How does any ecommerce store compete with the veritable giant known as Amazon?
They do billions of dollars in sales every year. Five years ago they employed over 30,000 people, but now have over 110,000 employees. One-quarter of all office space in Seattle is dedicated to Amazon.
As of now, they are worth more than all major US department chains put together.
But the most amazing thing about them is how they use data to improve the customer experience.
They utilize collaborative filtering engines (CFE) to analyze items that have been purchased, find products in shopping carts or wishlists, gather product reviews and connect it all to your search habits.
It’s like they know exactly what you want before you even know you want it. But this shouldn’t dissuade smaller retailers from sticking their toes in the water.
While Amazon may have access to a lot of data, smaller stores have access to the same data. They just may not know it.
Here’s how a small ecommerce store could potentially keep up with the likes of Amazon.
How Amazon Uses Data for Better Sales
Amazon was one of the first companies online to really use data to make the shopping experience as seamless as possible.
They have really leveraged data and AI over the years to create a customer experience that few other retailers can match.
Here are a few of the things that really set them apart when it comes to data:
Anticipatory Shipping Model
Amazon’s patented anticipatory shipping model uses big data to predict what products you’re likely to buy, when you may buy them and where you might need them shipped.
According to the patent, their forecasting uses data from your prior Amazon activity to populate its predictions.
This includes things like:
- Time spent on site
- Duration of views
- Links clicked and hovered over
- Shopping cart activity
This predictive analysis allows them to anticipate needs, which in turn increases their sales and profit margin and reducing delivery time. They make money by knowing what you want before you do.
Supply Chain Optimization
Not only does Amazon predict your orders, they also use data to link with manufacturers to get you products faster.
Amazon uses data systems for choosing the warehouse closest to the vendor (or the customer) in order to drop shipping costs by an average of 10 to 40%.
They use graph theory to decide the best delivery times, routes and product groupings to lower shipping expenses as much as possible.
Amazon also uses data for price optimization in order to attract more customers and increase profits (which they do by an average of 25% annually).
Prices are set according to your activity on the website, as well a bevy of other metrics like competitors’ pricing, product availability, item preferences, order history and so on.
Amazon also analyzes and updates their product prices every 10 minutes or so, which allows them to offer discounts and adjust prices as needed to drive more sales.
If all of this sounds impressive, it’s because it is. But it’s all made possible by the power of data. Without it, Amazon is just like any other store, really.
And data is also the key for smaller stores, too.
How Ecommerce Stores Can Keep the Pace
The only way to keep up with Amazon is to become what VentureBeat calls a “data-centric” company.
They describe a few key lessons that ecommerce stores can take from Amazon’s latest merger and their use of data for sales:
- Data will be needed to understand what drives consumer preferences and behavior
- Deep data gives you the competitive edge over other companies in your sphere of influence
- Depth and accuracy of your data will matter for effectiveness
The good news is that data is accessible to any retailer who knows how to get it.
Web scraping, for instance, allows you to gather data from competitor sites (including Amazon) for price comparisons and product details.
You can then use this information to offer discounts and optimize your prices in the same way that Amazon does.
Depending on the service you use, you can scrape this information as many times as you need to get the most accurate price data.
They will even track this information over time to find patterns.
You can also collect product reviews and ratings, as well as information from social media sites to offer insight into what your customers want, what you think they would buy again, or what they would skip.
If you scrape your own product data, you can figure out what they have already bought and offer product recommendations.
Almost anything that Amazon is doing with their data can be replicated by scraping data from the web.
In fact, Amazon does this all the time. If they want to know how their products are performing against BestBuy or Walmart, for example, they will crawl product catalogs from these two sites to find the gaps in their own catalog.
But the one thing that Amazon does well in terms of getting data is that they know how to use it once they have it.
This means getting the cleanest, most organized data you possibly can. You need product data that’s easily readable and decipherable, for example.
You also need the ability to gather new data from multiple sources as often as you need it. Amazon reviews their competitor data frequently enough to update their site every 10 minutes.
The fact of the matter is that you could be doing this, too.
The biggest thing that Amazon is doing that sets them apart in today’s market is using data to drive their purchasing, marketing, and sales decisions.
But the good news is that any company that can get their hands on data can do these things, too.
You don’t have to be the size of Amazon to do what Amazon does. You don’t need to be Jeff Bezos to drive sales.
You just need access to the right information.
You may not necessarily have the same influence that Amazon does in the marketplace, but there’s no reason why you can’t use Amazon’s best practices to gain an edge on your competitors.
Data is what powers Amazon’s sales, and that same data can be leveraged to power your sales, too.
The thing to remember is that you want to collect as much data as possible, but it needs to be clean, structured, and applicable to your services.
You don’t just want to use any data. You want to use the right data.