The blue jumper – a data story


September 15, 2020

Data drives customer experience conversions across channels. Get it right.

Thanks to COVID, seamless omnichannel experiences are more important than ever, with consumers increasingly looking to online and app-supported shopping. But for retailers, product information management (PIM) technology is only part of the solution. Why? The data that goes into a PIM platform will always affect the results that come out. For multi-channel strategies to work, data quality is a must. 

Comma’s head of data services, Arun Chandar, will be speaking at PIMpoint Digital 2020. He’ll explain three of the biggest PIM struggles – and how data quality can make them better. 

It’s all about achieving a single version of the truth: that golden record that’s available across every channel. Here, we look at why obtaining a single version of the truth is so important in retail – and the damage that disconnected product data can do through the story of a single product: a blue jumper.

When is a blue jumper not a blue jumper?

No, this isn’t a dad joke. We’re talking data – specifically how missing, inaccurate or out of date data can change your view of a product depending on how you’re accessing that information.

Thanks to digital, almost every product, sold by every retailer, can now be viewed through multiple channels. In store. Online. Via app. Through stock software. At the checkout. In a catalogue. The list goes on. 

In theory, the wonders of data should mean that regardless of what channel we’re using to view that product, we’ll see exactly the same information every time. It’s a jumper. It’s blue. It’s cashmere (classy) and it costs £79. 

A data story by Comma Group
The Blue Jumper via Comma

In reality, this isn’t always the case. Product data can be complicated, with multiple channels meaning multiple opportunities for one product to tell very different data stories. The result? Poor stock control, inaccurate cost analysis and a frustrating customer (not to mention employee) experience.

For example, let’s take that blue jumper. Online, product details say it’s 50% cashmere and machine washable. On the app, it’s marked as 75% cashmere and hand wash only. 

The customer experience impact

It might seem like a small error, but it’s confusing for the customer. Omnichannel shopping is now essential: people browse a product in more than one place before they purchase, and with different details on each they lose trust in the item, the app, and the brand. Is it 50% or 75% cashmere? Where is the mistake? Will it shrink after the first wash because the material content labeled is wrong? It damages customer confidence and can cost you a sale. 

Now multiply that experience by two hundred customers – and this is just one problem, within one data field. Imagine the myriad issues that can stem from incorrect data tags across all of your products. The wrong product showing in the wrong category, the right product failing to show in the appropriate product search, out of stock items appearing as in stock, women’s promotions being sent to people who have opted to receive menswear alerts… the problems range from irritating to loss-making. However, they always stack up to create a bad experience for everyone involved.

And with COVID continuing to disrupt markets, a seamless omnichannel experience is more important than ever. 

How to avoid data discrepancies? 

By making sure you have a single version of the truth.

One, central point where all data is stored, edited and accessed, available to every channel that needs it. Your blue jumper is a blue jumper, whether you’re looking at stock control or customer catalogue data: same price, same stock availability, same search tags, and sizing. 

Most retailers’ knee-jerk reaction to achieve this unified data experience is to buy in technology and, yes, technology is a big part of solving that problem. With PIM systems, you’re given a platform to manage your data from one place, but it isn’t a complete solution. 

Achieving a single version of the truth is a much bigger exercise than software alone can manage. The results you get out of your PIM can only be as good as the data you put in. The first step to making PIM work for your omnichannel strategy is data quality: a process to ensure that all of your product data is reliable, accurate, and relevant across every channel. 

So that you can be confident that your blue jumper is always a blue jumper, wherever it’s viewed. 

Guest post by Comma Group, a specialist consultancy providing advisory, delivery, and support services for product information management, data governance, and data quality. Comma is a sponsor of #PIMpoint Digital.