Coverbild der Sendung The Returns Management Podcast by ReturnLogic

The Returns Management Podcast by ReturnLogic

Podcast von ReturnLogic

Englisch

Business

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Mehr The Returns Management Podcast by ReturnLogic

ReturnLogic is a returns management platform for scaling ecommerce brands. On this channel, we'll discuss the latest retail trends, technology, and best practices for managing an ecommerce business and retail returns. We'll connect with ecommerce store owners, partners, and thought leaders within the vast online shopping ecosystem. Listen in as we uncover how retailers can manage and optimize their returns strategy, saving time, and labor, and ultimately increase customer loyalty and lifetime value.

Alle Folgen

13 Folgen

Episode ReturnAlytics Episode 10 | What is Bracketing and How Can You Manage Serial Returners? Cover

ReturnAlytics Episode 10 | What is Bracketing and How Can You Manage Serial Returners?

2020 changed how people shop. With more and more people turning to online shopping, finding the right size, fit, color, etc. became a lot more challenging and retailers had to find creative ways to adapt. So they started offering things like free return shipping to everyone. This lead to bracketing and other practices that may be convenient for shoppers but can negatively impact a retailer's bottom line. So who is considered a serial returner? Well, it could just be a customer who returns what a company deems to be excessive amounts. However, if retailers start banning shoppers left and right who return items, there are going to be some serious consequences. So what can you do about serial returners / bracketers? Find out on today's episode!

24. Jan. 2023 - 15 min
Episode ReturnAlytics Episode 9 | What Happens After Black Friday / Cyber Monday? Cover

ReturnAlytics Episode 9 | What Happens After Black Friday / Cyber Monday?

Sales aren't the only thing retailers need to be worried about this holiday season. Shoppers are projected to return $900 Billion worth of goods by the end of 2022 with online shoppers making up $280 billion of that – about a 9% uptick from last year. On Average, retailers get 4x as many orders from November 25th to December 25th and about 80% of their returns happen right after that time period as well. There's not much time left to prepare for the post Black Friday / Cyber Monday returns. Due to inflation, higher cost of living, highest ever cost of shipping, a lot of heavy discounting to move inventory, etc, this year will probably be a record-setting year for returns. But don't worry, there's still hope!  Learn how you can prepare for the rush of holiday returns on today's episode. Enjoy!

9. Dez. 2022 - 9 min
Episode ReturnAlytics Episode 8 | What is Returns Optimization and How Can You Optimize Your Returns Process? Cover

ReturnAlytics Episode 8 | What is Returns Optimization and How Can You Optimize Your Returns Process?

Returns Optimization is defined as 'continuous improvement strategies that use returns data to improve the shopper experience, improve operational efficiency, and grow profits'. Put another way, returns optimization focuses on improving the returns process for retailers, reducing return rates from shoppers, streamlining operations and increasing customers' lifetime value. Returns optimization is fueled by returns data. Returns data unlocks powerful insight for retailers that allows them to see where things are going wrong in their returns process so that they can make the right adjustments to fix them.  Without returns data, merchants can't see the full picture of their reverse supply chain and won't have the depth of information on their products or shoppers to keep growing. Listen in to learn how you can use Returns Optimization to fuel your business and take your shopping experience to the next level.

16. Nov. 2022 - 13 min
Super gut, sehr abwechslungsreich Podimo kann man nur weiterempfehlen
Super gut, sehr abwechslungsreich Podimo kann man nur weiterempfehlen
Ich liebe Podcasts, Hörbücher u. -spiele, Dokus usw. Hier habe ich genügend Auswahl. Macht 👍 weiter so

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