Let’s say you want to buy a pair of Nike Air Jordan 1s — undoubtedly the most recognizable Jordans of all time. What do you do first?
Chances are you answered: type “Jordan 1” in search. Correct?
Now, depending on your location, your search will give you the most relevant shopping items related to your query with prices, vendors and shipping details attached to a thumbnail of the shoes.
From there, you will most likely click on the lowest priced shoe in the design you favour, open the website and then go straight into “why is this so cheap” detective-mode.
Then you spend an hour diving down a deep rabbit hole, looking through reviews, company information or whatever helps you sleep at night, trying to figure out if the seller is legit, and if so you enter your credit card information, purchase the shoes directly from the site, and promptly send those puppies straight to your front door.
Typical standard shopping in the 21st century, but that’s the beauty of it.
The improvements to what’s available and how quickly you can get it, and also the competitiveness on pricing, is really working in the consumer’s favour. The responsibility has now fully shifted over to the seller to capture the attention of the buyer, and within that also breeds an opportunity for smaller sellers to be able compete on an even playing field with the behemoths like Walmarts and Targets of the world.
So, how do they accomplish this?
Well, there are likely hundreds of different web data outputs found on a single product page that each and every one of us as a consumer cares about or takes into consideration when purchasing a product without even noticing.
Now, with e-commerce penetration at an all-time high, retailers are taking advantage of the record amount of public e-commerce web data being generated by this industry, to make better decisions and gain full visibility over the market.
Focusing on one aspect of this analysis, like price comparison, through web data retailers are able to benchmark themselves against their competition by comparing and monitoring the prices of identical products directly competing with their own.
This information allows retailers to deploy dynamic pricing models that can react to the market in real-time and be better positioned to set attractive prices for their products that generate consumer interest, while maximizing profit margins.
This inevitably draws more consumer eyeballs to their website, considering price is the main driver that got us to click on that pair of Jordan 1s, we can safely assume that the same would go for any commoditised product.
While price is not the only determining factor involved in an online purchase, the specific data strategy of price comparison is one of the main drivers keeping our market open and competitive.
Think about it, considering that price directly correlates with the visibility, as well as the attractiveness of products listed on the online marketplace, it ultimately forces retailers to fall in line and keep the prices low enough to compete alongside one another. However they need to do so just high enough where the profit margins can still be managed appropriately.
Essentially consumers are the ones who dictate market prices. Every time a consumer pays for a product there are hundreds of data points that spider out from that purchase that illuminate a pathway for businesses to better understand what led to a successful purchase
Over time these data points are averaged out over millions of daily transactions occurring day-in and day-out, and as more data (or purchases) come in, the prices sway with the market and consumer behaviour in real-time.
Let’s take the sale of a microwave as an example. Over the course of 24 hours, three major retailers, Best Buy, Amazon and Sears, were all indirectly competing against one another for consumer interest in a GE microwave.
Over the course of the day, Sears kept the price of the microwave fixed, while Best Buy changed its price twice, raising it once at the peak shopping period, then lowering it back to the original.
The most dynamic of the three, however, was Amazon — a platform which sets the standard for online shopping — and during this period, the online marketplace changed its price of the microwave eight times to keep up with the ebb and flow of the market on that particular day.
It’s safe to say that Amazon was the most successful on the day, and set up a preview of how the market currently operates today. Products don’t sit on shelves anymore, salesmen do not have to come around to place new price stickers on the products, internal barcodes do not need to be updated.
So, if retailers do not dynamically set their prices at attractive levels for their consumers, they will not last long and their products will remain on “digital shelves”, gathering digital dust. This means the room for guesswork is gone, those days are in the past.
Retailers need to ensure their customers are getting their products on time, that they are readily available in stock, and as we’ve said over and over again, they must deliver on attractive price points if they ever want to maintain longevity in today’s overly saturated marketplace.
This is the way consumer expectations are positioned now, and this form of ultra-convenience has essentially shifted the way retailers conduct business, forcing them to react to real-time changes in the market, to meet the needs of this new consumer breed with open arms.
The only way to do this is by looking towards web data and the many insights it offers. A current and future trend that is not going anywhere, anytime soon.
Speak directly with Itamar on LinkedIn and find out how your business can achieve success using web data collection.
For more information on how web data collection can help your business, please visit Bright Data