As FBA sellers, you’re always looking for a way to improve, right? Sometimes the smallest tweaks to how you do things can yield results which blow your former performance out of the water.

Predictive analytics present an opportunity to make those performance-enhancing tweaks in your business. Put simply, predictive analytics allows you to predict needs and behaviors based on analysis of data over time.

For FBA sellers, having some degree of forecasting accuracy allows them to be ahead of the curve, to be proactive rather than simply reactive. Let’s take a look at how predictive analytics are helping FBA businesses.

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How Do Predictive Analytics Work?

First of all, let’s take a quick look at how predictive analytics actually work. Much like the term “big data”, predictive analytics has become a popular subject, but often within the realms of other “buzzwords” which aren’t fully understood.

The fact is, predictive analytics have been used in one form or another for years. If you’ve applied for credit and seen the role that your credit score plays in the terms you are offered, that is predictive analytics at work. In short, they’re used to predict your relative risk of default.

Predictive analytics work by accessing the vast banks of data we have available. Since credit scores first began in the 1950s, there has been ever-increasing amounts of possible data to analyse, bringing us to the “big data” of today.

Analytics programs work by using machine learning; they analyse and learn from data over time in order to be able to make predictions with some accuracy.

Predictive Analytics for FBA Sellers

As you can probably surmise, predictive analytics can have great implications for FBA sellers and eCommerce in general. They make the difference between guessing and data-based decision making.

Amazon itself uses predictive analytics programs which are built into the service, but for areas where sellers might want more or better data, there are several third-party software options which work by utilizing predictive analytics. Of course, if you’re also selling off Amazon via your own website, there are still more options available to you for data accuracy.

Here are some examples of predictive analytics at work for FBA sellers:

Better Targeted Promotions

For an FBA seller, the more sources of data you’re able to tap into, the better when it comes to creating more targeted promotions. Predictive analytics allow sellers to really hone in on the right audience and messaging rather than simply pushing out ads and hoping some stick.

Customer segmentation has become an important strategy for any business. The fact is, not everyone is your customer and not all of your customers are motivated by the same things. Predictive analytics can correlate data from multiple sources to build a better picture of what your customer segments look like and what types of promotions will be effective for each.

Assuming you have created a website to help you boost your brand profile, there are a number of tactics you can take outside of Amazon to help you gather better customer data. For example, check out eCommerce sites such as Fabletics which manage to gather customer data in a fun way, by having customers go through a quiz.

As you can see, not only does the quiz help Fabletics recommend clothing based on predictive analytics and the answers the customer gives, but it helps them to segment their customers so they can be relevant with any messaging they send them in the future.

Predictive analytics for targeting can also be garnered through browsing behavior combined with other data points. For example, if you sell clothing and you know the location of people browsing, you’d have a good idea of the types of clothing that are going to be appropriate for the climate they are living in.

A key thing to remember, no matter what kinds of programs and algorithms you’re using to source predictive analytics, is that while it can give you some advantages when working well, the data is by no means perfect. Machine learning means that these algorithms get better over time, but it’s also worth testing out any changes which might need to be made.

Product Recommendations

Amazon itself uses predictive analytics in a few different ways, most notably with their product recommendations. While you as the individual seller don’t have control over these, they can certainly help you out when they’re recommending your product.

As you will know from buying on Amazon, the more purchases you make, the more extensive your “recommended for you” page becomes. This is machine learning in action — Amazon is monitoring over time what your purchase habits and interests are. The more data they gather, the more accurate their recommendations become. You can also see this in action with offers or bundle deals during checkout.

Repricing Strategy

When it comes to boosting sales, winning the buy box is an effective strategy to get to the top. In fact, 70 – 82% of all sales on Amazon are made through the winner of the buy box. Price is one of several factors that go into how Amazon determines who the buy box winner is (they don’t disclose their exact measures), this means you need a reliable way to remain competitively priced.

Many FBA business owners turn to repricing as a strategy for staying competitive. The caution is that no one wants to be in a race to the bottom where your margins become so diminished that there’s no point in competing. For this reason, some sellers go for manual repricing (inherently time consuming and unreliable — you can’t be watching Amazon all the time). Some use a repricing tool that is rule based (e.g. “price my product one cent lower than the next cheapest price”). Finally, there are repricing tools based on algorithms which collect data over time.

Wiser has a tool which it describes as “predictive buy box”, providing sellers with a more targeted way to reprice, based on predictive analytics. The tool takes into account a number of different factors (including seller status and competitors) to come up with the highest possible price which will still get you the buy box. The idea is to both maximize sales and maximize margins. Why be the absolute cheapest if you don’t have to be?

Inventory Management

Now this is something we at Forecastly know a lot about. In fact, our entire tool runs on predictive analytics to ensure that inventory management is optimized. This works by analysing your sales and inventory data over time. The longer you use it, the more data to analyse and the better the predictions become.

Running out of stock can be a costly mistake to Amazon sellers. Not only do you lose sales, but you can lose your position at the buy box and then have to work hard to make your way back once you have product back in stock. Forecastly helps by providing recommendations on when to buy more inventory and how much you should buy. It also helps you to foresee future sales and inventory issues.

Sales Performance

Sometimes, when it comes to making decisions about what product line to go into next, you wish you had an accurate crystal ball. If you haven’t sold the product before, where can you get accurate data to suggest whether you should or not?

Predictive analytics are again here to help. By careful analysis of factors such as sales performance, competitors and product reviews, you can get a very good idea of what your next product should be.

Jungle Scout is a tool which helps with just that. It can be a saver both of your time and money as you don’t need to rely on trial and error methods to find a new product to sell. Like Forecastly and Wiser, this is a third party software which works for FBA sellers and others.

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Final Thoughts

While no data is ever going to be perfect, predictive analytics have come a long way in providing predictions with some level of accuracy.

Machine learning helps to improve predictive analytics tools over time and produce better, more useful predictions. You can observe this in your own Amazon buyer account.
Take advantage of the tools available for making sense out of data. In an age of “big data”, one of the challenges is ensuring that you’re paying attention to the right data, which is where tools designed for honing your targeting, purchasing, inventory decisions and more, can help.

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