577	16.9	0.3955	707,068	729,444	665,926	0.0456	Market Leader	0.016	0.1015	0.0125	0.0233	Emerging	59.5	3.32	325	66	Emerging	0.3473	22.1	1.37	661	25.2	0.4884	6	50	62	299	19	concentrated	0.2876	1.59	0	0	80	20	2,744	1,003	competitive	0.0469	0.62	6.1	20.4	61.2	12.2	8,820	5,026	competitive	0.0473	0.19	16.4	23	52.5	8.2	0.3359	0.5203	-0.3359	0.3549	100	101	20	78	64	0.9508	0.7953	0.8368	0.8342	0.9041	76.5	4.23	829	80.5	0.5983	5.1	0.46	157	10.7	0.2374	competitive	0.0118	0.76	75	25	0.8699	0.37	7.03	0.2022	0.8	-0.2022	0.0752	100	101	937	3,137	2,997	0.938	0.794	0.8082	0.8136	0.9088	83	4.68	1,654	92.6	0.7717	-1.4	0.01	-668	-1.4	0.064	competitive	0.0059	0.0004	1	0.14	0.8558	0.2094	0.3682	-0.2094	0.507	828,388	62.9	3.88	394	76.6	0.4737	18.7	0.81	592	0.362	0.9542	0.7746	0.8596	0.8061	0.9038	36,589	0.8719	14.6	181,847	116,109	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	17.4	0.49	544	0.3328	0.9524	0.8175	0.8532	0.8492	0.9286	13	64.87	26.17	0.8532	253	9.19	1,088	832	0.7619	7,618.73	0.17	57,737	21	0.0286	286.43	827.32	1,666.67	21.99	200	22.4	161.29	1.38	99.01	0.35	99.01	-5.4	-0.01	26	-0.3	-26.8	null	null	null	null	null	0.02	-44,240	0.062	0.8	81,137	0.887	0.01	-24,991	0.035	0.17	597,443	0.198	0	6,862	-0.007	0.05	707,067	0.046	0.45	-432,563	0.483	0.87	20	0.951	0.4	-374,617	0.498	0.86	937	0.938	0.8357	null	null	986	0.83	25	0.955	0.969	stable	0.83	5.83	25	25	79	284	0.974	0.975	0.975	0.955	0.969	22,735	23,587	23,578	3	46	stable	0.06	null	91.04
39LHLTF6	Smokin' Dave's BBQ - GREELEY	Food and Drink	Restaurants	Restaurant	Restaurant	819 9th St, Greeley, CO 80631	819 9th St	Greeley	Colorado	null	null	80,631	US	true	40.424216	-104.691863	America/Denver	(970) 50-***	0	null	true	Greeley	Colorado	US	http	http://greeley.smokindavesbbq.com	greeley.smokindavesbbq.com	greeley.smokindavesbbq.com	com	7,123	2006-09-29	2026-09-29	GoDaddy.com, LLC	null	null	0	0	null	3.88	198	{"1": 25, "2": 23, "3": 19, "4": 15, "5": 113}	Outdoor seating, Delivery, Takeout, Dine-in	Fast service, Great beer selection, Great cocktails, Serves local specialty, Sports	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Coffee, Comfort food, Hard liquor, Quick bite, Small plates, Vegetarian o(...TRUNCATED)	Lunch, Dinner, Catering, Dessert, Seating, Table service	Bar onsite, Gender-neutral restroom, Restroom	Casual, Trendy	Family-friendly, Groups, Tourists	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	purchase_dataset@	true	true	2	https://www.instagram.com/smokin.daves.greeley	smokin.daves.greeley	https://www.facebook.com/smokindavesgreeley	smokindavesgreeley	null	null	null	null	null	null	null	null	null	null	null	null	null	null	53	6.1	null	7.33	6.1	6.1	78	null	null	null	null	null	null	null	null	null	null	null	null	https://order.toasttab.com/online/sdqgreeley	https://google.com/maps/reserve/v/dine/c/23skcizk6gq?source=pa&opi=79508299	https://google.com/maps/reserve/v/dine/c/23skcizk6gq?source=pa&opi=79508299	2026-03-21T22:49:08.270184+00:00	0.05	1.56	2.5	8,073.44	349.9	121.3942	0.37	77.6	76.6	66.2	0.3364	1	0.6429	0.3572	0.3436	0.6936	0.2976	0.0736	82.1	67.2	100	0	0	78.57	14.29	7.14	63.64	27.27	9.09	69.23	25.64	5.13	improving	improving	0.3571	14.9	0.2993	22.2	2	14	44	156	73.8	68.5	68	83	72.4	90	209	524	340	8,333	21,601	14,401	387,370	1,072,260	620,072	416,208	209	483,906	45	461,053	444,022	101	376,375	646,505	95	578,664	184	320	717	13,786	28,554	724,238	1,424,284	724,238	0.1329	0.2612	0.3101	0.7388	0.2525	0.4442	0.2045	0.4171	0.7955	0.1455	0.3985	0.23	0.4505	0.77	0.1121	94	44	100	483,906	244,778	461,053	0.3374	0.6579	0.373	0.8271	0.6936	62.7	4.15	360	83.7	0.5434	8.2	-0.23	-171	-16	-0.2168	444,022	516,378	376,375	0.4024	0.2958	0.496	0.2626	0.2976	71.4	4.13	688	77.4	0.5183	-0.5	-0.21	-499	-9.7	-0.1917	646,505	699,318	578,664	0.1264	Average	0.0553	0.2191	0.0328	0.0736	Below Average	65.2	3.76	510	70.8	Emerging	0.4341	5.7	0.16	-321	-3.1	-0.1075	45	101	95	450	29	competitive	0.0118	14.01	6.8	29.5	56.8	6.8	3,311	1,089	competitive	0.0027	1.27	0	6	84	10	6,682	5,009	competitive	0.0039	0.3	5.3	24.5	59.6	10.6	0.3359	0.5192	0.6641	0.0434	100	101	147	282	241	0.6218	0.2668	0.3782	0.2902	0.2902	76.5	4.23	828	80.4	0.5975	-5.6	-0.31	-639	-12.7	-0.2709	competitive	0.0023	0.76	74	26	0.4422	0.37	7.03	0.2222	0.8009	0.7778	-0.2383	100	101	6,142	11,569	9,453	0.6031	0.2555	0.3942	0.2694	0.3044	83	4.69	1,652	92.6	0.7713	-12.1	-0.77	-1,463	-24.9	-0.4447	competitive	0.0011	0.0004	1	0.14	0.4361	0.2094	0.3682	0.7906	0.1944	828,388	62.9	3.88	394	76.6	0.4737	8	0.04	-205	-0.1471	0.6601	0.2325	0.4555	0.2629	0.2982	278,943	0.4704	-8.9	632,470	450,226	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	6.7	-0.28	-253	-0.1763	0.623	0.1944	0.369	0.2183	0.2302	96	64.87	-16.25	0.2302	253	9.19	1,088	832	0.7609	7,609.27	0.17	57,737	21	0.0286	286.04	1.39	222.22	0.08	99.01	0.15	105.26	0.05	99.01	0.01	99.01	4	0.01	8	-0.3	23	null	null	null	null	null	0.11	-91,223	0.123	0.44	483,902	0.337	-0.02	30,252	-0.04	0.4	444,012	0.402	-0.02	27,099	-0.034	0.13	646,489	0.126	0.02	-426,851	0.146	0.44	147	0.622	-0.02	-369,412	0.163	0.44	6,142	0.603	0.3266	100	0	189	0.37	11	0.846	0.825	accelerating	0.37	2.57	11	11	27	184	0.908	0.911	0.911	0.846	0.825	75,655	78,604	78,576	9	339	accelerating	-0.03	null	48.62
RUHRP6Z3	Taco John's	Food and Drink	Restaurants	Fast food restaurant	"Fast food restaurant, Breakfast restaurant, Burrito restaurant, Lunch restaurant, Takeout Restauran(...TRUNCATED)	2508 11th Ave, Greeley, CO 80631	2508 11th Ave	Greeley	Colorado	null	null	80,631	US	true	40.396834	-104.696556	America/Denver	(970) 35-***	1	null	true	Greeley	Colorado	US	https	https://locations.tacojohns.com/co/greeley/2508-11th-ave	locations.tacojohns.com/co/greeley/2508-11th-ave	locations.tacojohns.com	com	10,840	1996-07-26	2026-07-25	Network Solutions, LLC	purchase_dataset@brmtj.com	null	1	1	Fast-food chain featuring Mexican-inspired tacos, burritos, nachos & breakfast fare.	3.73	873	{"1": 120, "2": 63, "3": 148, "4": 257, "5": 400}	Delivery, Drive-through, Onsite services, Takeout, Dine-in	Fast service	Breakfast, Lunch, Dinner, Solo dining	Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible seating	Coffee, Late-night food, Quick bite, Vegetarian options	Breakfast, Lunch, Dinner, Catering, Counter service, Dessert, Seating	Restroom, Wi-Fi	Casual	Family-friendly, Groups	null	Checks, Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	purchase_dataset@	true	true	3	https://www.instagram.com/tacojohns	tacojohns	https://www.facebook.com/tacojohns	tacojohns	https://twitter.com/tacojohns	tacojohns	null	null	null	null	null	null	null	null	null	null	null	null	19,200	0.35	null	0.32	0.35	0.35	2,237	null	null	null	null	null	null	null	null	null	null	null	null	https://order.tacojohns.com/menu/greeley-11th-ave-3	null	null	2026-03-21T11:04:16.980389+00:00	17.65	0.84	0	7,605.09	237.1	121.3942	0.37	74.6	98.1	64.9	0.3544	1	0.6667	0.4085	0.215	0.1457	0.4599	0.0709	83.3	60.8	100	0	0	83.33	16.67	0	65.22	26.09	8.7	59.65	36.84	3.51	improving	improving	0.3333	22.5	0.4517	37	1	6	23	57	72.5	49.5	40	100	81.1	88	77	565	100	3,202	22,802	4,688	122,725	1,134,934	171,068	132,694	77	603,456	38	283,739	335,750	101	327,460	664,794	57	589,982	199	320	717	13,786	28,554	724,238	1,424,284	724,238	0.1157	0.2509	0.3444	0.7491	0.4056	0.2944	0.1712	0.2063	0.8288	0.5437	0.5082	0.31	0.499	0.69	0.251	56	37	100	603,456	637,860	283,739	0.178	0.1305	0.6134	0.1185	0.1457	59.6	3.59	479	69.1	0.364	10.5	0.14	388	-4.2	-0.0105	335,750	431,601	327,460	0.5454	0.4056	0.5611	0.3967	0.4599	74.2	4.2	744	79.4	0.5641	-4.1	-0.47	123	-14.5	-0.2106	664,794	706,301	589,982	0.102	Below Average	0.046	0.2038	0.0259	0.0709	Average	63.8	3.7	484	69.8	Emerging	0.4311	6.3	0.03	383	-4.9	-0.0776	38	101	57	491	118	competitive	0.0466	11.78	8.1	35.1	54.1	2.7	3,281	1,391	competitive	0.0115	1.27	0	1	83	16	6,880	5,013	competitive	0.031	0.18	7.1	23.2	60.7	8.9	0.3259	0.5216	0.6741	0.2284	100	101	152	309	83	0.6088	0.2021	0.7876	0.2358	0.3057	76.6	4.24	830	80.8	0.6031	-6.5	-0.51	37	-15.9	-0.2496	competitive	0.0103	0.76	74	26	0.5404	0.37	7.04	0.1922	0.7969	0.8078	-0.0469	100	101	6,550	12,567	3,647	0.5778	0.193	0.7661	0.2371	0.3242	83	4.69	1,670	92.6	0.7741	-12.9	-0.96	-803	-27.7	-0.4206	competitive	0.0052	0.0004	1	0.14	0.5188	0.2094	0.3682	0.7906	0.3818	828,388	62.9	3.88	394	76.6	0.4737	7.2	-0.15	473	-0.1202	0.6344	0.1659	0.8281	0.2289	0.3205	300,287	0.552	-11.7	688,504	142,128	24.3	58.7	7.7	9.2	828,389	86	63.2	3.84	518	68.1	0.3768	6.9	-0.11	349	-0.0233	0.6706	0.4118	0.6706	0.4471	0.5176	29	63.6	12.3	0.5176	86	9.19	1,088	832	0.763	7,629.67	0.17	57,737	21	0.0289	289.28	21.74	263.16	1.33	99.01	9.6	175.44	1.07	99.01	0.27	99.01	-8.3	0	8	-0.2	-33.4	null	null	null	null	null	-0.06	87,031	-0.115	0.29	603,456	0.178	-0.01	7,658	-0.01	0.51	335,750	0.545	-0.01	18,050	-0.022	0.12	664,794	0.102	0.12	-430,405	0.136	0.54	152	0.609	0.06	-369,004	0.138	0.52	6,550	0.578	0.3535	100	0	867	0.2	6	0.684	0.664	stable	0.2	1.4	6	6	18	64	0.774	0.782	0.782	0.684	0.664	173,580	180,528	180,244	8	257	stable	0.07	null	75.9
5BTFMBNK	McDonald's	Food and Drink	Restaurants	Fast food restaurant	"Fast food restaurant, Breakfast restaurant, Coffee shop, Hamburger restaurant, Restaurant, Sandwich(...TRUNCATED)	55 Oak Ave B, Eaton, CO 80615	55 Oak Ave B	Greeley	Colorado	null	null	80,615	US	true	40.524082	-104.710688	America/Denver	(970) 45-***	2	null	true	Greeley	Colorado	US	https	https://mcdonalds.com/us/en-us/location/co/eaton/55-s-oak-b/33289.html	mcdonalds.com/us/en-us/location/co/eaton/55-s-oak-b/33289.html	mcdonalds.com	com	11,585	1994-07-12	2026-07-11	CSC Corporate Domains, Inc.	"purchase_dataset@gmail.com, purchase_dataset@gmail.com, purchase_dataset@yahoo.com.tw, purchase_dat(...TRUNCATED)	realdomain	29	29	Classic, long-running fast-food chain known for its burgers & fries.	3.51	921	{"1": 181, "2": 83, "3": 197, "4": 237, "5": 398}	Curbside pickup, Delivery, Drive-through, Onsite services, Takeout, Dine-in	Great coffee	Breakfast, Lunch, Dinner, Solo dining	Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom	Coffee, Late-night food, Quick bite	Breakfast, Lunch, Dinner, Counter service, Dessert, Seating	Restroom, Wi-Fi	Casual	Groups	null	Debit cards, NFC mobile payments	Has changing table(s), High chairs, Kids' menu	true	purchase_dataset@	true	true	5	https://www.instagram.com/mcdonalds	mcdonalds	https://www.facebook.com/mcdonalds	mcdonalds	https://twitter.com/mcdonalds	mcdonalds	https://www.tiktok.com/@mcdonalds	mcdonalds	null	null	null	null	null	null	null	null	https://www.pinterest.com/mcdonalds	mcdonalds	5,513,935	0.37	null	0.21	0.37	0.37	493	null	null	null	null	5,300,000	347	37,200,000	4.88	1.32	1.88	2.37	4.88	https://mcdonalds.com/us/en-us/full-menu.html	null	null	2026-03-21T10:33:42.823011+00:00	5,067.95	0.7	0	7,974.93	142.1	121.3942	0.37	70.2	98.8	57.8	0.179	-1	0.0514	-0.0487	0.0984	0.8289	0.9681	0.3897	52.6	54.9	0	100	0	50	41.67	8.33	45.16	45.16	9.68	52.5	36.25	11.25	declining	stable	-1.0514	-2.3	-0.047	-4.2	2	12	31	80	72.2	48.5	92	100	58.3	88	68	602	88	3,001	24,103	4,362	112,942	1,204,773	156,883	122,336	68	103,617	10	535,489	54,807	3	328,410	689,671	11	705,836	217	320	717	13,786	28,554	724,238	1,424,284	724,238	0.2061	0.05	0.3831	0.45	-0.1214	0.6525	0.2778	0.4972	0.2222	-0.2355	0.8012	0.4167	0.8264	0.0833	-0.5647	10	9	2	103,617	169,495	535,489	0.8561	0.7613	0.2722	0.7187	0.8289	70.7	4.26	308	81.4	0.5973	-0.1	-0.74	606	-23.5	-0.4155	54,807	78,695	328,410	0.9209	0.8831	0.5598	0.9133	0.9681	80	4.48	743	87.9	0.7442	-9.4	-0.96	171	-30	-0.5624	689,671	319,725	705,836	0.0686	Strong	0.5476	0.0478	0.5471	0.3897	Market Leader	61.6	4.37	211	84.1	Below Average	0.597	9	-0.85	703	-26.2	-0.4152	10	3	11	290	200	moderate	0.2482	2.86	0	0	100	0	2,136	1,252	concentrated	0.3808	0.03	0	0	50	50	7,258	6,578	moderate	0.3027	0.03	0	50	50	0	0.3309	0.5265	0.1691	-0.2648	100	101	149	338	77	0.6166	0.1244	0.8031	0.1632	0.1684	76.6	4.24	830	80.8	0.6048	-6	-0.72	84	-22.9	-0.423	competitive	0.0109	0.76	74	26	0.5249	0.37	7.04	0.2222	0.8009	0.2778	-0.5392	100	101	6,300	13,371	3,335	0.5931	0.1426	0.7865	0.1831	0.2185	83	4.69	1,652	92.6	0.7713	-12.4	-1.17	-738	-34.7	-0.5895	competitive	0.0055	0.0004	1	0.14	0.516	0.2094	0.3682	0.2906	-0.1065	828,388	62.9	3.88	394	76.6	0.4737	7.7	-0.36	520	-0.2919	0.6504	0.1109	0.8414	0.171	0.2077	286,885	0.5458	-18.7	734,930	131,133	24.3	58.7	7.7	9.2	828,389	86	63.2	3.84	518	68.1	0.3768	7.4	-0.32	396	-0.195	0.6824	0.2471	0.7059	0.2941	0.2824	28	63.6	7.99	0.4471	86	9.19	1,088	832	0.7625	7,625.35	0.17	57,737	21	0.0286	286.04	615.87	1,000	1,450.34	3,333.33	916.57	909.09	1.19	99.01	0.3	99.01	-6.8	0	6	0	-35.8	null	null	null	null	null	0.07	-137,723	0.19	0.65	103,617	0.856	0.04	-74,818	0.099	0.8	54,807	0.921	-0.01	16,934	-0.021	0.21	689,671	0.069	0.1	-430,408	0.143	0.52	149	0.617	0.05	-369,254	0.153	0.52	6,300	0.593	0.1818	50	0	914	0.17	5	0.553	0.546	stable	0.17	1.17	5	5	17	85	0.719	0.729	0.729	0.553	0.546	213,014	221,732	221,154	14	373	stable	0	null	71.59
6C9S3HM8	Freddy's Frozen Custard & Steakburgers	Food and Drink	Restaurants	Hamburger restaurant	Hamburger restaurant, American restaurant, Delivery service, Fast food restaurant, Restaurant	4735 W 25th St, Greeley, CO 80634	4735 W 25th St	Greeley	Colorado	null	null	80,634	US	true	40.397735	-104.756823	America/Denver	(970) 70-***	2	null	true	Greeley	Colorado	US	https	https://freddys.com/location/greeley-co	freddys.com/location/greeley-co	freddys.com	com	10,106	1998-07-30	2028-07-29	NameCheap, Inc.	purchase_dataset@freddysusa.com, purchase_dataset@gmail.com, purchase_dataset@freddysusa.com	null	3	3	Vintage-style chain for steakburgers, hot dogs & other fast-food staples, plus frozen custard.	4.22	1,094	{"1": 79, "2": 39, "3": 132, "4": 307, "5": 774}	Outdoor seating, No-contact delivery, Delivery, Drive-through, Onsite services, Takeout, Dine-in	Fast service, Great dessert	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	Coffee, Comfort food, Late-night food, Quick bite	Lunch, Dinner, Catering, Counter service, Dessert, Seating	Restroom, Wi-Fi	Casual, Quiet, Trendy	College students, Family-friendly, Groups, LGBTQ+ friendly, Tourists	null	Credit cards, Debit cards, NFC mobile payments	Good for kids, Has changing table(s), High chairs, Kids' menu	true	purchase_dataset@	true	true	6	https://www.instagram.com/freddysusa	freddysusa	https://www.facebook.com/freddysusa	freddysusa	https://twitter.com/freddysusa	freddysusa	https://www.tiktok.com/@freddysusa	freddysusa	https://www.linkedin.com/company/freddy-s-p-a-	freddy-s-p-a-	https://www.youtube.com/freddysusa	freddysusa	null	null	null	null	null	null	110,800	0.16	null	0.18	0.16	0.16	3,041	null	null	null	null	15,700	257	162,400	2.97	null	4.04	2.87	2.97	https://freddys.com/menu	null	null	2026-03-20T12:23:23.209767+00:00	101.84	0.56	0	7,783.02	118.1	121.3942	0.37	84.4	100	80.3	0.5904	1	0.6667	0.681	0.6684	0.1885	0.1795	0.3796	83.3	83.4	100	0	0	83.33	16.67	0	84.62	15.38	0	83.13	14.46	2.41	improving	stable	0.3333	-0.1	-0.0017	-0.1	2	6	26	83	81.6	46.8	88	100	83.5	86	33	395	38	1,366	16,869	1,701	48,125	821,744	60,976	52,006	33	204,021	32	69,323	466,039	101	382,075	602,204	101	589,982	126	320	717	13,786	28,554	724,238	1,424,284	724,238	0.2814	0.2558	0.4511	0.7442	0.5489	0.6233	0.371	0.3368	0.629	0.6632	0.3579	0.2397	0.4286	0.7603	0.5714	100	31	100	204,021	572,399	69,323	0.717	0.2162	0.9055	0.1291	0.1885	67.9	3.73	708	69.5	0.3845	16.1	0.49	386	10.8	0.2082	466,039	586,458	382,075	0.373	0.2074	0.4884	0.1497	0.1795	70.7	4.05	681	75.2	0.4763	13.3	0.17	413	5.1	0.1164	602,204	366,297	589,982	0.1857	Average	0.4867	0.2038	0.4543	0.3796	Below Average	68.1	4.34	484	82.8	Below Average	0.5938	15.9	-0.12	610	-2.5	-0.0011	32	101	101	581	180	competitive	0.0475	9.87	3.2	19.4	67.7	9.7	3,256	1,014	competitive	0.0158	1.27	0	7	81	12	6,015	5,002	competitive	0.0221	0.32	0	22	71	7	0.3259	0.5191	0.6741	0.4809	100	101	11	208	35	0.9741	0.4508	0.9119	0.5181	0.5699	76.4	4.24	828	80.6	0.6007	7.6	-0.02	266	-0.3	-0.008	competitive	0.013	0.76	75	25	0.7984	0.37	7.02	0.2022	0.8	0.7978	0.2	100	101	361	8,928	1,410	0.9762	0.4226	0.9092	0.4894	0.5778	83	4.68	1,654	92.6	0.7717	1	-0.46	-560	-12.3	-0.179	competitive	0.0066	0.0004	1	0.14	0.79	0.2094	0.3682	0.7906	0.6318	828,388	62.9	3.88	394	76.6	0.4737	21.1	0.34	700	0.119	0.9841	0.4005	0.9337	0.4824	0.5711	12,478	0.7939	3.7	490,987	54,446	24.3	58.7	7.7	9.2	828,389	86	63.2	3.84	518	68.1	0.3768	20.8	0.38	576	0.2159	0.9647	0.6235	0.8235	0.6824	0.6941	4	63.6	20.29	0.7412	86	9.19	1,088	832	0.7609	7,608.81	0.17	57,737	21	0.0286	286.43	22.55	312.5	2.5	99.01	4.88	99.01	1.7	99.01	0.43	99.01	-1.2	-0.01	14	-0.1	-47.1	null	null	null	null	null	-0.07	110,165	-0.153	0.62	204,021	0.717	-0.02	27,073	-0.036	0.36	466,039	0.373	-0.01	7,897	-0.009	0.28	602,204	0.186	0.38	-432,572	0.507	0.8	11	0.974	0.33	-375,193	0.536	0.79	361	0.976	0.5927	100	0	1,085	0.13	4	1	0.414	stable	0.13	0.93	4	4	13	87	0.648	0.66	0.66	1	0.414	264,626	275,746	274,862	1	112	stable	0.1	null	83.89
E9D9USQU	Yummy Chinese Restaurant	Food and Drink	Restaurants	Chinese restaurant	Chinese restaurant	2028 35th Ave, Greeley, CO 80634	2028 35th Ave	Greeley	Colorado	null	null	80,634	US	true	40.405544	-104.732816	America/Denver	(970) 33-***	2	null	true	Greeley	Colorado	US	https	https://yummychinesegreeley.kwickmenu.com/index.php	yummychinesegreeley.kwickmenu.com/index.php	yummychinesegreeley.kwickmenu.com	com	3,258	2017-04-29	2032-04-29	GoDaddy.com, LLC	purchase_dataset@ymail.com	null	1	1	General Tso's chicken & other standard Chinese dishes are provided in casual quarters with a bar.	4.2	478	{"1": 45, "2": 23, "3": 28, "4": 79, "5": 302}	Curbside pickup, Delivery, Onsite services, Takeout, Dine-in	Fast service, Great tea selection	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Comfort food, Hard liquor, Private dining room, Quick bite, Vegetarian op(...TRUNCATED)	Lunch, Dinner, Dessert, Seating, Table service	Restroom, Wi-Fi	Casual, Cozy, Quiet	Groups	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs	true	purchase_dataset@	true	true	1	null	null	https://www.facebook.com/hunangreeley	hunangreeley	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	https://yummygreeley.com	null	null	2026-03-19T21:50:08.022400+00:00	0	0.14	3.6	7,609.27	699	121.3942	0.37	84	89.3	79.9	0.5832	1	1	1	0.8034	0.1356	0.4266	0.0526	100	90.2	100	0	0	100	0	0	100	0	0	90.91	9.09	0	stable	improving	0	9.8	0.1966	10.9	1	9	18	44	71.1	27.4	8	100	94.9	84	138	406	210	5,681	17,278	8,937	240,222	842,490	356,342	258,196	138	553,427	13	501,928	297,360	101	246,349	699,718	29	651,957	132	320	717	13,786	28,554	724,238	1,424,284	724,238	0.0668	0.2429	0.3604	0.7571	0.6396	0.3105	0.125	0.2562	0.875	0.7438	0.5411	0.2858	0.4816	0.7142	0.5184	28	12	100	553,427	440,677	501,928	0.2446	0.3914	0.3176	0.1692	0.1356	61.1	3.91	332	70.8	0.3585	10.7	0.29	146	9.1	0.2247	297,360	482,489	246,349	0.596	0.3395	0.6695	0.3412	0.4266	75	4.16	830	78.6	0.5551	-3.2	0.04	-352	1.3	0.0281	699,718	719,431	651,957	0.0553	Below Average	0.0289	0.1202	0.0164	0.0526	Average	60.5	3.55	355	67.6	Emerging	0.4092	11.3	0.65	123	12.3	0.174	13	101	29	229	69	moderate	0.1071	3.82	8.3	25	66.7	0	2,792	1,414	competitive	0.0057	1.27	0	0	81	19	5,788	5,026	competitive	0.0459	0.09	10.7	32.1	50	7.1	0.3359	0.5192	0.6641	0.4808	100	101	137	214	158	0.6451	0.443	0.5933	0.513	0.5544	76.5	4.23	828	80.4	0.5975	-4.7	-0.03	-350	-0.5	-0.0143	competitive	0.0057	0.76	74	26	0.5689	0.37	7.03	0.1922	0.7983	0.8078	0.2017	100	101	5,693	9,131	6,361	0.6323	0.4082	0.5921	0.4757	0.5633	83	4.68	1,659	92.6	0.7731	-11.2	-0.48	-1,181	-12.7	-0.1899	competitive	0.0029	0.0004	1	0.14	0.553	0.2094	0.3682	0.7906	0.6318	828,388	62.9	3.88	394	76.6	0.4737	8.9	0.32	84	0.1095	0.6883	0.3856	0.6683	0.4692	0.559	255,641	0.5915	3.3	502,224	274,279	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	7.6	0	36	0.0803	0.6389	0.3929	0.6071	0.4683	0.5317	91	64.87	18.29	0.5833	253	9.19	1,088	832	0.7609	7,609.27	0.17	57,737	21	0.0287	287.28	114.66	769.23	0.33	99.01	21.05	344.83	0.33	99.01	0.08	99.01	-0.1	0.01	3	0.1	-39.8	null	null	null	null	null	-0.07	115,615	-0.154	0.31	553,426	0.245	-0.02	20,518	-0.028	0.54	297,355	0.596	0	10,575	-0.012	0.07	699,713	0.055	0.15	-426,861	0.169	0.57	137	0.645	0.09	-369,861	0.192	0.55	5,693	0.632	0.5832	100	0	477	0.03	1	0.091	0.121	decelerating	0.03	0.23	1	1	10	53	0.281	0.292	0.294	0.091	0.121	528,654	556,970	554,104	6	298	decelerating	-0.17	null	83.16
WRDNRR9Q	Wonderful Inn Chinese Restaurant	Food and Drink	Restaurants	Chinese restaurant	Chinese restaurant	3605 W 10th St, Greeley, CO 80634	3605 W 10th St	Greeley	Colorado	null	null	80,634	US	true	40.423353	-104.737767	America/Denver	(970) 35-***	2	null	true	Greeley	Colorado	US	https	https://fronteats.com/product/#/pos/home/home?mid=532596	fronteats.com/product/#/pos/home/home?mid=532596	fronteats.com	com	923	2023-09-20	2026-09-20	Squarespace Domains LLC	purchase_dataset@gmail.com, purchase_dataset@gmail.com	null	2	2	Straightforward Chinese kitchen doling out hefty portions of classic dishes in basic surrounds.	4.4	624	{"1": 38, "2": 20, "3": 28, "4": 115, "5": 425}	No-contact delivery, Delivery, Onsite services, Takeout, Dine-in	Fast service, Great tea selection	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Coffee, Comfort food, Healthy options, Quick bite, Small plates, Vegetari(...TRUNCATED)	Lunch, Dinner, Dessert, Seating, Table service	Restroom	Casual, Cozy, Quiet	Groups	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs	true	purchase_dataset@	true	true	3	https://www.instagram.com/georgialeeeats	georgialeeeats	https://www.facebook.com/p/new-asia-chinese-restaurant-61575583932777	new-asia-chinese-restaurant-61575583932777	null	null	https://www.tiktok.com/@fronteats.com	fronteats.com	null	null	null	null	null	null	null	null	null	null	604	4.22	null	4.22	4.22	4.22	872	null	null	null	null	10	38	76	1.39	null	null	0.58	1.66	null	null	null	2026-03-19T21:50:07.945576+00:00	0.54	0.28	0.4	7,984.11	232.6	121.3942	0.37	88	93.2	86.5	0.7142	null	0.5	0.5714	0.5647	0.4829	0.3362	0.1834	75	78.2	null	null	null	75	25	0	78.57	21.43	0	76.47	20.59	2.94	stable	declining	null	-3.2	-0.0647	-4.1	0	4	14	34	78.5	32.8	76	100	79.5	84	115	302	163	4,622	13,238	7,035	189,440	632,837	272,396	203,273	115	173,578	24	61,163	340,179	101	294,347	698,899	56	688,996	89	320	717	13,786	28,554	724,238	1,424,284	724,238	0.0842	0.2061	0.3926	-0.2061	0.2074	0.7305	0.1739	0.5097	-0.1739	0.0903	0.4749	0.3155	0.4835	-0.3155	0.1165	55	23	100	173,578	355,826	61,163	0.7591	0.5063	0.9166	0.3146	0.4829	68.6	4.01	729	74.1	0.4797	11.2	0.39	-105	12.4	0.2345	340,179	546,062	294,347	0.5396	0.2584	0.6053	0.2218	0.3362	74.1	4.1	779	76.7	0.5297	5.7	0.3	-155	9.8	0.1845	698,899	637,643	688,996	0.0564	Strong	0.135	0.0705	0.2278	0.1834	Average	60.6	4.04	268	78.8	Emerging	0.5154	19.2	0.36	356	7.7	0.1988	24	101	56	411	29	competitive	0.0359	7.32	0	13	73.9	13	3,491	1,002	competitive	0.0079	1.27	0	2	82	16	5,857	5,010	competitive	0.0406	0.18	5.5	47.3	41.8	5.5	0.3359	0.5231	-0.3359	0.0769	100	101	29	157	129	0.9223	0.5803	0.6658	0.6995	0.7461	76.5	4.24	833	80.5	0.5995	3.3	0.16	-209	6	0.1147	competitive	0.0074	0.76	74	26	0.7427	0.37	7.03	0.2122	0.7978	-0.2122	-0.1978	100	101	1,652	6,734	5,174	0.8909	0.5608	0.6684	0.6759	0.7566	83	4.69	1,664	92.6	0.7721	-3.2	-0.29	-1,040	-6.1	-0.0579	competitive	0.0037	0.0004	1	0.14	0.7251	0.2094	0.3682	-0.2094	0.2318	828,388	62.9	3.88	394	76.6	0.4737	16.9	0.52	230	0.2405	0.9179	0.5433	0.739	0.6618	0.7447	66,101	0.7519	9.9	370,747	215,854	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	15.6	0.2	182	0.2113	0.9206	0.5754	0.6905	0.7143	0.7778	20	64.87	25.15	0.8254	253	9.19	1,088	832	0.7652	7,652.01	0.17	57,737	21	0.0288	288.16	12.86	416.67	0.63	99.01	16.52	178.57	0.55	99.01	0.14	99.01	-2.6	-0.01	3	-0.3	-41.3	null	null	null	null	null	-0.05	73,489	-0.102	0.73	173,577	0.759	-0.01	19,158	-0.026	0.47	340,177	0.54	0	1,166	0.001	0.08	698,897	0.056	0.32	-430,528	0.449	0.74	29	0.922	0.26	-373,902	0.451	0.73	1,652	0.891	0.7142	null	null	622	0.07	2	0.636	0.283	decelerating	0.07	0.47	2	2	9	37	0.439	0.452	0.454	0.636	0.283	417,455	437,538	435,431	4	248	decelerating	-0.03	null	90.02
BXKL467E	Coyote's Southwestern Grill	Food and Drink	Restaurants	Southwestern restaurant (US)	Southwestern restaurant (US), Brunch restaurant	5250 W 9th St Dr, Greeley, CO 80634	5250 W 9th St Dr	Greeley	Colorado	null	null	80,634	US	true	40.421849	-104.768092	America/Denver	(970) 33-***	2	null	true	Greeley	Colorado	US	http	http://coyotesgreeley.com	coyotesgreeley.com	coyotesgreeley.com	com	5,369	2011-07-19	2026-07-19	TUCOWS.COM, CO.	purchase_dataset@hotmail.com	null	1	1	Ample portions of Southwestern eats & margaritas served in a lively cantina with patio seating.	4.23	1,058	{"1": 56, "2": 53, "3": 111, "4": 266, "5": 678}	Outdoor seating, Curbside pickup, No-contact delivery, Delivery, Onsite services, Takeout, Dine-in	Fast service, Great beer selection, Great cocktails, Great dessert, Serves local specialty, Sports	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Coffee, Comfort food, Happy hour drinks, Happy hour food, Hard liquor, He(...TRUNCATED)	Breakfast, Brunch, Lunch, Dinner, Catering, Dessert, Seating, Table service	Bar onsite, Restroom, Wi-Fi	Casual, Cozy, Trendy	Family-friendly, Groups, Tourists	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	purchase_dataset@	true	true	1	null	null	https://www.facebook.com/coyotes.greeley	coyotes.greeley	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	null	https://coyotesgreeley.com/greeley-coyote-s-southwestern-grill-food-menu	https://opentable.com/restaurant/profile/1108492	https://opentable.com/restaurant/profile/1108492	2026-03-19T12:30:03.087015+00:00	0	1	2.3	7,612.11	697.9	121.3942	0.37	84.6	100	80.3	0.6158	1	0.8713	0.7086	0.664	0.205	0.1686	0.2502	93.6	83.2	100	0	0	100	0	0	85.71	7.14	7.14	80.82	10.96	8.22	improving	improving	0.1287	10.4	0.2073	12.5	3	12	28	73	75.3	50.5	8	100	91.9	84	43	392	52	1,972	16,718	2,624	68,136	813,122	89,648	74,005	43	638,839	13	466,799	459,815	101	382,847	562,956	101	518,859	124	320	717	13,786	28,554	724,238	1,424,284	724,238	0.2687	0.2508	0.4125	0.7492	0.4016	0.1805	0.1458	0.0841	0.8542	0.73	0.356	0.2772	0.4537	0.7228	0.3604	100	12	100	638,839	690,593	466,799	0.1311	0.0618	0.3652	0.1374	0.205	58.2	3.37	356	69.8	0.3914	17.5	0.86	702	10.5	0.2197	459,815	599,558	382,847	0.3815	0.1907	0.4873	0.1337	0.1686	70.9	4.03	680	74.8	0.4717	4.8	0.2	378	5.5	0.1394	562,956	525,631	518,859	0.2385	Emerging	0.278	0.2996	0.2513	0.2502	Below Average	70.5	4.21	645	79.3	Below Average	0.5468	5.2	0.02	413	1	0.0643	13	101	101	593	316	moderate	0.1983	3.82	16.7	25	50	8.3	3,113	1,133	competitive	0.0153	1.27	0	5	82	13	6,631	5,046	competitive	0.0161	0.32	0	12	79	9	0.3259	0.521	0.6741	0.2931	100	101	73	207	43	0.8083	0.4663	0.886	0.5181	0.601	76.5	4.24	828	80.6	0.6006	-0.8	-0.01	230	-0.3	0.0105	competitive	0.0126	0.76	74	26	0.729	0.37	7.03	0.1922	0.8025	0.8078	0.0116	100	101	3,664	8,815	2,183	0.762	0.4286	0.8589	0.4894	0.6024	83	4.68	1,663	92.6	0.7711	-7.3	-0.45	-605	-12.3	-0.16	competitive	0.0063	0.0004	1	0.14	0.691	0.2094	0.3682	0.7906	0.4459	828,388	62.9	3.88	394	76.6	0.4737	12.8	0.35	664	0.1374	0.8072	0.4073	0.905	0.4824	0.5952	157,359	0.7166	3.7	485,334	77,807	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	11.5	0.03	616	0.1082	0.7857	0.4246	0.9087	0.4841	0.5873	54	64.87	22.29	0.7262	253	9.19	1,088	832	0.7612	7,612.11	0.17	57,737	21	0.0288	287.96	393.28	769.23	2.35	99.01	2.6	99.01	1.59	99.01	0.4	99.01	-1.6	0	14	0.1	-40.8	null	null	null	null	null	-0.02	25,444	-0.032	0.18	638,838	0.131	-0.02	33,207	-0.043	0.36	459,814	0.382	-0.01	12,888	-0.016	0.27	562,955	0.239	0.31	-430,484	0.335	0.73	73	0.808	0.23	-371,890	0.322	0.69	3,664	0.762	0.6111	100	0	1,050	0.23	7	0	0.273	stable	0.23	1.63	7	7	18	85	0.816	0.822	0.822	0	0.273	142,983	148,636	148,433	1	6	stable	0	null	87.16
NUQTQUPN	El Pueblito Mexican Restaurant	Food and Drink	Restaurants	Mexican restaurant	Mexican restaurant, Latin American restaurant, Restaurant	2435 W 10th St, Greeley, CO 80631	2435 W 10th St	Greeley	Colorado	null	null	80,631	US	true	40.423203	-104.7197	America/Denver	(970) 34-***	2	null	true	Greeley	Colorado	US	http	http://elpueblitoco.com	elpueblitoco.com	elpueblitoco.com	com	1,497	2022-02-23	2027-02-23	Tucows Domains Inc.	null	null	0	0	"Casual, family-run spot offering a range of traditional Mexican entrees, including steaks & seafood(...TRUNCATED)	4.49	832	{"1": 38, "2": 20, "3": 46, "4": 141, "5": 615}	Outdoor seating, Curbside pickup, Delivery, Takeout, Dine-in	Fast service, Great cocktails, Great dessert, Serves local specialty	Lunch, Dinner, Solo dining	"Wheelchair accessible entrance, Wheelchair accessible parking lot, Wheelchair accessible restroom, (...TRUNCATED)	"Alcohol, Beer, Cocktails, Coffee, Comfort food, Happy hour drinks, Hard liquor, Quick bite, Small p(...TRUNCATED)	Breakfast, Lunch, Dinner, Catering, Dessert, Seating, Table service	Restroom	Casual, Cozy	Groups	Accepts reservations	Credit cards, Debit cards, NFC mobile payments	Good for kids, High chairs, Kids' menu	true	purchase_dataset@	true	true	3	https://www.instagram.com/el_pueblito_co_	el_pueblito_co_	https://www.facebook.com/elpueblitonoco	elpueblitonoco	null	null	https://www.tiktok.com/@elpueblitocorestaurant	elpueblitocorestaurant	null	null	null	null	null	null	null	null	null	null	88	6.53	null	null	1.14	7.01	16	null	null	null	null	0	3	0	0	null	null	null	0	https://foodbooking.com/ordering/restaurant/menu?company_uid=d366d667-cf17-4c98-98b6-042b59aa1552&restaurant_uid=e4c77c37-a028-49fd-bfd1-020ed5ea8cf1	null	null	2026-03-19T12:30:03.012490+00:00	0.08	0.57	0.5	8,131.32	232.4	121.3942	0.37	89.8	97.4	88.2	0.76	1	0.7107	0.7577	0.7382	0.2539	0.3797	0.0846	85.5	86.9	100	0	0	84.21	15.79	0	86.11	13.89	0	87.67	12.33	0	improving	stable	0.2893	-1.4	-0.0275	-1.6	3	19	36	73	79.7	36.8	76	83	87.5	84	85	254	110	3,412	11,233	5,024	131,934	528,753	184,373	142,424	85	533,374	31	325,762	340,179	101	259,983	684,745	45	652,465	65	320	717	13,786	28,554	724,238	1,424,284	724,238	0.082	0.2114	0.3395	0.7886	0.3371	0.3049	0.15	0.4057	0.85	0.2709	0.4999	0.3008	0.4769	0.6992	0.1997	44	30	100	533,374	662,704	325,762	0.2714	0.0981	0.5563	0.2033	0.2539	61.6	3.51	450	71.7	0.4098	18.6	0.98	382	16.5	0.3496	340,179	516,378	259,983	0.5396	0.2958	0.6512	0.2749	0.3797	74.1	4.13	815	77.6	0.542	6.1	0.36	17	10.6	0.2174	684,745	700,568	652,465	0.0753	Below Average	0.0536	0.1195	0.0287	0.0846	Average	62.1	3.75	354	70.3	Emerging	0.4456	18.1	0.74	478	17.9	0.3138	31	101	45	521	44	competitive	0.0581	9.55	13.3	10	70	6.7	3,267	1,060	competitive	0.0101	1.27	0	3	82	15	6,134	5,015	competitive	0.0507	0.14	6.8	31.8	52.3	9.1	0.3259	0.5223	0.6741	0.1543	100	101	27	121	92	0.9326	0.6788	0.7642	0.772	0.8212	76.5	4.23	830	80.5	0.5991	3.7	0.26	2	7.7	0.1603	competitive	0.0099	0.76	75	25	0.806	0.37	7.03	0.1922	0.7971	0.8078	-0.1205	100	101	1,455	5,360	3,857	0.9042	0.6481	0.7528	0.7338	0.8217	82.9	4.68	1,669	92.5	0.7698	-2.7	-0.19	-837	-4.3	-0.0104	competitive	0.005	0.0004	1	0.14	0.782	0.2094	0.3682	0.7906	0.3084	828,388	62.9	3.88	394	76.6	0.4737	17.3	0.61	438	0.2857	0.9269	0.6221	0.8173	0.7167	0.8115	58,718	0.8026	11.6	306,364	151,114	24.3	58.7	7.7	9.2	828,389	253	64.2	4.2	442	77.4	0.5029	16	0.29	390	0.2565	0.9325	0.6825	0.7897	0.7817	0.8492	18	64.87	27.05	0.8929	253	9.19	1,088	832	0.7633	7,632.89	0.17	57,737	21	0.0289	289.1	33.72	322.58	1.02	99.01	25.71	222.22	0.98	99.01	0.25	99.01	-1.2	0	15	0.2	-44.8	null	null	null	null	null	-0.03	31,116	-0.041	0.3	533,373	0.271	-0.03	33,443	-0.045	0.5	340,172	0.54	-0.01	12,869	-0.015	0.08	684,735	0.075	0.38	-430,530	0.459	0.81	27	0.933	0.32	-374,099	0.464	0.78	1,455	0.904	0.7594	100	0	819	0.13	4	0.659	0.497	decelerating	0.13	0.93	4	4	23	75	0.648	0.66	0.66	0.659	0.497	264,626	275,746	274,862	11	673	decelerating	-0.34	null	91.92

End of preview. Expand in Data Studio

All Restaurants in Greeley, Colorado, US

Free sample dataset from BeamStation

This dataset provides a complete export of every restaurant operating in Greeley, Colorado, United States. It contains 272 records, each representing a distinct establishment with all available profile columns such as name, address, cuisine type, contact information, and any other attributes supplied by the source. The data is refreshed on a weekly basis, ensuring users have access to the most current listings for analysis or application development.

Researchers studying local food economies, developers building restaurant‑finding tools, municipal planners assessing commercial density, and marketers targeting Greeley’s dining scene will find this collection valuable. Because it includes every licensed eatery in the city, it supports comprehensive surveys, competitive analyses, and service‑area mapping without needing to combine multiple sources.

Access the dataset directly via the provided URL to download the latest weekly export and integrate it into your workflows.

Dataset Details

Field	Value
Full dataset	272 records
Sample size	25 records
Location	Greeley
Category	Restaurants
Updated	weekly
Format	CSV
Columns	beam_id, title, category_main_group, category_sub_group, category, categories, address, street, city, state, ... (484 total)

Column List

#	Column
1	`beam_id`
2	`title`
3	`category_main_group`
4	`category_sub_group`
5	`category`
6	`categories`
7	`address`
8	`street`
9	`city`
10	`state`
11	`borough`
12	`neighborhood`
13	`postal_code`
14	`country`
15	`address_verified`
16	`latitude`
17	`longitude`
18	`timezone`
19	`phone`
20	`price_level`
21	`census_place`
22	`verified_census_city`
23	`beam_location_name`
24	`beam_state_code`
25	`beam_country_code`
26	`website_protocol`
27	`website`
28	`website_normalized`
29	`website_domain`
30	`website_domain_tld`
31	`website_domain_age`
32	`website_domain_registered`
33	`website_domain_expires`
34	`website_domain_registrar`
35	`emails_list`
36	`emails_list_website_domain`
37	`emails_count`
38	`emails_deliverable_count`
39	`emails_risky_count`
40	`description`
41	`rating`
42	`reviews_total_count`
43	`reviews_per_rating`
44	`service_options`
45	`highlights`
46	`popular_for`
47	`accessibility`
48	`offerings`
49	`dining_options`
50	`amenities`
51	`atmosphere`
52	`crowd`
53	`planning`
54	`payments`
55	`children`
56	`has_website`
57	`has_email`
58	`has_social`
59	`has_phone`
60	`socials_count`
61	`social_profile_instagram`
62	`social_username_instagram`
63	`social_profile_facebook`
64	`social_username_facebook`
65	`social_profile_twitter`
66	`social_username_twitter`
67	`social_profile_tiktok`
68	`social_username_tiktok`
69	`social_profile_linkedin`
70	`social_username_linkedin`
71	`social_profile_youtube`
72	`social_username_youtube`
73	`social_profile_github`
74	`social_username_github`
75	`social_profile_snapchat`
76	`social_username_snapchat`
77	`social_profile_pinterest`
78	`social_username_pinterest`
79	`instagram_followers`
80	`instagram_engagement_rate`
81	`instagram_engagement_rate_1m`
82	`instagram_engagement_rate_3m`
83	`instagram_engagement_rate_6m`
84	`instagram_engagement_rate_12m`
85	`instagram_post_count`
86	`first_social_post_days_min`
87	`first_social_post_days_max`
88	`last_social_post_days_min`
89	`last_social_post_days_max`
90	`tiktok_followers`
91	`tiktok_video_count`
92	`tiktok_heart_count`
93	`tiktok_engagement_rate`
94	`tiktok_engagement_rate_1m`
95	`tiktok_engagement_rate_3m`
96	`tiktok_engagement_rate_6m`
97	`tiktok_engagement_rate_12m`
98	`menu_link`
99	`order_links`
100	`reservation_link`
101	`last_updated_at`
102	`beam_cross_social_market_penetration`
103	`beam_cross_velocity_quality`
104	`beam_cross_social_urgency`
105	`beam_cross_per_capita_engagement`
106	`beam_cross_market_saturation_lead`
107	`beam_cross_population_adjusted_rank`
108	`beam_cross_demand_gap_index`
109	`beam_rating_score`
110	`beam_review_confidence`
111	`beam_rating_health`
112	`sentiment_avg`
113	`sentiment_avg_30d`
114	`sentiment_avg_90d`
115	`sentiment_avg_180d`
116	`sentiment_avg_360d`
117	`sentiment_percentile_1km`
118	`sentiment_percentile_5km`
119	`sentiment_percentile_10km`
120	`sentiment_score_90d`
121	`sentiment_score_360d`
122	`sentiment_positive_pct_30d`
123	`sentiment_negative_pct_30d`
124	`sentiment_neutral_pct_30d`
125	`sentiment_positive_pct_90d`
126	`sentiment_negative_pct_90d`
127	`sentiment_neutral_pct_90d`
128	`sentiment_positive_pct_180d`
129	`sentiment_negative_pct_180d`
130	`sentiment_neutral_pct_180d`
131	`sentiment_positive_pct_360d`
132	`sentiment_negative_pct_360d`
133	`sentiment_neutral_pct_360d`
134	`sentiment_trend_30vs90d`
135	`sentiment_trend_90vs360d`
136	`sentiment_diff_30vs90d`
137	`sentiment_change_360d`
138	`sentiment_diff_90vs360d`
139	`sentiment_change_pct_360d`
140	`reviews_count_30d`
141	`reviews_count_90d`
142	`reviews_count_180d`
143	`reviews_count_360d`
144	`beam_score_overall`
145	`beam_popularity_percentile`
146	`beam_social_presence`
147	`beam_data_completeness`
148	`beam_price_value`
149	`beam_data_freshness`
150	`beam_rank_city_category`
151	`beam_rank_city_overall`
152	`beam_rank_city_reviews`
153	`beam_rank_state_category`
154	`beam_rank_state_overall`
155	`beam_rank_state_reviews`
156	`beam_rank_country_category`
157	`beam_rank_country_overall`
158	`beam_rank_country_reviews`
159	`beam_rank_place_global_category`
160	`beam_rank_category`
161	`beam_rank_competition_1km_category`
162	`beam_rank_competition_1km_total`
163	`beam_rank_competition_1km_reviews`
164	`beam_rank_competition_5km_category`
165	`beam_rank_competition_5km_total`
166	`beam_rank_competition_5km_reviews`
167	`beam_rank_competition_10km_category`
168	`beam_rank_competition_10km_total`
169	`beam_rank_competition_10km_reviews`
170	`beam_export_rank`
171	`total_city_category`
172	`total_city`
173	`total_state_category`
174	`total_state`
175	`total_country_category`
176	`total_country`
177	`total_category_global`
178	`beam_competitors_10km_competitive_strength`
179	`beam_competitors_10km_competitor_avg_sentiment_30d`
180	`beam_competitors_10km_competitor_avg_sentiment_90d`
181	`beam_competitors_10km_sentiment_diff_30d`
182	`beam_competitors_10km_sentiment_diff_90d`
183	`beam_competitors_1km_competitive_strength`
184	`beam_competitors_1km_competitor_avg_sentiment_30d`
185	`beam_competitors_1km_competitor_avg_sentiment_90d`
186	`beam_competitors_1km_sentiment_diff_30d`
187	`beam_competitors_1km_sentiment_diff_90d`
188	`beam_competitors_5km_competitive_strength`
189	`beam_competitors_5km_competitor_avg_sentiment_30d`
190	`beam_competitors_5km_competitor_avg_sentiment_90d`
191	`beam_competitors_5km_sentiment_diff_30d`
192	`beam_competitors_5km_sentiment_diff_90d`
193	`beam_competitors_10km_competitor_count`
194	`beam_competitors_1km_competitor_count`
195	`beam_competitors_5km_competitor_count`
196	`beam_competitors_1km_rank_by_score`
197	`beam_competitors_1km_rank_by_rating`
198	`beam_competitors_1km_rank_by_reviews`
199	`beam_competitors_1km_score_percentile`
200	`beam_competitors_1km_rating_percentile`
201	`beam_competitors_1km_reviews_percentile`
202	`beam_competitors_1km_health_percentile`
203	`beam_competitors_1km_sentiment_percentile`
204	`beam_competitors_1km_competitor_avg_score`
205	`beam_competitors_1km_competitor_avg_rating`
206	`beam_competitors_1km_competitor_avg_reviews`
207	`beam_competitors_1km_competitor_avg_health`
208	`beam_competitors_1km_competitor_avg_sentiment`
209	`beam_competitors_1km_score_diff`
210	`beam_competitors_1km_rating_diff`
211	`beam_competitors_1km_reviews_diff`
212	`beam_competitors_1km_health_diff`
213	`beam_competitors_1km_sentiment_diff`
214	`beam_competitors_5km_rank_by_score`
215	`beam_competitors_5km_rank_by_rating`
216	`beam_competitors_5km_rank_by_reviews`
217	`beam_competitors_5km_score_percentile`
218	`beam_competitors_5km_rating_percentile`
219	`beam_competitors_5km_reviews_percentile`
220	`beam_competitors_5km_health_percentile`
221	`beam_competitors_5km_sentiment_percentile`
222	`beam_competitors_5km_competitor_avg_score`
223	`beam_competitors_5km_competitor_avg_rating`
224	`beam_competitors_5km_competitor_avg_reviews`
225	`beam_competitors_5km_competitor_avg_health`
226	`beam_competitors_5km_competitor_avg_sentiment`
227	`beam_competitors_5km_score_diff`
228	`beam_competitors_5km_rating_diff`
229	`beam_competitors_5km_reviews_diff`
230	`beam_competitors_5km_health_diff`
231	`beam_competitors_5km_sentiment_diff`
232	`beam_competitors_10km_rank_by_score`
233	`beam_competitors_10km_rank_by_rating`
234	`beam_competitors_10km_rank_by_reviews`
235	`beam_competitors_10km_score_percentile`
236	`beam_competitors_1km_competitive_tier`
237	`beam_competitors_10km_rating_percentile`
238	`beam_competitors_10km_reviews_percentile`
239	`beam_competitors_10km_health_percentile`
240	`beam_competitors_10km_sentiment_percentile`
241	`beam_competitors_5km_competitive_tier`
242	`beam_competitors_10km_competitor_avg_score`
243	`beam_competitors_10km_competitor_avg_rating`
244	`beam_competitors_10km_competitor_avg_reviews`
245	`beam_competitors_10km_competitor_avg_health`
246	`beam_competitors_10km_competitive_tier`
247	`beam_competitors_10km_competitor_avg_sentiment`
248	`beam_competitors_10km_score_diff`
249	`beam_competitors_10km_rating_diff`
250	`beam_competitors_10km_reviews_diff`
251	`beam_competitors_10km_health_diff`
252	`beam_competitors_10km_sentiment_diff`
253	`beam_competitors_1km_total_in_radius`
254	`beam_competitors_5km_total_in_radius`
255	`beam_competitors_10km_total_in_radius`
256	`beam_competitors_1km_avg_distance_m`
257	`beam_competitors_1km_closest_competitor_m`
258	`beam_competitors_1km_market_type`
259	`beam_competitors_1km_review_share`
260	`beam_competitors_1km_density_per_sqkm`
261	`beam_competitors_1km_tier_below_40`
262	`beam_competitors_1km_tier_40_59`
263	`beam_competitors_1km_tier_60_79`
264	`beam_competitors_1km_tier_80_100`
265	`beam_competitors_5km_avg_distance_m`
266	`beam_competitors_5km_closest_competitor_m`
267	`beam_competitors_5km_market_type`
268	`beam_competitors_5km_review_share`
269	`beam_competitors_5km_density_per_sqkm`
270	`beam_competitors_5km_tier_below_40`
271	`beam_competitors_5km_tier_40_59`
272	`beam_competitors_5km_tier_60_79`
273	`beam_competitors_5km_tier_80_100`
274	`beam_competitors_10km_avg_distance_m`
275	`beam_competitors_10km_closest_competitor_m`
276	`beam_competitors_10km_market_type`
277	`beam_competitors_10km_review_share`
278	`beam_competitors_10km_density_per_sqkm`
279	`beam_competitors_10km_tier_below_40`
280	`beam_competitors_10km_tier_40_59`
281	`beam_competitors_10km_tier_60_79`
282	`beam_competitors_10km_tier_80_100`
283	`beam_competitors_city_competitor_avg_sentiment_30d`
284	`beam_competitors_city_competitor_avg_sentiment_90d`
285	`beam_competitors_city_sentiment_diff_30d`
286	`beam_competitors_city_sentiment_diff_90d`
287	`beam_competitors_city_competitor_count`
288	`beam_competitors_city_total_in_city`
289	`beam_competitors_city_rank_by_score`
290	`beam_competitors_city_rank_by_rating`
291	`beam_competitors_city_rank_by_reviews`
292	`beam_competitors_city_score_percentile`
293	`beam_competitors_city_rating_percentile`
294	`beam_competitors_city_reviews_percentile`
295	`beam_competitors_city_health_percentile`
296	`beam_competitors_city_sentiment_percentile`
297	`beam_competitors_city_competitor_avg_score`
298	`beam_competitors_city_competitor_avg_rating`
299	`beam_competitors_city_competitor_avg_reviews`
300	`beam_competitors_city_competitor_avg_health`
301	`beam_competitors_city_competitor_avg_sentiment`
302	`beam_competitors_city_score_diff`
303	`beam_competitors_city_rating_diff`
304	`beam_competitors_city_reviews_diff`
305	`beam_competitors_city_health_diff`
306	`beam_competitors_city_sentiment_diff`
307	`beam_competitors_city_market_type`
308	`beam_competitors_city_review_share`
309	`beam_competitors_city_density_per_sqkm`
310	`beam_competitors_city_tier_below_40`
311	`beam_competitors_city_tier_40_59`
312	`beam_competitors_city_tier_60_79`
313	`beam_competitors_city_tier_80_100`
314	`beam_competitors_city_competitive_strength`
315	`beam_competitors_city_underserved_score`
316	`beam_competitors_city_competition_intensity`
317	`beam_competitors_state_competitor_avg_sentiment_30d`
318	`beam_competitors_state_competitor_avg_sentiment_90d`
319	`beam_competitors_state_sentiment_diff_30d`
320	`beam_competitors_state_sentiment_diff_90d`
321	`beam_competitors_state_competitor_count`
322	`beam_competitors_state_total_in_state`
323	`beam_competitors_state_rank_by_score`
324	`beam_competitors_state_rank_by_rating`
325	`beam_competitors_state_rank_by_reviews`
326	`beam_competitors_state_score_percentile`
327	`beam_competitors_state_rating_percentile`
328	`beam_competitors_state_reviews_percentile`
329	`beam_competitors_state_health_percentile`
330	`beam_competitors_state_sentiment_percentile`
331	`beam_competitors_state_competitor_avg_score`
332	`beam_competitors_state_competitor_avg_rating`
333	`beam_competitors_state_competitor_avg_reviews`
334	`beam_competitors_state_competitor_avg_health`
335	`beam_competitors_state_competitor_avg_sentiment`
336	`beam_competitors_state_score_diff`
337	`beam_competitors_state_rating_diff`
338	`beam_competitors_state_reviews_diff`
339	`beam_competitors_state_health_diff`
340	`beam_competitors_state_sentiment_diff`
341	`beam_competitors_state_market_type`
342	`beam_competitors_state_review_share`
343	`beam_competitors_state_density_per_sqkm`
344	`beam_competitors_state_underserved_score`
345	`beam_competitors_state_competition_intensity`
346	`beam_competitors_state_competitive_strength`
347	`beam_competitors_country_competitor_avg_sentiment_30d`
348	`beam_competitors_country_competitor_avg_sentiment_90d`
349	`beam_competitors_country_sentiment_diff_30d`
350	`beam_competitors_country_sentiment_diff_90d`
351	`beam_competitors_country_competitor_count`
352	`beam_competitors_country_competitor_avg_score`
353	`beam_competitors_country_competitor_avg_rating`
354	`beam_competitors_country_competitor_avg_reviews`
355	`beam_competitors_country_competitor_avg_health`
356	`beam_competitors_country_competitor_avg_sentiment`
357	`beam_competitors_country_score_diff`
358	`beam_competitors_country_rating_diff`
359	`beam_competitors_country_reviews_diff`
360	`beam_competitors_country_sentiment_diff`
361	`beam_competitors_country_score_percentile`
362	`beam_competitors_country_rating_percentile`
363	`beam_competitors_country_reviews_percentile`
364	`beam_competitors_country_health_percentile`
365	`beam_competitors_country_sentiment_percentile`
366	`beam_competitors_country_rank_by_score`
367	`beam_competitors_country_competitive_strength`
368	`beam_competitors_country_health_diff`
369	`beam_competitors_country_rank_by_rating`
370	`beam_competitors_country_rank_by_reviews`
371	`beam_competitors_country_tier_40_59`
372	`beam_competitors_country_tier_60_79`
373	`beam_competitors_country_tier_80_100`
374	`beam_competitors_country_tier_below_40`
375	`beam_competitors_country_total_in_country`
376	`beam_competitors_city_siblings_competitor_count`
377	`beam_competitors_city_siblings_competitor_avg_score`
378	`beam_competitors_city_siblings_competitor_avg_rating`
379	`beam_competitors_city_siblings_competitor_avg_reviews`
380	`beam_competitors_city_siblings_competitor_avg_health`
381	`beam_competitors_city_siblings_competitor_avg_sentiment`
382	`beam_competitors_city_siblings_score_diff`
383	`beam_competitors_city_siblings_rating_diff`
384	`beam_competitors_city_siblings_reviews_diff`
385	`beam_competitors_city_siblings_sentiment_diff`
386	`beam_competitors_city_siblings_score_percentile`
387	`beam_competitors_city_siblings_rating_percentile`
388	`beam_competitors_city_siblings_reviews_percentile`
389	`beam_competitors_city_siblings_health_percentile`
390	`beam_competitors_city_siblings_sentiment_percentile`
391	`beam_competitors_city_siblings_rank_by_score`
392	`beam_competitors_city_siblings_competitor_avg_recommend_pct`
393	`beam_competitors_city_siblings_recommend_pct_diff`
394	`beam_competitors_city_siblings_recommend_pct_percentile`
395	`beam_competitors_city_siblings_total_siblings`
396	`beam_competitors_city_businesses_per_10k_pop`
397	`beam_competitors_city_population_per_business`
398	`beam_competitors_city_population_density`
399	`beam_competitors_city_reviews_per_capita`
400	`beam_competitors_city_reviews_per_10k_pop`
401	`beam_competitors_state_businesses_per_10k_pop`
402	`beam_competitors_state_population_per_business`
403	`beam_competitors_state_population_density`
404	`beam_competitors_state_reviews_per_capita`
405	`beam_competitors_state_reviews_per_10k_pop`
406	`beam_competitors_1km_hhi_contribution`
407	`beam_competitors_1km_hhi_minimum`
408	`beam_competitors_5km_hhi_contribution`
409	`beam_competitors_5km_hhi_minimum`
410	`beam_competitors_10km_hhi_contribution`
411	`beam_competitors_10km_hhi_minimum`
412	`beam_competitors_city_hhi_contribution`
413	`beam_competitors_city_hhi_minimum`
414	`beam_competitors_state_hhi_contribution`
415	`beam_competitors_state_hhi_minimum`
416	`beam_trends_score_30d_beam_score_overall`
417	`beam_trends_score_30d_rating`
418	`beam_trends_score_30d_review_count`
419	`beam_trends_score_30d_beam_rating_health`
420	`beam_trends_score_30d_beam_popularity_percentile`
421	`beam_trends_score_90d_beam_score_overall`
422	`beam_trends_score_90d_rating`
423	`beam_trends_score_90d_review_count`
424	`beam_trends_score_90d_beam_rating_health`
425	`beam_trends_score_90d_beam_popularity_percentile`
426	`beam_trends_competitive_1km_30d_strength_change`
427	`beam_trends_competitive_1km_30d_rank_change`
428	`beam_trends_competitive_1km_30d_percentile_change`
429	`beam_trends_competitive_1km_90d_strength_change`
430	`beam_trends_competitive_1km_90d_rank_change`
431	`beam_trends_competitive_1km_90d_percentile_change`
432	`beam_trends_competitive_5km_30d_strength_change`
433	`beam_trends_competitive_5km_30d_rank_change`
434	`beam_trends_competitive_5km_30d_percentile_change`
435	`beam_trends_competitive_5km_90d_strength_change`
436	`beam_trends_competitive_5km_90d_rank_change`
437	`beam_trends_competitive_5km_90d_percentile_change`
438	`beam_trends_competitive_10km_30d_strength_change`
439	`beam_trends_competitive_10km_30d_rank_change`
440	`beam_trends_competitive_10km_30d_percentile_change`
441	`beam_trends_competitive_10km_90d_strength_change`
442	`beam_trends_competitive_10km_90d_rank_change`
443	`beam_trends_competitive_10km_90d_percentile_change`
444	`beam_trends_competitive_city_30d_strength_change`
445	`beam_trends_competitive_city_30d_rank_change`
446	`beam_trends_competitive_city_30d_percentile_change`
447	`beam_trends_competitive_city_90d_strength_change`
448	`beam_trends_competitive_city_90d_rank_change`
449	`beam_trends_competitive_city_90d_percentile_change`
450	`beam_trends_competitive_state_30d_strength_change`
451	`beam_trends_competitive_state_30d_rank_change`
452	`beam_trends_competitive_state_30d_percentile_change`
453	`beam_trends_competitive_state_90d_strength_change`
454	`beam_trends_competitive_state_90d_rank_change`
455	`beam_trends_competitive_state_90d_percentile_change`
456	`beam_trends_sentiment_current_sentiment`
457	`beam_trends_sentiment_positive_ratio`
458	`beam_trends_sentiment_negative_ratio`
459	`beam_trends_sentiment_review_count`
460	`beam_trends_velocity_reviews_per_day`
461	`beam_trends_velocity_reviews_per_month`
462	`beam_trends_velocity_percentile_city`
463	`beam_trends_velocity_percentile_state`
464	`beam_trends_velocity_trend`
465	`beam_velocity_reviews_per_day`
466	`beam_velocity_reviews_per_week`
467	`beam_velocity_reviews_per_month`
468	`beam_velocity_reviews_last_30d`
469	`beam_velocity_reviews_last_90d`
470	`beam_velocity_reviews_last_365d`
471	`beam_velocity_percentile_1km`
472	`beam_velocity_percentile_5km`
473	`beam_velocity_percentile_10km`
474	`beam_velocity_percentile_city`
475	`beam_velocity_percentile_state`
476	`beam_velocity_rank_1km`
477	`beam_velocity_rank_5km`
478	`beam_velocity_rank_10km`
479	`beam_velocity_rank_city`
480	`beam_velocity_rank_state`
481	`beam_velocity_trend`
482	`beam_velocity_change_30d`
483	`beam_velocity_change_90d`
484	`beam_trends_sentiment_recommend_pct`

Usage

from datasets import load_dataset
ds = load_dataset("beamstation/all-restaurants-in-greeley-colorado-us-109907")

Get the Full Dataset

This is a free sample with masked email and phone data. The full dataset with 272 records and unmasked contact data is available at:

All Restaurants in Greeley, Colorado, US on BeamStation

License

This sample is provided for evaluation purposes under the BeamStation Terms of Service.

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