If that sentence sounds reasonable to you, you’re in good company. Most enterprise retailers believe deploying your returns portal is the eCommerce equivalent of crossing the finish line. The label in the box is gone. Customers can self-serve. Your friends are waiting with a big self-painted “CONGRATS YOU MADE IT”-sign. Done.

The reality is different. Having a portal might be your first 5k. But the biggest savings – and the biggest CX wins – live in your city’s local half-marathon. However, contrary to marathon training, there’s no TikTok community that will tell you the right methodology for getting there. After setting up their portal, many retailers lack a structured process for discovering what’s actually broken, department by department, and solving it in the right order.

Meet the expert who’s been inside the machine

Thomas Wagener is our Product Owner for Returns at parcelLab. Not only has he been at the company for nearly six years, but he has also built the returns product from the ground up. Tom has been embedded in enterprise returns implementations with retailers like Dyson, Emma Mattress, Bestseller, and Conrad, across multiple markets and geographies. If you want to train for that returns marathon, Thomas is your ideal coach.

One pattern he sees constantly: companies approach him asking for a specific button or feature. His first question is always the same – “What problem are you trying to solve?” The answer usually reveals a completely different solution than the one they requested.

The real problem: Features first, questions never

Here’s how most companies approach returns optimization: They decide it’s time to improve things, list the features their return portal should have, configure them, launch, and close the project.

What’s missing from that sequence is the most valuable step: nobody sat down with each department to ask what their actual pain points are. Inbound logistics has different problems than customer service. Product teams have different data needs than the web team. Fraud has different priorities than CX. But these insights only surface through structured conversations – not through a requirements document.

When Tom asks stakeholders directly what they need, the answers are always more diverse and valuable than any feature list would suggest. Skip this step, and you solve the wrong problems, you miss the highest-ROI opportunities, and you leave departments silently absorbing costs that the returns portal could have eliminated.

The stakeholder audit: ask before you build

Tom’s methodology starts not with configuration but with a single question, posed to each department separately: “What is your biggest pain point around returns?”

Then you quantify, prioritize, and solve – largest financial impact first.

Why this matters becomes clear through a real example. One retailer explained that whenever a customer had a warranty issue, they called customer service, get told to send an email with photos and a description, and then wait for a response. Three touchpoints for one process.

“You had a warranty issue. You needed to call them. When you called them, they told you that you need to write us an email and send pictures and a description of what’s wrong. And then we will let you know how we proceed. So that’s three touch points for one process. Times five euros, whatever, right? We gather that in the first place. So you took two contact points out.”

That warranty flow was costing roughly €15 per case. But it was invisible to anyone not sitting in customer service. The portal consolidated it into one interaction. The optimization only happened because someone asked the right question.

And this isn’t a one-time exercise. Tom treats it as a recurring discovery loop. New pain points surface all the time as the business changes, as volumes shift, and as regulations evolve.

The four-department returns audit

What follows is a step-by-step playbook for discovering and solving your biggest returns pain points. Each section represents one department. For each, we’re covering what to ask, what you’ll typically find, a real use case, and the ROI signal.

Department 1: Inbound logistics and warehouse

What to ask your warehouse team: Where do you lose the most time processing returns? What manual steps could be eliminated? To plan better in the future, what information would you need in advance?

What you’ll typically find: Manual data entry is eating hours. Warehouse workers are typing in order numbers and item conditions by hand when barcode scanning with pre-populated portal data could handle it. There’s no advance visibility into incoming return volumes, which makes staffing optimization impossible. Routing is confused – damaged goods, open-box items, and resellable products all go to the same intake point instead of being pre-sorted.

The math on this is simple, and Tom has seen it play out at scale with a large global retailer.

“If you save five seconds per return, they could save three people. So those people are probably not the most expensive people, but it still might be 50K a year for three people. At least even in Poland. So the ROI is real.”

Barcode scanning with pre-populated data replaced manual entry. Five seconds saved per return. At the brand’s volumes, that could translate to three full-time warehouse positions – roughly €50,000 per year. An additional lever that benefits the brand is return volume forecasts which are typically available 24 hours ahead. This enables warehouse managers to shift staffing to match incoming loads.

Your ROI signal: If your warehouse team is manually entering return data, multiply five seconds by your daily return volume by your hourly labor cost. That’s your baseline savings – before any routing or forecasting optimization.

Department 2: Product and merchandising

What to ask your product team: What returns data do you currently receive? How granular is it? How long does it take to reach you? What would you do differently if you had better data?

What you’ll typically find: Return reasons are captured at the wrong level of granularity. “Too small” tells you almost nothing. “Too short,” “too tight,” or “wrong cut” tells you exactly what to fix. But most portals still use the same flat dropdown for shoes, electronics, and furniture – as if “too small” means the same thing for a pair of sneakers and a bookshelf.

The digital returns portal can ask follow-up questions that a paper form never could. “Too small” becomes “In what way? Is it short? Too tight? Wrong cut?” This feeds directly into product description optimization, sizing guide improvements, and potentially design changes. Category-specific questions matter enormously when finding out what the product team actually wants to know.

“Ask product-specific or category-specific questions. […] I would go to the people who work with the online store. What information will help you? How do you need that? So you can improve the descriptions to get returns down. Identify which are the most critical items and do short term advances.”

The timing dimension is equally critical. Tom mentions a large global brand, where returns data was taking half a year to reach product teams. That means corrective action on product descriptions or sizing guides lagged by two full collection cycles. If product teams are getting actionable return data in real time instead of six months later, they can adjust descriptions, add size recommendations, or flag problematic SKUs within the current season – not two seasons too late.

Your ROI signal: Ask your product team how long it takes to receive returns data today. Every month of delay is a month of preventable returns on products with known issues.

Department 3: Customer service

What to ask your CS team: What are the most common return-related requests you handle? How are they categorized? Which ones are repetitive and low-decision? Which ones require judgment?

What you’ll typically find: A high volume of repetitive, rule-based tasks: issuing labels, explaining return policies, confirming receipt. Those could easily be fully self-served through the portal. Warranty and claims cases that require multi-step back-and-forth can often be consolidated into a single portal interaction.

There’s a lack of segmentation: loyal customers and first-time buyers go through the exact same process. And during peak season, the approval queue becomes a bottleneck that can’t be adjusted dynamically.

Here’s an example from a parcelLab customer’s warranty flow that shows how dramatic the impact can be.

→ Before: the customer calls (touchpoint one, roughly €5-8), gets told to email photos (touchpoint two, roughly €5-8), and waits for a response (touchpoint three, roughly €5-8). Total: approximately €15-24 per warranty case.
→ After: the portal collects photos, description, and customer declaration in one step. It opens a pre-filled ticket for the CS agent, who has everything needed to make a decision immediately. Two touchpoints eliminated.

Then there’s the organizational complexity. At a large U.S. retailer, an internal conflict broke out between the fraud team and customer service over missing package claims. Fraud needed a signed declaration form. CS protested that the form would increase customer effort and drive up call volume. The platform resolved the conflict. The portal collects the declaration digitally, eliminating the phone call entirely and ensuring the fraud department gets what they need. CS gets fewer contacts. Both departments win.

There’s also a dynamic lever that most companies overlook: approval thresholds can be adjusted by season, risk level, and customer segment. Tom describes it plainly:

“We can segment and say, 50% need to go into approval and 50% do not. And if you want to flip that number to ‘nobody goes into approval because it’s peak season’, then you can just flip the number, right? That’s continuous optimization based on what season you’re in and what you want to do.”

Retailers achieve this level of flexibility by using a platform designed for it.

Department 4: Web, shop, CRM, and commercial teams

What to ask your CRM and commercial teams: How do you currently use post-purchase touchpoints? Are returns integrated into your loyalty or CRM strategy? Do you use return-to-store? Are you tracking which return experiences drive or kill repeat purchases?

What you’ll typically find: Returns exist as a separate silo, disconnected from the CRM and loyalty program. There’s no differentiated treatment based on customer value or history. Return-to-store isn’t offered or incentivized, missing a direct revenue rescue opportunity. At the same time, gift card or store credit options are underused, so there is no top-up incentive to keep revenue in-house.

“You want to make it convenient to the customer. […] If you have stores, you should tell them: Hey, drop it off in store – that’s how you can make revenue because people tend to spend more money if they’re getting to the store.”

In-store drop-off is a revenue lever that’s easy to miss. Redirecting returns to stores rescues revenue that would otherwise be pure loss.

Gift card returns with a top-up bonus – say, the return value plus 10% store credit – keep money in the ecosystem. This is a CRM play, not a logistics play. But it only works if the returns platform actually integrates with the CRM.

Segmentation logic follows the same principle: loyal members get faster refunds, no return fees, and no signature required for claims. First-time buyers or flagged accounts go through standard or enhanced verification. In simple terms, it’s the café owner who lets a regular customer pay tomorrow when they forget their wallet. That level of trust, at scale, is what CRM-integrated returns enable.

Your ROI signal: What percentage of your returns currently result in a full cash refund vs. store credit or exchange? Every percentage point shifted toward store credit or exchange is retained revenue.

In our blog, you can find more basics on how top retailers manage returns.

What changes when you run the audit

Retailers who follow this methodology unlock a fundamentally different operating model.

• Warehouse efficiency gains compound at volume. Seconds saved per return translate into FTEs. This scales with every market and warehouse you operate.
• Customer service deflection is where the numbers get large fast. Warranty, claims and troubleshooting flows consolidated into self-service. At enterprise volumes, this could reach six figures annually.
• Product improvement velocity accelerates dramatically. Return reason data reaches product teams in real time instead of months later – enabling in-season corrections instead of next-season fixes.
• Revenue rescue becomes systematic. Return-to-store programs, gift card top-ups, and “keep the item” logic for cases when return shipping exceeds product value keep money in the ecosystem instead of watching it walk out.
• Organizational clarity replaces fragmentation. You get one owner, one system, and one feedback loop. Departments stop optimizing in isolation and start building a shared returns infrastructure.

Two use cases show what becomes possible once the audit reveals the real opportunities.

At Emma Mattress, a customer could return a mattress for being “too hard.” Instead of processing a return – expensive, given the bulky item, special logistics, cleaning, and resale uncertainty – CS calls and offers a free topper. If the customer accepts, no return happens. The cost of a topper is a fraction of the cost of a mattress return. The revenue saved per case far exceeds the intervention cost. The most valuable optimization here isn’t faster returns. It’s fewer returns through smarter intervention.

At Dyson, damaged batteries cannot legally be shipped via standard parcel. Before integration, these cases were likely handled ad hoc or ignored entirely. Now the portal identifies damaged-battery returns and routes them automatically to specialist hazardous-goods carriers. That process exists because someone asked: “What edge cases are costing you the most?”

Where this goes next

The methodology is deliberately low-tech at the start. Begin with structured conversations across four departments. Ask one key question in each and prioritize the outcomes by financial impact. No new software required for step one.

The mindset it demands, though, is not low-effort. This is not a quarterly project. It’s a continuous optimization loop. The companies extracting the most value from their returns infrastructure are the ones who never stop asking, “What’s your biggest pain point?”

Tom sees the space moving toward automated, CRM-driven decision-making:

“The future – what I really believe – is not just about segmentation. It’s also gonna be about automatic decision for certain things. Customers will bring their CRM data in. […] There’s going to be way more automation triggered by the returns portal based on customer data.”

Customer data will trigger dynamic approval thresholds – auto-approve for green-light customers, escalate for flagged accounts. AI will validate damage photos, chatbots will handle end-to-end returns in natural language: the customer describes the issue, and a label arrives by email without ever visiting a portal. AI will play a key role in CX. The returns portal becomes invisible infrastructure – the interface between customer intent and operational fulfillment.

This vision might sound like Fiction to you. But the good news? The first step is the simplest. Sit down with your warehouse lead, your CS manager, your product team, and your CRM owner. Ask them one question. The answers will tell you where your money is going.

When managed properly, returns can provide opportunities to drive conversions and loyalty, especially when you implement marketing strategies during the returns process. They also serve as valuable touchpoints for gathering customer feedback and making data-driven improvements.

For these reasons, you must ensure that your operations and teams are equipped with solutions to stay on top of returns. 

Read on to learn how to do just that.

Common reasons for customer returns

To effectively handle returns, it’s best to understand why they happen in the first place. Depending on the industry, the top reason for a return can vary. For example, in Fashion, the most common reason for returns are fit and size issues.

Across the board, though, the most common reason that a customer returns an item is that they received a damaged or defective product. In some cases, this can be prevented by quality control and/or better packaging of the product when it ships. On the other hand, the product could end up damaged en route to the customer, regardless of preparation.

Then, the other reasons for returns are buyer’s remorse, fraud, and items delivered later than expected. Now, you can’t control buyer’s remorse, but you can make it more difficult for shoppers to commit return fraud and display more accurate delivery dates.

To address these return reasons appropriately, you should have a solid system in place to collect return data and improve the process as a whole.

Methods for handling returns

There are several methods and channels to handle returns. Depending on your business, you can choose to accept returns in-store, online, or both. Our advice is to give consumers the option to return across online and offline channels. That way, they can choose the option that is best for them.

Let’s look closer at the different channels you can use when accepting and processing eCommerce returns. 

In-store returns

Implementing in-store returns means allowing customers to return their online purchases in-store. Retailers with brick-and-mortar locations typically implement this return method. 

Here’s how in-store returns work:

Customers head to the store to return their items. Then, store teams inspect the items. Depending on the condition of the goods, they may be put back on the shelf, refurbished, or disposed of. 

It’s worth noting that you may still be able to implement in-store returns even if you don’t have a physical store.

Consider teaming up with a brick-and-mortar retailer or another facility that can handle in-person returns. 
Amazon, for example, allows customers to return items in select Kohl’s or Whole Foods locations. 

Warehouse returns

Warehouse returns take place when customers send back their orders via mail. Here’s how it works:

Customers initiate the return process online, usually through a self-service return portal, and follow the steps outlined in the return policy. 

Upon approval, customers receive a Return Merchandise Authorization (RMA) number and a prepaid shipping label or QR code via email or directly in their online account. 

Customers package the items securely, affix the shipping label, and drop off the package at a designated carrier location. 

Once the returned items arrive at the warehouse, they undergo inspection to assess their condition. The items may be restocked, refurbished, or disposed of depending on the condition. 

After the inspection, customers are notified of the status of their return, and any applicable refunds or exchanges are processed accordingly.

Outsourced logistics

eCommerce returns have multiple moving parts and can be quite complex, especially if you have a large and distributed customer base. That’s why some merchants use third-party logistics companies that can handle returns for them. 

Outsourced returns management means teaming up with a Third-Party Logistics (3PL) provider that specializes in handling the various aspects of the returns process. This can include everything from receiving and inspecting returned goods to restocking, refurbishing, or disposing of items.

The importance of a return policy and setting clear returns guidelines

Whatever your process is for handling returns, you need to ensure that it’s backed by a solid returns policy. Ironing out your policy and setting clear guidelines are crucial for several reasons.

A good returns policy promotes trust and transparency

Clearly stating what and when it is acceptable to return an item in your return policy establishes transparency, which builds trust between you and your customers. Your return policy should be easily findable. This means including it on your product detail pages, in your post-purchase communications, and in your return portal. People are more likely to purchase from you if they know they have a hassle-free experience. 

Ensure compliance

Be aware of consumer protection laws around returns, and make sure you adhere to them. Having a well-documented returns policy that complies with the necessary regulations can help you minimize legal and regulatory risks.

It makes you more efficient

Having a well-documented policy will guide your team in handling returns so they can manage returns efficiently. A good policy also ensures consistency in how returns are dealt with, regardless of who takes care of them. 

A returns policy can influence purchase decisions

NRF’s Retail Returns Landscape report shows that 82% of shoppers check the return policy when shopping with that brand for the first time. This means that your returns policy isn’t just a backend consideration; it’s an important customer-facing tool. And when you have a good returns policy in place, customers may be more inclined to buy.

What to include in your returns policy

Now that we’ve tackled the benefits of a returns policy, let’s discuss what it should look like. Generally speaking, a good returns policy outlines the following:

Time frame for returns

Specify the time frame for when returns can be made. What is your return cut-off time? Many retailers set a time frame of 30 or 60 days, while others are more lenient.

Note that you can adjust your time frames depending on the product. It’s not uncommon for brands to have a different policy for high-value items like jewelry or electronics. 

You can also adjust your policy depending on the time of year. Many retailers expand their returns cut-off during the holiday season. That’s because this is a period when many purchases are made as gifts. Extending the return window accommodates the gift-receiver, who might not have the opportunity to evaluate the gift until the holiday is over. 

Product condition

Your returns policy should also have guidelines around the condition in which products can be returned. Should they be returned in their original packaging? How will you determine if something is used or worn? Make sure you establish your eligibility criteria to avoid issues down the road. 

Refund process

Outline how refunds (or lack thereof) are handled. If you’re issuing refunds, specify how long it’ll take and the method by which customers can expect the funds. If you’re not offering refunds, your policy must also state that and indicate that you’ll only be allowing exchanges or issuing store credit.

Return channels

Ensure your policy sheds light on the methods and channels customers can use to return their products. If you’re accepting online returns to your warehouse (or 3PL’s facilities), indicate who is responsible for shipping costs.

Returns procedures

In line with the section on returns channels, it’s also helpful to outline the steps customers should take to ensure a smooth returns process. What actions should they take to initiate a return? How can they obtain the necessary information or documents (like shipping labels) to return their purchases?

Exceptions

Finally, if you have products that aren’t eligible for returns, specify what those items are so customers know that they’re purchasing something that’s a final sale. 

Streamline customer returns by leveraging self-service return portals

To truly offer a seamless experience, you should be leveraging a flexible self-service return portal. This portal should make the returns process faster and more efficient, increasing customer satisfaction.

Not only should your return portal be equipped to properly handle returns, but it should also encourage customers to exchange or accept store credit. The returns management software that you use should be able to work with your return rules to try to recover revenue.

For example, if an item is defective, the customer can choose to exchange that item for another item. Or, if someone ordered a Yeti water bottle, but it was a smaller size than they expected, they should be given the option to exchange it for the larger size. This way, the customer is happy, and you get to keep that revenue that would have been lost to a return.

From a business operations perspective, a standardized, automated process ensures that all returns are handled consistently, reducing the likelihood of errors or discrepancies. Additionally, return portals can also collect data on why customers return items. This information can be super valuable for identifying trends, improving products, and tailoring future marketing efforts.

Keep your customers in the loop during the process

Another vital component of returns management strategy lies in post-purchase communications. Just as you would proactively communicate tracking updates and send shipping notifications when customers make a purchase, you should also extend the same level of diligence to the returns process.

Rather than a generic-looking email, send a message that’s aligned with your brand’s look and feel. Every communication you send from pre-purchase to post-purchase and returns should be consistent. When a returns experience can make or break whether a customer shops with you again, it is important that this journey doesn’t differ just because they had to make a return.

Additionally, the return communications should empower customers to track the journey of their package back to your warehouse or 3PL. This helps set the right expectations, particularly when it comes to their refund. It also frees up your team from having to deal with WISMR (Where is my return?) inquiries because the customer is proactively informed throughout the process. 

Gather feedback on the return journey

The best way to improve your returns process (and overall shopping experience) is to collect data and input from your customers. You should incorporate feedback surveys within your return portal and in your returns communication. After all, it’s helpful to know:

• Why they’re returning a product

• How they feel about the customer experience
• The ease and speed of the return and refund process
• What they think about the returns or shipping options
• How your process compares to other retailers

Understanding these factors allows you to spot areas of improvement so you can make changes and enhance the post-purchase journey even more. 

Final words

Returns can be challenging to deal with, but there are several steps you can take to streamline the process for both your business and your customers. Start by having a solid policy and ensure your operations are backed with robust tools and technologies that can simplify the returns experience. 

If you are interested in learning more about how to reduce your return rates, we have the blog for you.

On top of the increasing return costs, retailers also deal with expensive customer acquisition costs. This is why it is more important than ever to keep the customers you already have. And if you do get a new customer, your post-purchase journey should be top-notch. Otherwise, you risk losing the shopper you worked so hard to gain.

Recently, retailers have been focusing more on their returns journeys. But what does that actually mean, and what’s been effective?

While there are plenty of ways to reduce your return rate, an effortless self-service returns process is one solution that has been deemed very useful for retailers looking to decrease costs and improve the customer experience.

What are self-service returns?

A self-service return refers to a process where shoppers conveniently return items using a returns portal on a retailer’s website. This interactive experience lets customers easily choose items from their order to return or exchange, share why and how they want to return them, and then print labels or receive QR codes to complete the process. Simple! And all without having to contact customer service for help.

Customers then package their return for pick-up or drop-off to a designated carrier or location. With digital QR codes, you don’t even require a box or for the customer to print a label. Can’t get more convenient than that!

Included in the self-service returns are components such as refund options, step-by-step instructions on how to return the package, and a status overview for tracking the returns status in the customer’s account. Some retailers also offer the option of dropping off the goods at their physical store or having the logistics provider pick it up at home.

All with the aim of creating an effortless returns process that is as simple and stress-free as possible.

The self-service return approach can also handle more complex return processes like damage claims, warranty repairs, or replacements. Retailers can prompt shoppers to supply additional details and photos, so they can approve and process claims faster. This allows retailers to deliver a better customer experience while saving on customer service costs. Smooth!

Why should retailers care about self-service returns?

71% of shoppers say that if they have a poor returns experience, they are less likely to shop with that retailer again. That means if you aren’t currently working on improving your return experience, this is your sign to do so!

parcelLab data has found that retailers who leverage a returns portal see 3x more repeat purchases. In addition to this, self-service returns hold a lot of advantages for retailers. Let’s dive into some benefits below.

1. More efficient warehouse operations

With a paper-based process, retailers only know what has been returned once the package is received and processed at the warehouse. With a digital self-service returns process, retailers get more data faster. They know exactly which items in an order have been selected for return and why. While the items will still need to be inspected, it helps retailers plan and staff based on each day’s expected returns volume. They can also determine which items can be restocked and which may need to be disposed of or recycled earlier.

2. Improved data collection and inventory management

Having more immediate information allows eCommerce teams to analyze the reasons why items are being returned. They can then use that knowledge to make changes and reduce the likelihood of future returns. For example, they may update sizing and fit recommendations in clothing descriptions or update photos if colors are not represented as customers expect.

Product teams can also use returns data to improve future product iterations. If a customer complains that a feature is too difficult to use, then the team can work on making it better.

3. Revenue protection and faster re-purchases

Self-service returns empower retailers to recapture revenue that otherwise would be lost by offering exchanges, store credit, or gift cards in place of refunds. If a customer selects the return reason as “wrong size,” the return portal can show what other sizes are available for that item so your customer can do an exchange. Or, perhaps the customer didn’t like the color they received, so they can be shown other colors that they might like instead. This level of personalization is a game-changer for recovering revenue.

In the case of a customer who prefers to just submit the return, a return portal can promote relevant products and promotions. This way, shoppers can also be enticed to make repeat purchases sooner.

4. Elevated customer experience and loyalty

Since most return portals are flexible, brands can customize it based on their return policy and segmentation rules. For example, you may offer a first-time customer an incentive for store credit with a refund. So, they return to shop with your brand again. For a loyal customer, you may offer an instant refund since you know they will take the proper steps to return their item.

The returns experience is an important part of the customer journey

Making returns more convenient through self-service initiatives is a key area of opportunity. With more data, retailers can be more in tune with customer needs, create engaging and personalized returns experiences, and provide proactive customer support. It’s a win-win for eCommerce retailers and shoppers alike.

Read all of the Returns Management Playbook Chapters:

Chapter 1 – What is Returns Management?
Chapter 2 – Returns Management: Challenges and Best Practices
Chapter 3 – How to Reduce Your Return Rate: 11 Tips For Fewer Returns
Chapter 4 – What is Self-Service Return? You are here
Chapter 5 – Guide to Retail Returns Management read next chapter
Chapter 6 – The Best Return Management Software
Chapter 7 – Understanding B2C Europe Returns
Chapter 8 – The Complete Guide to Retail Returns Marketing fit recommendations in clothing descriptions or update photos if colors are not represented as customers expect.

This observation from Angus Knights, VP of Product at parcelLab, cuts to the heart of why so many retailers stay stuck with post-purchase vendors they openly complain about. The barrier goes way beyond technical complexity or budget constraints: most eCommerce teams have simply never experienced what great post-purchase can look like.

The invisible problem nobody owns

Post-purchase sits in a strange category of business problems. As soon as your warehouse management system fails? Products stop shipping. If your payment gateway breaks? Orders can’t be processed. The pain is immediate, visible, and impossible to ignore.

Post-purchase is different. Packages still arrive, and emails still go out. On the surface, everything appears to function. But beneath that surface, the cracks run deep, and almost nobody can see them. Angus explains:

“The thing about post-purchase experience is that the benefits are different. It’s not to keep the lights on technology. But actually, when you really double click into “how to build profitable eCommerce businesses”, experience is essential. You cannot survive long-term without it. But I think the pain is a different pain. It’s like a chronic kind of slightly undiagnosed pain that sits in the background.”

This chronic pain manifests in ways that rarely trigger alarm bells. Customers who don’t return, preventable support tickets, and revenue attribution that’s broken without anyone realizing it. The costs accumulate invisibly, quarter after quarter, while teams focus on brighter fires.

Making matters worse, post-purchase spans nearly every department in an organization. Logistics handles carrier relationships. eCommerce owns the website. Marketing manages customer communications, customer service deals with the fallout, and CX teams measure satisfaction. But who actually owns the end-to-end experience?

“It’s such a cross-functional project across operations, logistics, and eCommerce. It touches on marketing, it touches on customer experience, and it impacts customer service. There are so many different departments across this whole space that often the ownership is split.”

Back to the question: “Who picks this up?” The answer, too often, is: nobody does.

When first implementations disappoint

Most retailers considering a vendor switch aren’t starting from zero. They’ve been through this before. Years ago, they invested in a post-purchase solution with high hopes for better tracking, proactive communications, reduced support volume, and maybe even incremental revenue.

The implementation delivered some of those benefits. Metrics improved. But the transformation everyone envisioned? It probably never quite materialized. Projects that were supposed to take two months stretched to five or six. Features that sounded simple proved surprisingly difficult to execute. And somewhere along the way, enthusiasm gave way to resignation.

This creates a particular kind of organizational trauma. Teams begin to question whether the problem was their vendor, their own execution, or whether post-purchase simply isn’t as impactful as everyone claims. That uncertainty becomes its own barrier: why risk another painful implementation if the payoff might be equally disappointing?

The expert perspective

Angus Knights brings a unique vantage point to these questions. Before leading product strategy at parcelLab, he ran the Solutions Consulting team. The technical pre-sales group that works directly with retailers who are evaluating vendor switches. He’s sat across the table from hundreds of eCommerce leaders wrestling with this exact decision.

All that experience revealed a pattern. The retailers who stayed stuck weren’t lacking capability or resources; they were lacking visibility into what was actually possible. Vendor promises weren’t helping because every vendor promises everything.

The 95/5 execution gap

Here’s the uncomfortable truth about vendor evaluation: on paper, every post-purchase platform offers essentially the same features. Need embedded tracking pages on your domain? They can do it. Want proactive delay notifications? No problem. Looking for carrier integration with your specific 3PL setup? Absolutely. Angus confirms:

“On a theoretical level, almost every vendor has almost all capabilities. If you really just break it down to: “can we put a tick in the box for ‘did we do this once somewhere?’” The answer is usually yes. Almost everyone has done something once somewhere. But that doesn’t mean that the people […] actually know how to do this.”

This is the checkbox problem. Vendors staff RFPs with features they’ve technically implemented at least once, somewhere, for some customer. That single successful implementation becomes a “yes” on the capability list regardless of whether the team assigned to your project has ever done it before, or whether they can do it consistently at scale.

In short, execution frequency beats capability. Angus illustrates this with tracking pages:

“In 95% of cases, for hundreds of customers that we have, our pages are embedded. In 95% of cases for other vendors, the pages are not embedded. We both have all the same capabilities, but 95% of the time we’re behaving differently.”

Same features on the spec sheet. Radically different outcomes in practice. This 95/5 execution gap explains why two retailers can choose vendors with identical capability lists and end up with completely different results.

This translates directly into the due diligence question that actually matters: Instead of “Can you do this?” ask: “What percentage of your customers are you actually doing this for?”

The three P’s of vendor evaluation

Breaking through the capability theater requires a different evaluation framework. One that looks beyond feature lists to the factors that actually predict success. Angus describes this as the Three P’s: Purpose, People, and Platform.

Purpose comes first, before any vendor conversation begins. What are you actually trying to achieve? The answer shapes everything that follows.

Some retailers are revenue-first. They see post-purchase as a channel for driving repeat purchases, and they want segmentation capabilities, personalized product recommendations, and different communication flows for different customer cohorts. Others are experience-first. They’re focused on reducing friction, proactively addressing delivery issues, and turning support contacts into opportunities for delight.

Neither approach is wrong. But a vendor optimized for one may underdeliver on the other. Starting with purpose prevents the common mistake of evaluating platforms based on features you’ll never prioritize.

People determine whether capabilities become reality. The humans behind the vendor – their expertise, their availability, their understanding of your specific business goals – matter more than any feature on a roadmap.

Reference calls should give you a good idea of the team you’re working with. Be sure to ask: “How does the collaboration actually work? Who do you have access to when problems arise? Do they understand what you’re trying to accomplish, or are they just trying to close tickets?”

Watch for warning signs:

• Project teams focused solely on getting to launch rather than driving business outcomes.
• Expertise that exists somewhere in the vendor organization but isn’t available to you.
• Slow response times that suggest you’re not a priority.

Platform is not just a question of features, but of accessibility. Can your team actually use the capabilities on offer, or do they require weeks of vendor involvement for every change?

This distinction matters enormously for long-term value. Angus observes:

“If setting up an email communication is going to take you five weeks, you just don’t bother because it’s not on fire. It’s just a friction that you’d like to address, and it’s hard to do. And if you are working on a solution where it’s very easy, like a couple of hours to test a solution, then your likelihood of taking that step is just so much higher.”

Self-service capability isn’t a nice-to-have. It’s the key to driving improvements continuously over time.

Strategic principles for eCommerce and CX leaders

Beyond the Three P’s framework, several principles separate the retailers who successfully navigate vendor evaluation from those who stay stuck.

→ Order from the vendor’s customers. Every vendor will show you their lighthouse references. The handful of implementations they’re proudest of. These prove that their capabilities exist somewhere. They tell you nothing about consistency.

Instead, place actual orders from retailers using the vendors you’re evaluating. Experience their tracking pages, their email communications, and their returns process. Do this across multiple brands, not just one. The patterns that emerge will reveal far more than any demo or reference call.

→ Use reference calls strategically. When you do get on calls with existing customers, skip the softball questions. Ask which metrics mattered most during their switch. Ask how the collaboration actually works day-to-day. Ask what surprised them, positively or negatively. Ask what they’d do differently.

→ Solve the ownership problem internally. The most successful post-purchase implementations share a common organizational pattern: cross-functional ownership, typically through product management.

When post-purchase sits with logistics, the focus narrows to carrier performance. When it sits with marketing, the focus narrows to email metrics. When it sits with customer service, the focus narrows to ticket deflection. Only when a cross-functional owner can optimize across all these dimensions does post-purchase reach its full potential.

If your organization doesn’t have this ownership model today, no vendor switch will solve the underlying problem. The organizational design has to come first.

→ Establish benchmarks before you switch. The ability to demonstrate clear before-and-after improvement changes everything about internal momentum. It turns skeptics into advocates and justifies continued investment. In the long run, you’ll need the organizational permission to push further.

Identify your key metrics now – WISMO contact rates, repeat purchase attribution, delivery exception handling, whatever matters most to your purpose – and establish clean baselines before any migration begins. Interested in how the story continues? Check Angus’ 3 Phase Playbook for successful vendor migration.

The cost of waiting

The gap between “good enough” and “best in class” post-purchase experience is widening. Leading retailers are pushing into territory that simply doesn’t exist in legacy setups: AI-powered WISMO agents that handle customer inquiries conversationally, predictive interventions that resolve delivery issues before customers even notice, and hyper-personalized communication flows that drive measurably higher lifetime value.

These capabilities are fundamentally new, and they’re creating competitive separation that grows more significant every quarter.

Meanwhile, contract cycles are creating natural evaluation moments. Many retailers implemented their current post-purchase solutions 3 to 5 years ago, during the eCommerce boom. Those contracts are coming up for renewal. The best moment to evaluate alternatives is now: with clear eyes about what’s actually possible.

The chronic pain of suboptimal post-purchase won’t announce itself. It won’t trigger urgent action the way a warehouse failure would. It will simply continue accumulating in customers who don’t return, support costs that could have been avoided, and revenue attribution that remains invisible.

Breaking free starts with recognizing what you might be missing. Shop the competition. Ask the hard questions. Solve the ownership problem. And above all: resist the assumption that what you have is good enough, simply because you’ve never seen better.

Top-line revenue growth for fashion is expected to remain modest. Many traditional growth engines, like luxury spending and pure digital discovery, are under pressure. With consumers becoming increasingly price-conscious and competitive pressures intensifying, brands need new levers for differentiation and loyalty.

To cut to the chase, the post-purchase experience is now entering the chat for many retailers. It’s no longer considered an afterthought, but now a necessity to maintain a competitive advantage and keep customers happy.

Customers judge you after the buy button

Fashion brands can’t rely on product, price, or discovery alone to retain customers. McKinsey’s research shows that consumers are increasingly focused on value and experience. Loyalty is no longer a given.

In this environment, the post-purchase experience becomes a rare opportunity to influence how customers feel about a brand and whether they come back again. Often, pre-purchase engagement is mediated by marketplaces, search platforms, or social media influencers. On the other hand, post-purchase touchpoints such as delivery visibility, proactive communication, and returns remain owned by the brand. That ownership is a goldmine for building trust and loyalty.

At parcelLab, we’ve seen this play out firsthand with fashion brands of all sizes. The difference between a brand that simply fulfills orders and one that makes customers feel consistently valued often comes down to how the post-purchase experience is designed and executed.

Experience is everything

Take Hugo Boss, one of the world’s leading fashion houses. As the brand scaled its global eCommerce operations, it recognized that delivery and returns were critical moments for customer engagement. Their post-purchase journey includes real-time tracking and personalized communications. What once were routine shipping updates are now engaging touchpoints that reduce support inquiries, drive return visits to the brand site, and open doors for cross-sell and upsell opportunities.

This shift turns something traditionally seen as “logistics” into an end-to-end brand experience. Instead of customers wondering “Where’s my order?” with uncertainty, they’re met with clarity, transparency, and relevance. Factors that contribute directly to loyalty.

Think about today’s consumers, especially Gen Z. Shoppers are willing to trade down for value or look to resale or thrift stores. If they decide to purchase with your brand and you don’t earn their trust, they’ll switch to a different brand. That’s why the brands that focus on the post-purchase experience see higher customer loyalty than the ones that don’t.

Turning post-purchase into revenue growth

Another example comes from True Classic, a mid-sized fashion brand that used branded post-purchase messaging to directly influence revenue. True Classic saw a 29% increase in revenue per email driven by post-purchase engagement alone.

This is more than a one-off metric. It demonstrates a broader trend: post-purchase messaging can be a revenue driver when it goes beyond basic order updates. By embedding tailored content, offers, and recommendations into delivery communications, brands can seamlessly guide customers back into the shopping experience long after the initial purchase.

With AI-powered curation being a major focus for brand engagement moving forward, owning the post-purchase relationship gives brands a direct line to their customers that isn’t controlled by third parties.

Why returns and exchanges are competitive frontiers

An astronomical amount of money is lost each year to returns, and the fashion industry, unfortunately, has the highest return rates. While some returns are unavoidable, the returns experience represents an opportunity. It’s a moment of friction that, if handled elegantly, can dramatically increase loyalty.

Leading brands are rethinking returns as a relationship-building moment. When you make returns easy, transparent, and empathetic, customers feel like the brand understands them, and that builds emotional equity. While it may seem like a huge lift to revamp your returns journey, it is easier than you think. The returns management platform you use should work with you to adjust to any new rules, personalization, and refund methods that work with your return policy.

If you want to look into recommendations on how to reduce return rates, we have the blog for you.

Post-purchase as a strategic differentiator

Ultimately, McKinsey’s outlook for fashion is sluggish top-line growth and shifting consumer behavior. It just underscores the importance of competitive differentiation. Brands can no longer rely on product alone. They must offer experiences that justify customer loyalty.

Post-purchase is one of the few stages of the customer lifecycle where brands can consistently create value at scale. When brands have a strong post-purchase experience, they:

• Build customer trust and retention
• Turn delivery and returns into revenue opportunities
• Reinforce brand value beyond price
• Create moments that differentiate leading brands in a crowded market

Whether it’s a luxury heritage brand like Hugo Boss or a challenger like True Classic, the brands investing in post-purchase as a strategic experience are the ones capturing long-term loyalty and revenue growth.

Looking ahead

As the fashion industry evolves through economic headwinds and technological shifts, brands that continuously innovate their entire customer journey will stand out amongst the rest. The post-purchase is a core competitive advantage that fashion brands must embrace to thrive in a crowded, value-driven market.

The uncomfortable truth? All major AI models are functionally identical. The problem lies elsewhere.

“One in a thousand retailers create opportunities to go beyond basic implementation,” says Julian Krenge, Co-Founder and CPO at parcelLab. “Yes, basically only a few retailers that really doubled down on this and wanted to drive real customer experience improvement.”

That’s not a typo. One in a thousand. Which raises an obvious question: What are those 0.1% doing differently?

Julian Krenge works with hundreds of retailers from SMBs to enterprise giants every single day. He sees which AI implementations deliver results and which ones fall flat. More importantly, he’s identified a pattern: Retailers often don’t know where they stand on the AI maturity scale. And because they don’t know where they are, they choose the wrong next steps.

From these observations, Julian developed a stage model that allows retailers to assess their current position and plan their next move with clarity. Picking a tool before understanding your current state is like navigating without a map. First assess where you are, then define where you want to be.

Why the traditional approach doesn’t work

“AI for Customer Service” is too broad to be actionable. Without clear progression logic, retailers don’t know what’s realistic. They expect a 30% ticket reduction and run into the reality that a basic FAQ bot is about as effective as a digital parrot.

The jump from “informing” to “acting” gets massively underestimated. That’s where implementations stall. AI success isn’t a question of the tool. It’s a question of maturity, and that maturity builds in clearly defined stages.

The AI CX maturity ladder

Before retailers can progress through the maturity stages, they need to see the full customer experience (CX) landscape. Most think “AI in CX” equals “AI in Customer Support” and miss three other domains entirely.

The complete picture includes four areas:

• Customer support – covering WISMO, returns, and warranties.
• Pre-purchase support – handling sizing, product guidance, and compatibility.
• Automated communication – managing order confirmations, dispatch, and cancellations.
• Legal obligations – processing returns, recalls, and chargebacks.

This domain map becomes your use case backlog. It shows where AI can create value and helps you prioritize where to start. With the full landscape in view, retailers move through a predictable development.

Each stage has clear characteristics, measurable outcomes, and specific requirements for the next step:

• Stage 0: AI makes an informed guess (FAQ-Level)
• Stage 1: AI handles one thing well – Informative
• Stage 2: Branching path – “Taking action” OR “One AI for everything”
• Stage 3: Combined multi-use case AI with cross-pollination effects

Understanding where you stand on this ladder changes everything. It sets realistic expectations, clarifies the next actionable step, and prevents the most common mistake Julian sees: switching tools instead of enabling them.

The detailed blueprint: Stage by stage

Stage 0: AI makes an informed guess

The FAQ-bot is better than nothing, but far below potential.

At this stage, your AI uses FAQ data combined with standard LLM knowledge. No live data or customer specificity. When someone asks about their order, the typical response is: “Here’s the link to our order status page.”

The AI knows general eCommerce knowledge from its training, your FAQ content, and standard processes like “FedEx typically delivers within 3-5 days.” What it doesn’t know: individual order status, customer history, or product-specific details.

The expected impact remains modest. A small reduction in customer service inquiries and less traffic on your FAQ page. But there’s no significant monetary impact.

Stage 0 works when you’re selling simple products like smartphone cases, using Fulfillment by Amazon, or running highly standardized processes. It falls short with complex logistics, high product variance, or B2B-adjacent markets with specific requirements. On the opposite end of complexity sits a retailer like IKEA, who operates their own fleet to deliver furniture. For them, such a setup would essentially solve zero problems.

The most common mistake at this level: Tool-switching instead of tool-enabling. Retailers change providers instead of integrating more data into their existing system. As Julian puts it:

“Fundamentally, even if you look at all of the benchmarks and the underlying AI models, ChatGPT and Gemini and Claude are identical. They are as good as the other. The limiting factor is how do you put in more knowledge, more context so it can give the right answer.”

Stage 1: AI handles one thing well (informative)

The AI accesses real data and delivers individual answers.

This is where things get interesting. Your AI now has live data for at least one use case, retrieves customer-specific information, and provides personalized responses.

Take WISMO inquiries as an example. Instead of a generic link, the AI now says: “There’s this one order for you. It’s two packages. One is coming from our East Coast Fulfillment Center, one is coming out of the West Coast Fulfillment Center, and both are with FedEx. And for one, we already have a delivery date because it has been dispatched, and the other one will probably be dispatched tomorrow.”

That’s a fundamentally different experience.

“Realistically, you can have an expectation for something between 20 and 30% of the WISMO inquiries that are currently hitting your customer support team, you will be able to resolve with AI before it actually ever hits a human. Those are non-value adding contacts anyways that are deflected ahead of time.”

Retailers like YETI, with their Ada-powered order lookup, and True Classic, with their codefuse-powered chatbot, operate at this level.

Moving from Stage 0 to Stage 1 requires four steps.

• Identify which use case has the highest impact.
• Map what data the AI needs.
• Integrate real-time data sources technically.
• Test and evaluate response quality.

When prioritizing, multiply Impact by Confidence. Low confidence means a bigger discount on expected results.

Stage 2: The branching path

The strategic decision: Go deeper or go broader?

After Stage 1, retailers face a fork in the road. You can either go vertical, enabling your AI to take action, or go horizontal, expanding to multiple use cases.

Stage 2A: Taking action

The AI executes. Not only is it informing, but it’s doing.

Your AI learns to trigger processes autonomously. It becomes transactional, requiring significantly more technical integration. Consider the returns experience. At the informative level, the AI can look up your order and tell you: “I see you ordered three items. One is a hygiene item. You cannot return this. Everything else is returnable until December 14th.”

At the action level, rather than only giving you information about the return policy, the AI actually asks you what items you want to return and why, and you just chat with it. At the very end, you get a return label and an email saying you can drop off your items.

If you’re at this stage, you belong to the 0.1% of retailers most invested in AI. Pandora works toward this vision with their “Gemma” AI – a one-stop shop that can take actions on behalf of the customer. They’re not there yet, but that’s what they’re building toward.

They expect the impact to be a 50-70% reduction in manually processed cases, and approximately a 20-25% repurchase rate for loyal customers.

But here’s the caveat, Julian warns:
“The step between this informative AI is so large that it’s kind of its own stage. Moving to having it take action is larger from an effort level than the stage from zero to one.”

Stage 2B: One AI for everything

One chatbot, many use cases with compound effects.

Instead of deeper action-taking, you expand broader. The same chatbot handles order status, sizing help, and shopping assistance simultaneously. This creates cross-pollination effects:

“Maybe before you were able to resolve 20% of your WISMO queries. But now people go for shopping assistance and sizing help pre-checkout, and already interact with your chatbot. So they’re much more likely to use it post-checkout. Maybe your resolution rate goes up from 20 to 25 or even 30% because you have more adoption.”

True Classic operates this way – combining order status, sizing help, and shopping assistance in one interface.

Choose this path when multiple use cases have similar effort levels, when action-integration seems too complex, or when pre-purchase conversion represents a significant pain point. Julian sees huge potential here:

“I think the potential of having the AI help with this product discovery over a search, for example, is huge. So you start maybe with reducing costs. But ultimately, it helps you generate upside potential. And the upside is much more interesting.”

Stage 3: Combined multi-use-case AI with cross-pollination

The vision: One central agent for everything.

At this pinnacle, you achieve multi-domain coverage with action-taking capability. The AI understands customers holistically across pre-purchase, post-purchase, returns, and service, using context across all domains.

But how do we get to this Iron Man 3-esque stage?

By combining multiple use cases with action-taking ability, your probability of adoption increases because the more your chatbot can do, the more likely people are to come back to it. You get all of the individual case improvements combined, plus higher adoption overall.

However, please don’t crash into your IT department yet, waving this blog post around: Even leading brands like Pandora are still building toward this. It requires massive technical and organizational investment, and may only be realistic for retailers with dedicated AI teams.

From invisible to unbeatable: What each stage delivers

The transformation becomes tangible through concrete benchmarks:

At Stage 0, your AI answers: “Here’s the link to our order status page.” Customers research everything themselves with no personalized experience.

At Stage 1 and beyond, your AI responds with real, individual data. Customers feel understood. 20-30% fewer tickets reach human agents, freeing them for complex cases requiring genuine expertise.

At Stage 2 and beyond, your AI acts proactively. Customers experience frictionless processes. Retention and revenue rise measurably.

Conclusion: Your next move on the maturity ladder

In order to achieve AI success in CX, you need to build maturity systematically: stage by stage. The required mindset is threefold. Manifest this:

• Patience: The jump from Stage 1 to Stage 2 takes time.
• Focus: Better to execute one use case properly than three halfway.
• Re-evaluation: Assess your position every six months as technology evolves rapidly. As Julian notes: “Whatever you thought six months ago doesn’t work anymore.”

With all the caveats about complexity and effort, one thing remains clear. Julian emphasizes: “The cost of not doing it is way higher.”

Wonder where to start?

• Assess: Where do you stand on the maturity ladder?
• Prioritize: What’s the next realistic step?
• Execute: One use case, done right
• Evaluate: Measure, learn, iterate

Those who lay the groundwork now will be best positioned when AI capabilities continue to advance.

Every retailer could probably think of a crazy return fraud story that’s happened to them. Trust us, we have heard a few. From the warehouse receiving rocks instead of a product to fake receipts stolen off of TikTok videos, fraudsters know how to be creative in hopes that your brand falls for their tricks.

The good news is that retailers have found successful ways to reduce the likelihood of return fraud, and we have the inside scoop.

Let’s jump in.

1. Use clear communication to set expectations

While this may seem the most obvious, return fraud thrives in ambiguity. Clear policies, communicated in plain language, remove gray areas without sounding threatening. It is also best practice to make sure your brand’s return policy is easily accessible. This means that you have it findable in post-purchase communication, on the tracking page, and on the return portal.

For the most cohesive return policy, we recommend

• Explaining why certain return rules exist
• Reinforcing fairness (“to keep prices fair for everyone”)
• Keeping the tone human, not legal, so everyone can understand

These practices not only make it easier for customers to understand but also ease the burden on your customer service team. Customers are far more likely to follow the rules when they understand them, and your agents can better enforce polices when they’re written in plain language.

2. Define and create smart, segmented rules

When a return policy is vague or one-size-fits-all, the chances of fraud increase dramatically. Fraudsters thrive when rules are predictable and universally generous. But you also wouldn’t want to create a strict return policy, as it can alienate loyal and genuine customers who want to shop with your brand.

Instead, we recommend that retailers should leverage a self-service return portal where they can configure different return rules based on:

• Customer lifetime value
• Purchase and return history
• Product category (high-risk SKUs vs. low-risk items)
• Reason for return

Retailers that use this best practice offer loyal customers options like free returns or instant refunds. Then, first-time or unknown shoppers are shown options like store credit, exchanges, or potentially a fee for the return. This depends on the return policy, of course, and can be used to recover revenue during the returns journey while still keeping loyal customers happy.

If you are a brand that sees a lot of return fraud, you can try adding rules for restocking fees once a shopper passes a certain threshold. This works well with shoppers who may purchase a lot of different sizes for clothes (repeatedly), then choose to return the ones that don’t fit.

While return policies and rules can be tricky, it is helpful to know there are ways you can make loyal customers never feel the friction and make bad actors quickly lose the incentive.

3. Require return validation

Fraud often happens because returns are too easy to game. When resources are tight, adding manual checks everywhere sounds like a logistical nightmare. There is a good middle ground, though.

Here are a few better alternatives that won’t take up all of your team’s time:

• Require reason codes with structured options (not just free text)
• Trigger photo uploads only for high-risk items or customers
• Validate serial numbers, barcodes, or SKU-level data on select products

The goal isn’t to interrogate every customer. It’s to apply guardrails selectively where the risk is highest. This way, loyal customers continue to come back time and time again.

4. Track return behavior patterns

Sometimes fraud doesn’t show up as a big red flag. It’s usually a pattern over time. While brands may not be able to block every instance of fraud, there are ways to monitor trends that display fraudulent behavior.

Here are some common signs to look for:

• Customers who repeatedly return after promotions
• High-value items that are returned at unusually high rates
• “Wardrobing” behavior (used items returned as new)
• Claims of “item not as described” across multiple orders

Returns data plays a powerful role in improving the returns experience for your customers and for your brand. This can only be accomplished when the data is centralized, searchable, and actionable. If you can’t currently access data like this, o

5. Time refunds to confirmation, not drop-off

Instant refunds are great for loyal customers, but they should never be applied universally. Just like with any personalization tactic, there should be rules in place to ensure that your customers don’t start abusing certain policies.

This means:

• Charging for returns until a customer passes a certain threshold or can be deemed as “trusted” and loyal
• Delaying refunds until item scan or warehouse receipt for higher-risk profiles
• Transparent refund timelines so customers aren’t left guessing

When your brand is as transparent as you can be, you reduce the likelihood of fraud happening and reduce costs as well.

6. Treat return fraud as a CX problem

Fraud prevention shouldn’t live only with finance or ops. It’s a post-purchase experience challenge. While it may feel like all roads lead back to the customer experience team, hopefully, by looking at fraud from a new angle, you can make small efforts over time that can bring a dramatic impact.

Retailers that reduce fraud most effectively:

• Embed fraud logic into their returns flow
• Use data to personalize decisions in real time
• Balance protection with empathy
• Leverage technical resources where necessary, i.e., a returns management platform and/or a fraud prevention tool

A returns experience is never one size fits all

What works for other brands may not work for you, and that’s okay!

This is the time to think about new approaches to your post-purchase and returns journey. Take the time to look through your return data from last year and see if you can spot any trends that can help improve for this year. See if the returns management platform you are currently using is actually working with you and for you. Trust us, if you need to make a switch, it’s easier than you think with the right partner.

At NRF, parcelLab’s Chief Product Officer, Julian Krenge, sat down with Jordan Gesky, formerly of True Classic, to unpack three years of hands‑on experimentation across post‑purchase, returns, and customer experience. The headline takeaway was powerful:
If your post‑purchase journey has a dead end, your customer journey does too.

True Classic’s approach shows what happens when post‑purchase isn’t treated as an operational afterthought, but as a revenue, loyalty, and customer experience driver. Below, we break down the key themes, tactics, and lessons from the session.

Post‑purchase shouldn’t be the end

parcelLab’s CEO, Tobi Buxhoidt, opened the session with a mindset shift that framed the entire conversation: if post‑purchase is done well enough, it stops being post‑purchase at all. Instead, it quietly becomes pre‑purchase marketing for the next order.

True Classic leaned fully into this idea. Every confirmation email, tracking update, and returns touchpoint was designed not just to inform, but to keep customers engaged, confident, and ready to come back. A purchase wasn’t the finish line. It was just a milestone.

Building a high‑touch experience with a lean team

Despite massive order volume and cultural impact, True Classic has a surprisingly lean CX and ops team. They are proof that just because you have a smaller team, it doesn’t mean you have to sacrifice the experience you provide for your customers.

They make sure their priorities are clear. This means:

• Make customers feel informed and cared for at every step
• Proactively answer questions before customers have to ask
• Eliminate the friction that drives unnecessary support tickets

A strong post‑purchase journey shows that True Classic takes its customer experience seriously. Their customers receive proactive updates directly in their inbox or via an on‑brand tracking page, often before they even thought to check.

The result? Fewer “Where is my order?” tickets and more time spent on meaningful customer interactions.

Keeping tracking and communication on‑brand (and on‑site)

One of the earliest moves True Classic made was bringing the tracking experience back onto their own website instead of sending customers to third‑party carrier pages.

This is super important because it means:

• Customers stay inside the True Classic ecosystem
• Embedded links made it easy to start the next purchase
• Every post‑purchase email quietly drove incremental revenue

In fact, the team saw that every post‑purchase email generated roughly an additional dollar in revenue. This led to a 29% lift in the first year. It’s proof that tracking pages aren’t just informational, they’re commercial.

Proactive communication beats perfect delivery

Let’s be real: delays happen. What sets brands apart is how fast and how human they respond. True Classic implemented aggressive timelines (not aggressive messaging) for proactive outreach. If tracking didn’t update within 48 hours, customers heard from the brand first.

Instead of “Your package is arriving late.” Customers got: “We see the issue, we’re on it, and here’s what happens next.”

This approach helped:

• Reduce WISMO tickets
• Set realistic expectations in an Amazon‑shaped world
• Kept conversations positive, even when things went wrong

Crucially, these messages were never “do not reply.” Customers could always reach a real person if needed. This maintains trust when it mattered most.

Navigating carrier changes without breaking CX

As carriers came and went, including newer, less familiar delivery providers, True Classic stayed focused on one non‑negotiable:
The tracking link must work, and the delivery expectation must be clear.

When customers don’t recognize the carrier, or worse, don’t recognize the delivery method, it creates friction fast. The team even stepped in when a customer flagged that one carrier delivered packages from personal vehicles late at night.

This taught the team a valuable lesson. Choosing innovative or cost‑effective carriers is fine, but the brand experience doesn’t end at checkout. Expectations need to be clearly set with both customers and carriers.

International shipping: One size does not fit all

As True Classic expanded internationally, they quickly learned that customer expectations vary significantly by region. This led to making key adjustments, which included:

• Segmenting feedback by country and region
• Clearly communicating when orders are being shipped from multiple warehouses
• Using post‑purchase insights to decide which SKUs to localize

The payoff was significant. Local fulfillment didn’t just reduce costs. It dramatically improved delivery speed and customer satisfaction.

Using AI to resolve issues instead of escalating them

AI played a growing role in True Classic’s post‑purchase support, but with clear guardrails. This meant feeding AI richer shipment and order data, letting AI resolve early‑stage questions automatically, and using time‑based rules (e.g., 12+ days triggers resolution paths).

The team also learned what didn’t work well. For them, this meant that AI should not respond to angry or aggressive messages, and AI should not be used as a replacement for human judgment.

The key is balance. AI handles speed and scale. Humans handle nuance, emotion, and edge cases.

Returns that retain customers

Returns are treated as a second chance to win loyalty, not a loss to minimize. True Classic offers multiple options to give customers flexibility during the returns journey. Customers can either use:

• Happy Returns for fast, in‑person drop‑offs
• USPS with label or QR code fallback
• In‑store returns at flagship locations

But the real game‑changer was implementing uneven exchanges within their returns portal. Instead of forcing equal‑value swaps, customers could upgrade to higher-priced items or choose lower-priced items and receive the difference.

The impact:

• 2 out of 3 customers upgraded their exchange
• Average upside of ~$22 per exchange
• Customers stayed engaged instead of churning at the return

Protecting profitability without punishing good customers

True Classic’s free returns come with smart safeguards instead of blanket restrictions.

The team uses:

• Return limits over defined time windows
• Manual reviews for repeat or suspicious behavior
• Region‑specific rules where shipping costs were extreme

In some international cases, it was cheaper (and better for CX) to refund and let customers keep the product. This was framed as a “donate it” moment rather than a loss. More importantly, bad actors were handled individually. The experience stayed frictionless for everyone else.

Solving the pack problem

Bundled products introduced a tricky challenge: what happens when one item in a nine‑pack is defective?

Forcing customers to return everything wasn’t an option. Instead, True Classic built logic within parcelLab’s platform that allowed partial pack returns, triggered only when there was a legitimate issue.

This required deep system integration, but the result demonstrated lower return shipping costs, faster resolutions, and a dramatically better customer experience

The big takeaway

True Classic’s story proves that post‑purchase isn’t about emails, tracking links, or returns labels. It’s about continuity. When communication is proactive, data‑driven, and human, post‑purchase becomes a growth lever. And when done right, the journey doesn’t end at delivery or return. It quietly loops back to the next purchase.

Watch the full NRF session above to hear the full conversation between parcelLab and True Classic.

According to the National Retail Federation, eCommerce return rates were estimated to be around 19% in 2025, meaning close to 19 out of every 100 products sold online were sent back. This rate spikes even higher during holiday seasons, with fashion retailers averaging nearly 35-40% of sales returned.

If there were a magic button you could press to magically erase all returns, you’d do it. But unfortunately, there isn’t.

So, let’s take a look at the next best thing. Here are some strategic ways you can lower these return rates, so your brand can cut costs, improve the customer experience, and boost long-term loyalty.

1. Improve product information before purchase

It may seem like common sense, but one of the most effective strategies to prevent returns is addressing customers’ expectations on the product detail page. Poor product descriptions, visuals, and inaccurate delivery dates are major drivers of returns.

Retailers should:

• Use high-quality images and videos from multiple angles.
• Show products being worn on models of different body types.
• Include detailed specifications, dimensions, materials, and care instructions.
• Leverage technology for a virtual try-on process or “visualize in room” capability.
• Evaluate the accuracy of their delivery promises.

This tactic helps customers form accurate expectations. On one hand, it can reduce the chance that what arrives at their door looks or feels different from what was expected. Then, on the other hand, an improved delivery promise can prevent returns from coming back by getting to the customer by when they need it, not after.

2. Educate with reviews, guides, and FAQs

Customer reviews and user-generated content are potent tools to reduce return rates. Nearly 93% of shoppers use reviews to inform their purchases, and when they see others’ experiences, especially photos, they can better anticipate what they’ll receive.

Retailers should aim to have the following on their product detail pages:

• Detailed reviews with fit and use case notes.
• FAQs about length, fit, material stretch, etc.
• Cross-sell suggestions for complementary products.

Additionally, sending customers guides and videos during the post-purchase process can help deter customers who may return due to not understanding how a product works or is built. These all help manage expectations and discourage impulse buys that often lead to returns.

3. Collect and leverage return data to reduce future returns

Every return tells a story. Retailers that capture why a product was returned gain important insights they can use to prevent future returns.

It is helpful to leverage a returns management solution that can segment return trends, so your brand can act on them. For example, flagged high return segments can trigger targeted content, fit guides, or personalized rules to prevent repeat returns.

Retailers should track trends like:

• Specific product SKUs with high return rates.
• Common reasons for returns (fit, defect, expectation mismatch).
• Customer segments most likely to return items.

Feeding these insights into product development, sizing strategies, and pre-purchase content helps close the expectation gap that drives returns.

4. Tailor return policies without alienating customers

Return policies affect both purchase decisions and return behavior. However, they shouldn’t be so rigid that they drive customers away. Retailers constantly battle over whether they should charge for returns or make them free, and we are here to tell you, you don’t have to pick one way or the other.

Here are some ways to personalize the returns experience while also making sure you don’t hurt your bottom line:

• Offer free returns or instant refunds to loyal customers.
• Provide store credit incentives for new or first-time customers.
• Offer exchanges on items based on return reasons (e.g., didn’t like the color or wrong size)
• Use data to identify frequent returners and apply tailored rules (e.g., charge restocking fees for casual returns).

Returns reduction is a proactive strategy

Reducing eCommerce return rates isn’t about tightening policies and hoping for the best. It’s about anticipating customer needs and aligning retail experiences accordingly. From better product visuals to tailored return experiences, every touchpoint presents an opportunity to cut return costs while retaining revenue and customer loyalty.

Forward-thinking retailers view returns as a competitive advantage, not just a cost center. The brands that learn to fully personalize the experience will create customers for life.

…an enterprise retailer in North America needed to switch post-purchase vendors. Nothing about their setup was standardized – no Shopify, nothing simple, everything complex and enterprise-grade.

The dev team scoped the work. Then, they scoped it again because the estimate looked suspiciously easy. They couldn’t believe it would actually be that straightforward. But the work really did take just a couple of days. The entire migration was done within a single sprint.

As Angus Knights – VP of Product at parcelLab and the wizard responsible for this magic trick – recalls:
“The product manager was like: ‘I’ve never seen anything like this. This was easily within a sprint.”

That story contradicts everything most retailers believe about vendor switching. The common misconception is that changing post-purchase providers means a six-month nightmare of massive internal resource allocation and significant operational risk.

The reality however? The fastest successful migrations happen in about three weeks. “Ha!”, you’ll say, “Not with our super complex setup though.” But what if we told you the secret is not a simpler setup, but a smarter approach?

The expert behind the playbook

Angus Knights has witnessed hundreds of vendor switches from both sides of the table. Before leading product strategy as VP of Product at parcelLab, he ran the Solutions Consulting team – the technical group that works directly with retailers evaluating and executing migrations. That experience revealed clear patterns: what makes switches succeed, what makes them drag on, and why the conventional wisdom about migration complexity is usually wrong.

His core observation: a fast switch is all about the structured approach.

Why the traditional approach fails

Most vendor migration projects follow a predictable trajectory. They’re scoped at two months, then stretch to five or six. Departments argue about priorities. The temptation to redesign everything simultaneously turns a focused migration into a sprawling transformation initiative. Momentum stalls. Enthusiasm fades. Sometimes the project just quietly dies like the trip that never made it out of the group chat.

The fundamental problem is that post-purchase looks deceptively simple from the outside. You send some emails. You show a tracking page. How complicated could it be? Angus paints the reality:

“It’s like the duck, peaceful above the surface, legs frantically paddling below the surface. Because the reality is that a lot of the post-purchase experience is a partnership space. So many different third parties come together.”

Carrier integrations illustrate this hidden complexity perfectly. A retailer might think they’re working with DHL — one carrier, one integration. The reality is far messier.

“The retailer thinks they’re working with DHL, and we’re sitting here thinking, we’ve got 17 integrations with DHL, different aspects. So actually, what’s really happening below the hood? And if your technology provider isn’t helping you to navigate these waters, then they’re pretty treacherous.”

Different service levels run through different APIs. File transfers from 3PLs bundle data for multiple brands that needs to be separated. Data feeds stop without warning or explanation. None of this is visible to the retailer. They just know that their promised two-month implementation is now approaching month six, and they still can’t explain why.

The iterative alternative

The solution isn’t to plan more carefully for a big-bang migration. It’s to abandon the big-bang approach entirely. Angus explains: “Post-purchase experience is the living and breathing part of your whole proposition to the customer. So you need to find a way of making it manageable. It’s like, how do you do five minutes a day rather than two hours in one day and then forget, you know, it’s like practicing any skill. You want to incrementally build on this over time in the smallest steps.”

This mindset shift changes everything about how migrations should be structured. Build a habit instead of a new year’s resolution: Instead of trying to launch with a fully redesigned, optimized post-purchase experience, you start by simply porting what already exists. Then you improve incrementally, building momentum through quick wins rather than betting everything on a distant go-live date.

The 3-phase migration model

Phase 0: Port, don’t redesign

The first phase has one goal: get live with exactly what you have today. No improvements. No redesigns. Just migration.
This means establishing the order data flow, which is often reusable from your existing setup. It means building carrier connections, where the vendor’s expertise handles the underlying complexity. And it means porting your existing communications templates directly, HTML and all.

“So everyone’s got their message flows and setups done. There’s a baseline understanding of what they want to send, what information that should have in it, how that should be different for different markets for different carriers. So all of that is the version zero setup. That’s what you would migrate over. But coming up with that in the first instance can take quite some time. They’ve done a lot of work there. I think the key is not to try and redesign all of that.”

The timeline for Phase 0 is measured in weeks, not months:

• Order data setup typically fits within a single sprint
• Carrier connections are handled by the vendor
• Communications QA takes one to two weeks

The entire foundation can be operational before internal stakeholders even start questioning whether the project is on track.

One critical step before going live: establish baseline measurements for your key metrics. This before-and-after comparison becomes essential for demonstrating impact and building internal momentum for continued investment.

Phase 1: Expand your message arsenal

With the foundation in place, Phase 1 focuses on building out your communication capabilities using self-service tools. No dev resources required. This is thinking work, not coding work.

Most retailers run four or five different message types in their post-purchase communications. The most complex parcelLab customers, by contrast, run 40, 50, or even 60. That’s a factor of ten between baseline and what’s actually possible: a backyard compared to a stadium.

The approach is systematic:

→ Analyze the reasons customers contact your service team.
→ Build targeted messages that address each scenario before it becomes a support ticket. Address validation issues get their own communication flow.
→ Split orders where part of the shipment arrives before the rest. Packages that get misrouted. Customs delays. Trucks breaking down. Each edge case becomes an opportunity for proactive communication rather than reactive support.

“You want to pick off all of the different reasons for contacts from your customer services team that are still coming in – and understand the context of why or where customers are calling in for those reasons. And then you build targeted communications to kind of respond to each of those different reasons.”

Every new message type chips away at your contact volume while improving the customer experience. And because these are built through self-service tools rather than vendor projects, the iteration cycle is hours rather than weeks.

Phase 2: Connect, automate, personalize

Phase 2 extends post-purchase beyond communications into business system integration and intelligent automation. At this stage, the path diverges based on individual business priorities.

“It starts to diverge more based on what are the priorities for you as a business. Generally, there’s two main angles of attack. One is experience first, and one is revenue first.”

For revenue-first retailers, this might mean segmenting customers and speaking to different groups differently, implementing product recommendations within communications, or building specific flows for frequent purchasers and loyalty members.

For experience-first retailers, the focus shifts to automation around friction points: automatically creating customer service tickets when a carrier scan indicates damage in transit, triggering alerts for shipments stuck in customs, or setting up automatic refunds for missed premium shipping promises.

The specific mix depends entirely on your strategic priorities. There’s no single “right” Phase 2 – only the one that aligns with your business goals.

Phase 3 and beyond: Never done, always improving

Post-purchase is a living system that requires ongoing attention.

“It’s never actually done because things change and evolve in your eCommerce setup.”

Beyond Phase 2, Angus wouldn’t even strictly call them phases anymore.

“It’s more like having a backlog of topics and ideas that you would have business impact against and then basically continuing to iterate on those over time.”

Your carriers will change. Your customer expectations will evolve. New capabilities will become available. The retailers who treat post-purchase as a continuous improvement discipline rather than a one-time implementation are the ones who pull ahead.

What results look like

The first metric retailers notice after switching typically appears within a day: revenue attribution in Google Analytics from customers who visit tracking pages and make additional purchases.

“The first metric that people see is always a revenue number. Always in Google Analytics that shows the revenue impact of the customers who come back to track. That’s always the first number because after a day, there’s something on the scoreboard.”

The improvements can be significant – though Angus admits he was initially skeptical himself before seeing the data. The drivers become logical once you understand them:

→ Embedded tracking pages on your domain eliminate a click from the repurchase funnel and keep customers within your site experience.
→ More reliable email delivery means more messages actually reaching customers.
→ Better carrier data means more accurate, timelier communications.

“If you go from less reliable to more reliable, again, if you’re sending 20% more messages and then you’re on an embedded tracking page, that [uplift] suddenly becomes quite understandable. Because you’re actually just sending more communications more reliably and then you’re funneling your customer traffic in a better way.”

What consistently surprises retailers is how much headroom exists beyond their initial expectations.

“A lot of times when we improve or enhance things, we’re pleasantly surprised by how much headroom there is and how much we can actually grow into it. And this is one of those ones where people come in with a certain set of expectations and then often they break through those.”

Some reference points from parcelLab’s experience:

Metric	Observation
Typical message types before optimization	4–5
Message types with mature setup	40–60
Fastest documented migration	~3 weeks
App customer CLV vs. average	20–30% higher

The minimum viable migration team

Successful switches don’t require massive project teams. The minimum dream team includes three roles (tag yourself).

→ Logistics provides support for carrier credentials and connection details. They’re not doing the integration work. The vendor handles that complexity – but they need to provide the access and information required.
→ IT contributes a minimal but essential piece: the order data switch. This is typically the only development work required, and as the enterprise example demonstrated, it’s often measured in days rather than weeks.
→ An Experience Owner signs off on communications and owns the customer-facing output. This person might sit in eCommerce, digital, product, customer experience, or even customer service. The title matters less than having someone accountable for the end result.

The pattern that predicts the fastest, most successful migrations is cross-functional ownership – ideally through product management. Angus notes:
“Every time we see it owned by a cross-functional product person, we see those solutions get driven really effectively.”

Clear deadlines accelerate everything. Retailers with contract expirations looming execute faster than those with a comfortable runway. Some of the best migrations had real-time pressure:

“I think you need a deadline. I think you need to make this a priority for a period of time. (…) It was like, wow, our contract is expiring so soon with this other vendor. We need to switch like immediately.”

The warning signs for migrations that drag on: nobody actively pushing the project forward, too much time buffer in the schedule, and attempting to redesign simultaneously with migration.

The path forward

The fastest route to a successful vendor switch follows a simple principle: migrate what exists, then improve incrementally. Phase 0 ports your current setup. Phase 1 expands using self-service. Phase 2 automates and integrates based on your priorities. Phase 3 and beyond treats post-purchase as the living system it actually is.

The biggest delays come from the opposite approach – trying to redesign everything simultaneously, turning a focused migration into a sprawling transformation that loses momentum before it delivers value.

The required mindset prioritizes pragmatism over perfection. It uses deadlines as accelerators rather than sources of stress. It trusts the vendor’s expertise to navigate the hidden complexity that lives beneath the surface of every post-purchase implementation. Angus concludes:

“Switching post-purchase vendors is easier than most retailers think. Because there’s a team who’s done this before who will have your back.”