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Get rid of those Excel files; a PIM is essential!

In 2013, 4.4 zettabytes of data were available on earth. In the next few years this will increase with approximately 40 percent to an astonishing 44 zettabytes in 2020.

How much of these data are used effectively? Currently about 22 percent. In 2020 it will still be a mere 37 percent. This is exemplary for the use of product data. It's not a surprise, as research for the Shopping2020 report shows that the majority of product managers uses Excel and manually enters their data.


We keep on collecting!

We prefer to collect as much data about our customers as possible, because the more we know about the customer, the better we are able to serve him. More and more firms are proudly showing off with their customer focused vision and their customer experience programmes. The data helps in customizing offers for their clients. We preferably also add some social media and new technologies to the mix. With fancy photo's and video's ofcourse, because images generate more revenue, right?


Images generate more revenue, right?

Wrong! Research shows that only 18% of Amazon's website visitors looks at the images, while 82% is focused on the text. It seems that a customer spends his time and energy in researching the specifications of products, but in many cases this information is incomplete or even incorrect. Customers often do not truely know what they are buying. They have to postpone the feeling that they've made the right choice until they have received the product.


Give and take

It's not really fair: we ask a lot of our customers, but what do we offer them in our webshop? We share information such as ' others also bought this' to increase sales. Social data is added to show off with our popularity. But what information do you provide customers to help them choose the right product? Think about specificiations of the products and how it has been packaged, how durable it is or what factory made the product.


Customer and government: hungry for information.

Even those questions about durability are becoming increasingly important, because the customer expects more. During a session on the congres ' Shopping Together', Frits van den Bos, chairman of Shopping2020's PIM expertise team said: "The customer is online 24/7. He orientates through websites and shops. He demands solid information, also regarding durability. And if the customer is not yet asking, the government will."

During the presentation, that started with the dubious phrase ' data is sexy', hunger for information is a central theme. A hunger that is clearly not only present on consumer level, but also on government level. The data are definately present, but usually these are fragmented over several proces-focused systems. Or, as Shopping2020's research pointed out, in Excel sheets. Often it is not mapped where certain files are stored, which ones are correct and how quickly and error-free they can be translated to the webshop.


Holistic approach

A PIM system, where product data is centrally stored and managed, can be a solution, although implementing such a system obviously should never be an objective on itself. It's definately not a sexy topic, no flashing technology of new feature to attract customers. However, it is indispensable if you wish to grow in these economically rough times. By automatically collecting, checking and managing product data, you can get products in a webshop much faster. Far fewer mistakes will be made. The customer service department will also be less pressurized, as customers have fewer questions.


A PIM system isn't sexy, but it is indispensable

A PIM system is often not easily implemented, but let's not start there. A PIM system is about the holistic mindset. You first need to develop a strategy that covers the entire organisation, where departments communicate with each other and where data can be used for multiple ends. Individually operating departments are growth's worst enemy: it is like every department invests the wheel on its own. By connecting people and systems, you can iteratively build on previous results, rather than endlessly searching for the right data, files and sources.



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