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Vinkal Chadha
Managing Partner, Global Business Development
Search among the top café & restaurant brands by number of locations
Join us for a demo where we'll discuss how Realytics can support your business growth and adaptability in changing market conditions
Managing Partner, Global Business Development
Search among the top 10,053 café & restaurant brands by number of locations
Search among the top café & restaurant brands by number of locations
In Cafe & Restaurants
·May – Jul 25
Sizzler is in the top 1% of brands
Sample of brands in the same percentile
See what factors influence Sizzler performance in the Thailand and how they change over time
See what factors influence Sizzler performance in the Thailand and how they change over time
Available by subscription
Available by subscription
An analysis of Sizzler' competitors in the Thailand
An analysis of Sizzler' competitors in the Thailand
Top-5 brands that brand's customers also visit
Discover your traffic workload during different times of the day
Join us for a demo where we'll discuss how Realytics can support your business growth and adaptability in changing market conditions
Managing Partner, Global Business Development
In Cafe & Restaurants
In Cafe & Restaurants
Search among the top 10,053 café & restaurant brands by number of locations
Cafe & Restaurants
Market share reflects brand strength and customer preference, crucial for gauging competitive success and growth potential in the industry.
Sizzler's market performance in Thailand is leading, holding the 99th percentile. This signifies a very strong market position, placing it among the top brands in the Cafe & Restaurants industry. The performance peers include multiple brands holding the same percentile.
Customer satisfaction indicates brand loyalty and service quality, directly impacting repeat business and positive word-of-mouth referrals.
Sizzler's overall customer satisfaction in Thailand is 57%, a decrease of 12.1 percentage points year-over-year. Satisfaction varies by location, with Songkhla Province at 89% and Chon Buri Province at 73%. Recent months show fluctuation, peaking in June. Attention is needed to address declining satisfaction.
Average check reflects customer spending habits and menu pricing power, essential for revenue optimization and profitability analysis.
The overall average check for Sizzler in Thailand is 467.8 THB, up 1.9% year-over-year. Phuket Province has the highest average check at 718.2 THB, while Chiang Mai Province has the lowest at 378.8 THB. Average check fluctuated between April and June 2025.
Outlet count indicates brand reach and market penetration, affecting accessibility and overall revenue generation across regions.
Sizzler has outlets in multiple provinces in Thailand. Chon Buri Province leads with 3 outlets. Several other provinces including Surat Thani, Chiang Mai, and Rayong have 2 outlets each. The remaining provinces each have 1 outlet.
Identifying top competitors is key for strategic positioning, highlighting competitive threats and opportunities for differentiation.
Sizzler's top competitors in Thailand, based on customer cross-visitation, are McDonald's (6.53%), Café Amazon (6.25%), Starbucks (5.68%), KFC (5.40%), and Burger King (3.98%). This data reveals the alternative dining choices of Sizzler's customer base.
Understanding traffic patterns helps optimize staffing and resource allocation, ensuring efficient service during peak hours.
Sizzler's peak traffic workload in Thailand occurs between 17:00 and 19:00 (5 PM - 7 PM), reaching a high of 73.77. Traffic is minimal from midnight to 9:00 AM. This data informs staffing and promotional strategies to manage workload effectively during peak times.
Consumer insights enable targeted marketing, maximizing engagement and relevance by tailoring strategies to specific demographics.
Sizzler's customer base shows a higher affinity towards women (72%) compared to men (115%). Among generations, Gen X is overrepresented (144%), while Gen Y (92%) and Gen Z (73%) are underrepresented. This suggests targeted marketing should consider gender and generational preferences to optimize engagement.