dear-lover.com
Dear-lover.com is an online platform offering a wide range of products such as womens clothing, lingerie, swimwear, and accessories. The website accommodates various styles and sizes, aiming to provide fashionable and affordable options for customers. It also features a user-friendly interface and convenient shipping and return policies.
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dear-lover.com's revenueOVER TIME
Over the past three months, dear-lover.com revenue has experienced decline of 12%, compared to the preceding three months.
dear-lover.com competitors
In July 2025, dear-lover.com had a revenue of $490,987 with 2,667 transactions and 542,349 sessions. Their average order value (AOV) ranged from $175 to $200, with a conversion rate of 0.00% to 0.50%. Comparing this data to its competitors, goodstuffapparel.com had a revenue of $5,992 with 28 transactions and 1,591 sessions, offering a higher AOV of $200 to $225 and a conversion rate of 1.50% to 2.00%. wholesale7.net performed better than dear-lover.com with a revenue of $121,840, 588 transactions, and 60,718 sessions, while maintaining a similar AOV and conversion rate. lovelywholesale.com and wholesalefashionsquare.com also showed strong performances compared to dear-lover.com in terms of revenue, transactions, and conversion rates. Overall, dear-lover.com may need to improve its conversion rate to stay competitive in the market.
Revenue share by device at dear-lover.com
In July large majority of sales on dear-lover.com, 70% was finalized on desktop devices, with 30% of sales coming from mobile devices (mobile web only, excluding app usage, if relevant).
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dear-lover.com channels
Identify top traffic channels that drive growth for dear-lover.comand discover how performance of traffic channels has changed over time.
dear-lover.com Google Ads spend
Evaluate dear-lover.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.
dear-lover.com devices
Review dear-lover.com's performance across desktop and mobile devices. Analyze how revenue, conversion rate, transactions, AOV and sessions vary depending on the device shoppers use.
