Ever since George Orwell penned 1984, we’ve been overly concerned about what either governments or big companies know about us. But is it so odd for a company to know your preferences?
I mean, we absolutely love it when we walk into our favorite coffee shop and the barista says, “Your regular?”
When you shop anywhere, there is a record of what you bought. It’s just that when you enter an online store, the physical rules of time and space do not inhibit store owners.
In the physical world, it’s difficult to track when a customer picks up an item and examins it. But in the online world, it’s extremely easy to see where someone goes on your website.
So, what’s the difference between what your small town cafe does to make your visit personal and what Amazon does? Very little. The only difference is, you’re one in a million to Amazon.
So, how does Amazon make your visit to their site personal and use that to make money? Let’s take a quick look.
1. What Is Big Data, Really?
We hear it in the news media all the time. Ever since Snowden blew the lid on Prism, big data has been a scary term for most people.
When your government spends around $5 billion to spy on you and your fellow citizens, that doesn’t do much to make you feel good about the associated terms.
But what the government collected through Prism and what Amazon collects through its services are two different kinds of big data.
Two Different Kinds: Consented and Stolen
The government collected data without permission and “bugged” people’s phones and broke into encrypted emails. They didn’t own the services where they collected the data.
And their purpose was mainly to “catch terrorists.”
Amazon owns the services where it collects data. This data is not any more personal than what a store merchant could gather if they followed you around and wrote down what you picked up in their store.
Their main purpose is to understand marketing trends and put together a big picture.
Both groups collect sizeable amounts of data — hence “big data” — and they both need large resources to collect it.
What’s the biggest difference? Ownership.
By browsing a website owned by Amazon, you’re consenting to Amazon farming your shopping data. (Unless you use Tor and a VPN.)
There are no ethical barriers to this kind of data collection. It’s when that line of consent and ownership is crossed that people become wary and untrusting.
2. What Big Data Isn’t
There are a lot of misconceptions out there about what Big Data is. And the myths behind the words are easy to dispell.
It’s Not Just a Bunch of Data
Yes, the name big data comes from the fact that companies collect a whole lot of data. But it’s not the amount of data that makes it valuable.
Really, if we judged a book by the number of words, the dictionary would be on the best seller’s list every month.
What makes both a book and a set of data valuable is the big picture they each create for the user. The meaning behind the data is what’s important about big data.
It’s More Than One Technology
When picturing big data, it’s easy to picture some supercomputer brain churning out reams of data. But even at the NSA, there is no FATE supercomputer directing everything.
Big Data is a collection of technologies and not just one technology. This means that how Amazon collects, analyses, and gleans meaning from data varies from situation to situation.
The government and Amazon could be using vastly different technologies to collect and analyze the data they use.
Big Data Isn’t a Fad
Until internet technology quits relying on numbers and calculations to operate, big data is going nowhere.
The great thing about big data technology is that it’s always evolving. And it evolves quite naturally.
And as long as billions of people access the internet every day, there will be a large volume of data to analyze.
3. How Does Amazon Use Big Data?
It’s no accident that Amazon is one of the most successful e-commerce websites out there. And big data analytics is one of the chief reasons they’ve done so well.
But what parts of Amazon actually use big data analytics?
Supply Chain Optimization
Amazon isn’t always using big data to analyze personal shopper data. They’re also attempting to streamline their fulfillment services.
Running logistics is an art and a science. Coordinating between suppliers, warehouses, your own e-commerce website, and ensuring fast delivery are all of equal importance in logistics.
It’s a massive operation and the only way to keep track of all the data is through analytics software.
Specifically, Amazon uses the data to determine things like the closest warehouse to the customer or vendor. They also use technologies like the graph theory to work out delivery schedules, routes, and product groupings.
What if you could predict when a customer is going to buy something and already have it in processing before they buy it? This is the question Amazon asked and they used big data to figure out how to do it.
Essentially, Amazon knows what warehouse they should place items that you will most likely purchase. If you live in Alabama, they will place your next order of dog food at their Atlanta shipping center in advance of your order.
Ad Optimization and Product Recommendations
To maximize ad revenue, Amazon has to place ads in front of customers and those ads must interest the customer. Otherwise, nobody would click on an ad.
The only way to determine if an ad will be useful or interesting to a visitor is through their browsing data. Amazon does use the browsing data from their own websites, but they also buy data from other companies.
With this data, they can make predictions about what you will most likely buy or what sites you would most likely visit. Their machine learning algorithms then filter ads and products based on your preferences.
Prices are constantly shifting on Amazon. In fact, an item’s price can change eight times during a 24 hour period.
Big data analytics helps Amazon determine when to drop prices to make more sales happen. They’ll track when the most people will be on during the day, how much of each product people will buy, and what kinds of products they will most likely buy after a purchase.
4. How Can I Use Big Data Too?
Big data isn’t just for the big boys. Small businesses can use big data too.
Improve Your Products
Surveys are an important part of product development. But what about product improvement?
You should always be working to improve your products and services. And the only way you will know how your product functions in the real world is by asking customers about it.
If you output lots of products, you have a ton of potential product information.
But without analytics software, you won’t be able to pull meaning out of your data. You need the software that collects the data and the software that analyses the data. Two different technologies.
Optimize Social Media
If you garner a large following on social media, how will you know what’s working and what’s not?
Sites like Facebook already offer a small amount of data on your users, but you will need more in order to optimize your campaign.
Media analytics like Synthesio exist solely to examine your posts and track things like reputation, competitor share, follows, likes, and other trends.
But big data can reveal more from social media than just how to optimize your accounts. You could identify customer satisfaction with your product or service. You could identify major problems consumers see in your product or service.
You could improve many aspects of your product or service with all of the data available through social media.
Real-Time Call Tracking
Not all big data technologies analyze past data. Some data needs to be analyzed instantly.
If you run a business that uses customer representatives, you will want to show real-time information to your rep. But without analysis software that does this for you, it’s impossible.
For example, call tracking software like Ringba will track even your marketing calls and give you immediate feedback. You can use this information to direct your calls and increase your chances of sealing a deal or solving a customer’s problem.
Why You Should Do Big Data
Amazon’s millions are a good example of how companies should use big data to their advantage. You can’t get ahead of the competition without using the tools you already have.
If you enjoyed this article, check out our other articles on e-commerce here at shoemoney.com!