Automated techhology
Automated techhology
Established in 2001, we only work recovering Walmart deductions. During that time, we have built substantial expertise and relationships that enable us to recover more >>> faster than internal teams or our competitors.
INCREASED APPROVAL PERCENTAGE
Our unique tailored service results in higher approval rating, we average returns totalling 80% of our ask vs. typical approval rates being as low as 40%.
INCREASED APPROVAL TIMES
Our unique escalation paths ensure the time taken from our initial aks to money in your bank is reduced to an average of 4 weeks,vs. up to 6 months experienced by some of our clients before they engaged with us.
REDUCED EFFORT
We handle all the heavy lifting to free up your internal resources, allowing your team to focus on more valuable tasks instead of repetitive work. We implement our unique automation solutions where applicable and utilize cost-effective university students to manage the heavy lifting. This combined resource approach enables us to remain uniquely flexible and tailored in our recovery strategy.
We offer a free, no-obligation size of prize analysis. Discover how much more money we could recover for you.
We utilize our unique technology solution to automate the identification of invalid deductions. Our experts fine-tune and build the recovery strategy. We recover funds through a combination of conventional and unconventional processes. This flexible approach allows us to recover more >>> faster
We handle all the heavy lifting for you, including gathering evidence to support your claim, developing tickets, and offering negotiation assistance. Our focus is on providing you with the information you need to provide management oversight without getting involved in the finer details. We send you weekly reports and engage with you only on key decision points.
Copyright © 2024 Retail Recovered - All Rights Reserved.
We use cookies to analyze website traffic and optimize your website experience. By accepting our use of cookies, your data will be aggregated with all other user data.