
Trove
The world’s most innovative brands trust Trove to run their resale platforms.
Date | Investors | Amount | Round |
---|---|---|---|
- | investor investor investor investor investor investor investor investor | €0.0 | round |
N/A | €0.0 | round | |
investor investor | €0.0 | round | |
investor investor investor investor investor investor | €0.0 | round | |
investor | €0.0 | round | |
investor investor investor investor investor | €0.0 | round | |
investor investor investor investor investor | €0.0 | round | |
* | $30.0m Valuation: $388m | Series E | |
Total Funding | 000k |

USD | 2019 | 2020 | 2021 | 2023 |
---|---|---|---|---|
Revenues | 0000 | 0000 | 0000 | 0000 |
% growth | - | 120 % | 98 % | - |
EBITDA | 0000 | 0000 | 0000 | 0000 |
Profit | 0000 | 0000 | 0000 | 0000 |
EV | 0000 | 0000 | 0000 | 0000 |
EV / revenue | 00.0x | 00.0x | 00.0x | 00.0x |
EV / EBITDA | 00.0x | 00.0x | 00.0x | 00.0x |
R&D budget | 0000 | 0000 | 0000 | 0000 |
Source: Dealroom estimates
Related Content
Trove.co is a technology company that provides brands with the tools to operate their own resale platforms. The company operates in the growing market of second-hand retail, serving brands that want to tap into the increasing consumer demand for pre-owned items. Trove's technology uses computer vision and machine learning algorithms to identify, price, and relist items, ensuring they are resold at their maximum value. This helps brands maintain customer loyalty and increase customer lifetime value by offering a trade-in option for used items.
Trove's business model involves providing brands with a composable, branded resale storefront that can be integrated with their existing channels. This allows brands to offer a seamless customer journey, from purchasing new items to trading in used ones. Brands can offer store credit for traded-in items, which encourages customers to continue shopping with them. This model has proven successful, with online inventory typically selling within one week.
Trove's technology has been adopted by several high-profile brands, including Arc’teryx, Patagonia, and lululemon. These brands have reported that the addition of a used gear option has allowed them to reach a new audience, indicating the potential for growth in the second-hand retail market.
Keywords: Resale, Technology, Brands, Second-hand Retail, Trade-in, Customer Loyalty, Store Credit, Computer Vision, Machine Learning, Seamless Customer Journey.
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Investments by Trove
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