How the Data is Collected and Used by the Retailers?
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Aug 10, 2018 | 582 Views
The challenge of pricing has entered a new era and every industry should learn from what's happening in fashion right now. While competition with Amazon often gets a lot of attention, industry upheaval due to the rise of e-commerce is much broader than that. Retailers need to embrace external market data, in real time, in order to succeed.
Consider this the ultimate cautionary tale for modern retailers, whether they sell pencils, groceries or cars. It wasn't all that long ago that shoppers avoided buying fashion online. When you're picking out clothes, you often want to see how they feel, see how they look on you, and try different options. This relationship between consumers and clothing helped draw shoppers to stores, even as e-commerce grew. People purchased what was available to them locally, within driving distance.
Now, buyers can easily have the best of both worlds. They can go to a store, find the items they want, then leave and buy those items online. This idea, "showrooming," has been around for years. But new technologies have given it massive new power. Shoppers have an unfathomable number of options at their fingertips due to the rise of e-commerce, including cross-border shipping. They're using it 82% of consumers do research online to inform their purchase decisions. So ultimately, their money goes to whoever gives them the best deal on the best merchandise.
Take, for example, this designer dress. It's available at different prices from retailers all over the world, and within the United States.
This helps explain why some European fashion e-retailers like ASOS, Net-a-Porter, and Farfetch as well as traditional bricks and mortar retailers like Selfridges and Harrods who now ship across borders are stealing U.S. market share from department stores like Neiman Marcus and Saks Fifth Avenue. Many Americans haven't heard of competitors like Farfetch that don't have physical stores in the U.S. But when shoppers look for prices online, they discover these international websites. Every day, less market-aware companies lose customers, while more digitally savvy businesses optimize prices and products to be globally competitive.
In a 2018 report from the Business of Fashion and McKinsey & Company, fashion designer Tory Burch noted how big a change this is for the industry. "It used to be the department stores who were in charge; now the customer is charge because technology has really given the customer access to so much information," she said. Today's buyers have high expectations, including with cost, since "they can go on an app and compare pricing, globally, instantaneously."
Sixty percent of executives surveyed in the report said a priority for their spending this year is in "omnichannel integration, e-commerce, digital marketing," while only 26% said in-store experiences were a priority. The same principle applies to just about anything that still brings shoppers to stores. While bricks and mortar will never die, e-commerce data grows every year. So the best practice is for retailers is to use these same emerging technologies to their advantage. They should implement data solutions that provide them with the information to see prices of the same or similar products they're selling, and to make decisions every day based on the competitive marketplace. Sellers also need to know why prices are fluctuating worldwide, including factors like global premiums and exchange rates, as well as discounts.
With the right technology in place, retailers will empower themselves to be every bit as smart and well informed as their consumers. They'll adjust price points to remain competitive. For today's retailers, in fashion and beyond, these kinds of data-driven partnerships are a crucial best practice. But they're also more than that. They're a survival issue to compete in the digital era.
The best way to understand what data to collect is to understand the principles of maximizing profit in a brick-and-mortar and online context. In a brick-and-mortar store, you offer the same shopping layout and experience to all customers, so your goal is to implement the layout that maximizes the chance of a sale for the average customer that walks into that store. You can do a lot of this by just knowing a breakdown of sales for each store, you do not need to tie each sale to a customer. However, there are also ways to personalize the experience for customers in a brick-and-mortar context. For instance if you knew their identity the moment they walked into a store.
In the online context, you can personalize the experience for each customer as you know his identity once he logs in, so your goal is to understand the customer as much as possible to show him the right message, at the right time, at the right place.
Given the principles above, there is a hierarchy of importance of data when it comes to understanding customers that is ranked based on how correlated an action is to a purchase intent:
Purchases (what did they buy?)
Add to cart (what did they add to their cart?)
Product click (what products did they click on?)
Product view (what products did they view?)
The most important data to collect is purchase information (and of course the means to contact the customer via email, SMS etc.). In brick and mortar stores, this is done through loyalty programs, because otherwise you do not know who bought what. In online stores, this is usually collected, except when you sell through a third-party like Amazon.
The next level of data add-to carts, clicks and views can be tracked online using clickstream tools like Google BigQuery and Adobe Marketing Cloud. In brick and mortar stores, the use of beacons and RFID tags are starting to gain popularity in tracking things like number of times a product is lifted from the rack, amount of traffic in a certain area in the store.
There is another type of data used to determine pricing, sizing and product design strategy. This is information about you and your competitors products, things like ratings, reviews, colors, pricing etc. In the online context, this is used extensively when selling on marketplaces like Amazon. In the brick-and-mortar context, brands rely on research companies to give them such intelligence.