Tag Archives: product returns
Recently, I ordered a pair of athletic pants from a high-fashion, online retailer. The pants were a well-known brand and cost $96.00. The package arrived within a few days. However, when I opened the box, I found it did not contain the product I expected. The brand and color were correct, but it was not the style I’d chosen. Disappointed, I wrote the retailer, explaining the issue and requesting the correct product. Then, I returned the incorrect product.
According to recent research, the average vendor’s “cost per return” is $20.00. That means that my return was a Margin Killer for the retailer.
Three days later, the replacement delivery arrived. Whoop there it is… Disappointment number two. It was the exact same incorrect product. Yet another Margin Killer, Return Number 2. Another $20.00 in costs for the retailer. What would it take for this retailer’s logistic team to avoid repeating their error? Could they scan the product? Could they use a QR code, a bar-code or some sort of picture?
I returned the incorrect product for the second time. Eventually, shipment number three reached my home. Can you guess what was in the box? Yes, the same incorrect product, again, for the third time. The Margin Killer: Return Number 3. For this retailer, the math is simple:
Return 1: $20.00
Return 2: $20.00
Return 3: $20.00
Total return cost: $60.00
Revenue = Possibly zero?
Funky side note: When browsing stores downtown on Saturday, I found the correct pants in a SportScheck store, and for ten dollars less! So remember, the modern customer is demanding, always-connected and shopping on an “Informed Purchase Journey”.
So how can I learn more?
If you work in retail technology, you will find rich information about this purchase journey at the Informatica World 2014 conference. The Retail Path track will feature insights from companies like Nike, Avent, Discount Tire, Nordstrom, Geiger, Intricity and Deloitte. Experts will share ways to leverage your data to boost your sales and heighten customer experience. The conference even has a dedicated MDM Day on Monday May 12 with workshops and sessions showing how vendors, distributors, retailers and individuals interact in the “always-on” connected world. Make sure you have a spot by signing up HERE.
Do you know how good your multichannel data is? This blog covers four business objectives when accelerating multi channel commerce and which quality of product data is needed to deliver to that and a summary of questions to ask when establishing your strategy. These questions help ecommerce managers, category managers and marketers at retailers, distributors and brand manufacturers ask the right questions on product and customer data when establishing a multi channel strategy.
The Multichannel Challenge: Availability of Relevant Information
At every customer touch point, the ready availability of product information has a profound effect on buying decisions. If your customers can’t find what they’re shopping for, don’t understand how well your product meets their needs, or aren’t confident in their choice, they won’t complete their purchase.
When customers are researching or actively online shopping for products, research says 40 is the magic number:
40 % of buyers intend to return their purchase at the time they order it.
40 % order multiple versions of a product.
40 % of all fashion product returns are the result of poor product information (Consumer electronics are 15,3%; Sources: Trusted Shops, 2012, Internet World Business 7.1.2013)
All the high-quality product data in the world is useless if an organization cannot leverage that data for quicker time to market, improved e-commerce performance, and greater customer satisfaction.
Four Business Objectives When Accelerating Multi Channel Commerce
This white paper comes with four common use cases that illustrate typical business objectives within a multichannel commerce strategy. When looking into your product information, here is a list of questions you might consider.
1. Increasing conversions and lowering return rates by ensuring that customers can access product information in an easy-to-consume form.
- Where is the flawed content coming from?
- What tools and incentives can we provide for suppliers to maintain the high quality content?
- Which data quality processes should be automated first?
- Do we need a bespoke data model to fit your requirements?
- Can we effectively use industry standards for communicating with suppliers (such as GS1 or eClass)?
2. Lowering manual processing costs by merging the best product content from multiple suppliers.
- How many product catalogs do we have and what are the processes that slow us down?
- Who is responsible for the quality of the product information?
- How can we define and enforce the objective and measurable policies?
- Which supplier has best descriptions / certain translation, high-quality images / video / etc.?
- How do we collaborate with our large and small suppliers to achieve best data quality?
3. Growing margins through “long tail” merchandising of a broader assortment of products.
- Can we automate product classification?
- Which taxonomy will work best for us?
- Do all stakeholders have visibility of data quality metrics and trends?
- How can we leverage information across all channels and customer touch points, not only ecommerce?
4. Increasing customer satisfaction through more consistent information and corporate identity across sales channels.
- How should we connect customer and product information to provide personalized marketing?
- How can we leverage supplier and location data for regional marketing?
- How do we enable crowd sourcing of comments, reviews and user images?
- What information do internal and external users need to access in real time?
Find more information with the complete white paper on multichannel commerce and data quality.