Regardless of whether you’ve got a grounded store or you are just dipping your toes into e-commerce, there’s a chance that you have thought about taking advantage of machine learning. Rightfully so, because
machine learning is very sophisticated technology that offers those in ecommerce a number of advantages. Today, however, we will be discussing how you can use machine learning in order to optimize your prices. We’ll go over topics such as why you may be struggling with setting the best prices, what exactly machine learning is, what price optimization actually is, how you can use A/B testing alongside machine learning, as well as an example of how machine learning is applicable to the ecommerce world.
So, let’s begin with why you may be having difficulties with setting the best prices for your items.
You may have come across some texts about different types of pricing strategies and learned how they can bring you lots of success. Some of these may have even inspired you enough to try to incorporate it into your own store immediately. There’s nothing to be ashamed of as you are merely seeking out those same results. However, the problem with those articles is that they don’t elaborate on the fact for every pricing strategy, there are advantages and disadvantages that differ depending on the company. After all, every store is going after a different goal. For instance, while some may be trying to make the most profit they can from each item, others may be trying to capture a new market or a new area or they may be simply looking to raise their market share as a whole. Regardless of your objective, though, know that there is a pricing strategy that will work wonderfully alongside it; the best way to figure this out is through machine learning technology. Indeed, whenever you are trying to figure out how to price your items, questions such as the following may arise:
-“What should the price of my items be if I’d like to raise my sales by a certain percentage?”
-“Which price is the fairest when looking at the market activity occurring at the moment?”
If you are looking to pricing your items correctly, you will need facts to back up the answers to these questions rather than choosing an answer based on intuition.
So, what is machine learning and how can it help?
A kind of artificial intelligence, machine learning is a method that you can utilize in order to enhance how well a system works over some time, depending on the experience. When it comes to ecommerce, it can help you get a much better understanding of the processes that you are currently working with. Indeed, it can offer you so much more such as what it is that customers do and don’t like, along with everything else that falls in the middle. It is also a great way to figure out in what way your customers prefer information to be given to them. This is made possible by trying out and conforming the processes that you have in place in order to realize and learn patterns. Through these patterns, it is able to make predictions regarding which moves are the smartest to take next, based on cold-hard data. Over time, by using the information from your store, your shoppers, as well as your customers, the machine learning system will be able to improve the way that you think when it comes to pricing as well as conform in a way that better corresponds to each customer. In addition, it lets retailers come up with advanced pricing strategies that way they can realize the objectives that they are going after much quicker and with less effort.
Now, what does it mean to actually optimize prices?
If you are looking to
optimize the prices of your items within the ecommerce store, then you depend on data analysis if you want a more solid understanding of the way that your customers will react to various prices as well as set the most optimal prices for your company, which depend on overall business objectives.
The thing is, when ecommerce first started to make its mark, retailers could simply working with pricing strategies such as cost and strategy or the power of nine, for instance. Now, though, due to technological advances, retailers can expertly figure out what the demand for an item is in comparison to the price that they are asking for. As a result, they can figure out how marketing campaigns will influence both their sales and their revenue, forecast the most optimal price point for an item regardless of the time period, or how much an item should be sold for in order to make a certain amount of money during a certain period of time. Indeed, ecommerce firms can take into consideration what the local demand is, what the global demand is, what the seasons are, the costs to operate, the objectives, the prices of rivals, and even the weather. Through it, they will be able to figure out what the most solid first price for an item will be in order to make the most revenue as well as profit, what price would be the best to keep the items, as well as which is the best discount price for your items depending on customer’s willingness to buy.
Now that we know that machine learning algorithms gather both information and data about pricing trends by learning about what is occurring inside and outside of your store, you will be dealing with a lot of information.
Let’s take a look at an example.
Suppose that you have an online shop that sells shirts and you are interested in finding out what the most optimal price for the following season would be. After all, you have a lot of competition, so you want to make sure that you have the best prices.
Therefore, begin by collecting information via machine learning. Give the algorithm some data so that it can learn as well as conform accordingly. For example, give it information regarding your rivals’ pricing data, your transactional information, previous promotions, your inventory, as well as the reviews from customers. Make sure that the information that you are providing it with, though, goes hand in hand with your goals. For instance, if you are looking to raise prices, then it would definitely be important to provide it with both transaction and competitor data.
Indeed, prior to the algorithm being able to make predictions, it must understand the criteria that you have established. For instance, if you don’t want your shirts to be sold under a certain price, you need to make the system aware of this. With the help of these rules, the algorithm will have a much better understanding of your business model so that they properly apply the outcomes from the information.
As soon as those objectives have been established, you will have to begin modeling your information. This means that the information that the algorithm had gathered in the past will now be used to make models. There are a variety of models that are used today such as logistic regression as well as GLM. Choose the one based on the complexity of your data.
Through these models, the machine learning system will be able to make sure that you can easily and quickly locate the data that you are looking for depending on old information. As soon as the system has been trained well, you can begin predicting the most optimal prices for your new items. As a result, you will have all of the information that you need for your shirt company that go hand in hand with your goals.
Since pricing is so important to how your business expands, you want to make sure that you do it correctly. As you’ve learned, there is no such thing as a one-size-fits-all pricing strategy since everyone is going after different objectives. In addition, since margins are decreasing and competitiveness is increasing on a daily basis, ecommerce firms have to stay on their toes. As a result, those store owners who are thinking ahead are beginning to utilize technology such as machine learning so that they can make sure that the decisions that they make are actually dependable and based on data that is real and based on past information. In addition, you will have a better understanding of how your shoppers will end up acting to every pricing strategy that you end up incorporating. The best part, though, is that you won’t need to program them on your own. After all, this technology learns the patterns from all of that data that you had given it on its own.