big-tall.com
Big-tall.com is an e-commerce platform catering specifically to individuals of larger stature. The website offers a wide range of clothing, footwear, and accessories that are specifically designed to accommodate the needs and preferences of big and tall individuals. It provides a convenient online shopping experience for customers looking for fashionable, well-fitting options.
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big-tall.com's revenueOVER TIME
Over the past three months, big-tall.com revenue has experienced decline of 37%, compared to the preceding three months.
big-tall.com competitors
In July 2025, big-tall.com generated $7,154 in revenue from 37 transactions with 3,431 sessions, boasting an average order value (AOV) of $175-200 and a conversion rate of 1.00-1.50%. In comparison, dickanthonyltd.com had revenue of $5,477 from 60 transactions and 1,968 sessions, with an AOV of $75-100 and a higher conversion rate of 3.00-3.50%. jackvictor.com outperformed big-tall.com significantly with revenue of $69,456 from 153 transactions and 13,640 sessions, featuring an AOV of $450-475 but a similar conversion rate of 1.00-1.50%. muldoons.com, bigandtallmart.com, and westportbigandtall.com also had higher revenues, transactions, sessions, and AOV compared to big-tall.com, with varying conversion rates. Despite strong competition, big-tall.com holds its ground with a decent revenue and conversion rate in the big and tall clothing market.
Revenue share by device at big-tall.com
In July large majority of sales on big-tall.com, 65% was finalized on mobile devices (mobile web only, excluding app usage, if relevant), with 35% of sales coming from desktop devices.
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big-tall.com channels
Identify top traffic channels that drive growth for big-tall.comand discover how performance of traffic channels has changed over time.
big-tall.com Google Ads spend
Evaluate big-tall.com's Google search ad spend, ad clicks and cost-per-click. Review performance over time and gain deeper view into their ad campaign spend.
big-tall.com devices
Review big-tall.com's performance across desktop and mobile devices. Analyze how revenue, conversion rate, transactions, AOV and sessions vary depending on the device shoppers use.
