How do you discover your products?
16th February 1 Comment
Commerce is about buying products, right? And before you actually buy them, you first of all need to find them, don’t you? Of course! What sounds like a no-brainer is actually something not many shop owners think about. And I’m not talking about product search. Rather, I would like to talk about discovery, an aspect the solution of which will be at the core of successful commerce companies in the future.
The absolute majority of web shops that exist today follow a more or less strict adherence to nested categories. Why is this so? And why should this be discussed and questioned? Let’s go an very short time travel:
A little history lesson
Nobody knows when retail was invented, but it must have happened shortly after mankind had learned how to eat, have sex and kill each other. If someone wanted to make his living selling products to others, and his offering exceeded a certain size, he had to make sure to find the stuff people in his mom-and-pop store wanted quickly enough. Self-service was not invented until the beginning of the 20th century, and also here, a certain order had to be established. More and more refined strategies for building up and maintaining inventories were developed, bigger and bigger warehouses made it necessary to make sense of gazillions of different products. Until today, brick-and-mortar stores are organised along aisles and departments, with big signs making it clear to customers where to find their stuff.
When the first mail order companies such as Montgomery Ward or Sears started their business in the late 19th century and distributed their catalogs, this logic was adhered to. Pages for clothes would be followed by juwellery, weapons and horse harnesses (see this video of the so-called Montgomery Ward Wish Book to get an idea of how mail order looked in the days of yore).
About a century later, Amazon started their online book business, and, not surprisingly, modelled their website according to the taxonomy logic. There were a lot of categories reflecting the various genres of literature they were selling at the time. These days, now that Amazon is basically selling everything, a category structure is even more prominent. Software companies based their webshop software products on this structure – Intershop started their business at the time when Amazon went online in 1995 – and after that, generations of similar products have been created, in the wake of which hundreds of thousands of web shops were created around the globe that use a category structure in their offerings.
The development of computers and the web as we know it today have pushed forward another way of finding products one is looking for: blazingly fast and increasingly clever search algorithms. Modern database systems can race through millions of entries in no time, sifting all the pieces of text of products’ names and descriptions in one’s store for the search phrase given by the user. Modern technologies have introduced a variable degree of fuzziness to this process, allowing for decent search results even if a phrase is misspelled or synomyns are used. To top this off, modern product search engines make use of man-made matching-tables: Search for “maroon skirt” and they will output every product that features any shade of brown.
The biggest search engine of them all is not even located within online stores: Considerable amounts of product searches happen via Google, which accesses its database containing billions of pages to find products matching the respective query. If all goes according to plan for the shopowner, his products will rank well so that many of the Google searchers visit his store. (As an aside: one of the most important reasons the category structures mentioned above are used today is for Google to find a nice array of keywords in the corresponding URLs: welcome myshop.com/cameras/dslr/canon-cameras/eos.)
When a commerce business starts in 2012 and plans its inventory, it will mostly start with creating a new Excel sheet: products and their various attributes, category trees, price lists, etc. Not to be mistaken: This is a common-sense and time-tested approach – but it’s only one side of the coin.
When someone walks into a mom-and-pop store or moves through the aisles of a supermarket, he sees the products he is looking for but also other things! You see the products next to the ones you were looking for in the first place and might reconsider. You could walk into a department store without even knowing what you wanted or even needed in the first place! You just stroll around, let your eyes wander and – yes! – discover stuff! Why do you think IKEA is so successful? Because in contrast to many furniture stores that have existed before, customers can go for a walk through a fun home accessory wonderland and always (always!) buy something. You might have planned to have a look at some pillow cases, you end up buying a garlic press and some Swedish chocolate: that’s the IKEA effect, product discovery at its best!
The Excel-sheet/category approach is the exact opposite: if people know exactly what they want, understand the category structure they are faced with or use the right search phrases, they will pointed to the desired products. If they are looking for a bit of inspiration, however, they are lost.
Let’s once more delve into what has just been said about mail order. One thing I can distinctly remember is how my mother enjoyed sitting on the couch with a cup of coffee and the OTTO catalog (OTTO, which is now a multi-billion Euro retailer, sent out their first catalog in 1950 in Germany), casually flicking through the pages and seeing what they had to offer. She would write down the article numbers of the products she found interesting, pick up the phone and order. A couple of days later the parcel would arrive, and some weeks after that, the invoice had to be paid. Reading the catalog like a magazine, ie. even making it an enjoyable act is something that supports inspiration and product discovery. In the last years, however, the shopping experience centered more and more around male technophiles than inspiration-seeking female discoverers.
There are a number of strategies that try to support the discovery bit while still clinging to the old taxonomy model. This is where all shades of so-called cross- or upselling come in. Modern shop systems allow the administrator to manually interconnect products so that if a visitor sees the product details of the pot, he sees those of the lid – and vice versa. Other strategies try to upsell the customer by showing something underneath the shopping cart that is connected to what’s already in the cart – only much better and only slightly more expensive.
Modern recommendation engines go a step further and analyse the purchasing behaviour of statistically relevant groups of customers. If enough people have bought product A together with product B, those two will be presented together or even offered as a set at a reduced price – you Amazoners will know exactly what I mean.
A number of shops try to break free of old paradigms and focus on so-called product worlds. The German Tchibo chain, which began their business with selling coffee, now also has a large online store for clothing and all sorts of household items. The clou: Using the slogan “Every week a new world”, Tchibo offers a large, image-rich brochure containing products revelant for the current topic. People scroll through the offers – I should rather say immerge themselves in what Tchibo has to offer – and casually put some of the products into the shopping cart.
The Social Layer
Another aspect of the types of enhanced product discovery we will see in the future is the increasing importance of the social layer. Coming up with successful product worlds like in the Tchibo example is a sign of competent and imaginative product managers, and building a recommendation engine able to output relevant results is a technological feat, no doubt. In my opinion, however, this is just the tip of the iceberg and could be turned into a much better customer experience by integrating one’s social graph. If the choice of products is based on what I or people close to me have expressed in one of the various social channels, this would make for an unequally better product discovery experience. Just a small example: For most people it would work to be shown snow gear in December while browsing Tchibo. But what the system knew I was planning on going to Australia for Xmas?
There’s much more to be said about product discovery, which will surely happen on this blog. I’ve tried to cover some basics, most of which, however, need to be looked at in more detail. What’s also missing in this picture: The incredible rise of tablet salesm, which will also support models that center around product discovery, in a casual environment.
(Image by Evil Erin)