Machine Learning A Pillar of Price Optimization

General, Price-monitoring, Machine-learning · 08 Jun 2020

“A breakthrough in machine learning would be worth ten Microsofts.” - Bill Gates

Well, then machine learning must be a serious thing. And to be honest, it does sound so. You would think that is meant only for high-tech companies, and that it doesn’t have much to do with your eCommerce store. But, that’s not entirely true. Whether you’re a beginner, or you already have an established eCommerce store, machine learning is something you should consider adopting.

Machine learning is an advanced technology that has found its purpose in almost all business spheres.

It sounds like a difficult concept, but you’ll see that it’s not such a bugbear after all. :)

Do you know how Netflix always recommends you the content that you like? Well, they are also using ML. The platform learns what we like, and then uses that information in order to make the recommendations that are more personalized.

Besides creating a more personalized experience, this approach can be used in eCommerce, especially in the pricing optimization process.

Want to know how?

Then stay with us, since we’re going to take a deep dive into it!

1. The struggle of setting the right price

The Internet is flooded with articles about numerous pricing strategies. As you read them, you get the impression that each strategy is even better than the previous one. Then you start implementing it. Of course, who wouldn’t like to use something so beneficial? But, surprisingly (or not) it turns out not to be so suitable for your eCommerce business.

How is that possible when they praised it so much?

There is nothing wrong with the strategy itself, it’s just that is isn’t the right pick for you. Naturally, you begin to wonder how come that it worked for someone else then? The answer is simple - their goals were aligned with the chosen strategy.

For example, some eCommerce stores set maximizing the profit gained on each product as their goal. Others want to enter a new market, or to increase their overall market share.

All those scenarios need different pricing. Therefore, you want a pricing strategy that will correlate with your goals. In order to know which strategy will be, you should use machine learning. There are also some price monitoring tools, such as [Price2Spy] (https://www.price2spy.com/en/), that can help you on this road.

The spicy articles are great, but they won’t bring you profit. Using machine learning will.

2. What is machine learning?

Let’s start from the beginning. As can be found in [Wikipedia] (https://en.wikipedia.org/wiki/Machine_learning), “machine learning is the study of computer algorithms that improve automatically through experience”. This is actually an application of artificial intelligence (AI) These systems can actually learn from experience without being explicitly programmed.

Therefore, the main aim of the process is to allow computers to work automatically without human help. The ultimate goal is to identify patterns in data and previous cases/examples. This would ensure better decision-making in the future. This requires computers to have access to data and examples on the basis of which they can create patterns. In this way, they would be able to make future decisions automatically, without human intervention.

The process can be implemented in almost any business filed, so eCommerce is no exception. This advanced technique goes beyond pure generalizations. It means that you won’t only learn about what your audience likes and dislikes, but instead use that information to create patterns. The same patterns would be the base of future smart decision making.

What does that mean for eCommerce businesses? You will be able to develop complex pricing strategies that will lead you towards the desired goal.

Price optimization is another term we’ll deal with here. So let’s explain it a bit better to see how it is connected to ML.

3. Price optimization overview

The first step in price optimization is to rely on data to help you understand how consumers react to different prices. In this way, you will be closer to achieving your goals. While eCommerce was still in its infancy, there was more room for error. Yet today, mistakes in pricing strategies are costly. However, with technology advances, eCommerce professionals are able to wisely predict the demand for a product against the desired price point.

The main advantage of implementing a pricing optimization based on machine learning is its capacity to analyze a large amount of data.

Therefore, this data helps companies to adapt their prices to the needs of the market in order to increase sales. One of the strategies that quickly became the most popular is the dynamic pricing. But, in order to make dynamic pricing to work to your advantage, the machine system must lean. As we said, it must learn from your previous decisions and the results that they made. Those past steps must be taken into consideration in the present when considering new price changes.

What do you need to start optimizing your prices?

First and foremost, you must create some sort of roadmap. That means that you need to identify what is your main objective. After that, you need to define your KPIs accordingly. That includes sales history, campaign launches, promotions, customer reviews, competitor analysis, and all other data that is relevant to your business.

But, let’s explain the relationship between machine learning and eCommerce through an example.

4. An example of machine learning in eCommerce

Let’s say you have an online store where you are selling mugs. You are interested to know what’s the best price you should sell them. Now that you’ve learned more about machine learning, you know that you first need to give ML something to learn from. Therefore, you must provide some data. It can be basically anything - competitors’ pricing data, stocks, customer reviews, etc.

If you were reading carefully, you are aware that this will depend on the goals that you’ve set.

The next step is to provide the system with some parameters on which it can base future predictions. For instance, if you’re certain that you don’t want to sell your product for less then $7, then that will be one of your rules.

Once your goals are set you can proceed with modeling the data. In that sense, everything that the data algorithm managed to collect will be used when creating models. In other words, it will become a pattern.

This is crucial because it will allow you to quickly find the information you need based on previous data. That way your system will be able to predict the right prices for the future, new products.

Conclusion

By now, we have it clear how important it is to set the right pricing strategy. Even though there are a lot of contributing factors, businesses should always be focused on their goal. The goal is the cornerstone of your future strategy.

Therefore, don’t blindly follow the trends - find out what is the best strategy for you, and stick to it.

If you aren’t sure what strategy that should be, you can always start your 30 days free trial with Price2Spy, to find out. Since the market conditions are changing so fast, you need to be sure that your decisions are based on accurate data. That’s exactly what machine learning will bring you.

With this, you’ll be able to understand your customers better, and even predict the feature steps. What is even better is the fact that you don’t need to program models by yourself. Your job is to provide data, and as we explained, the system will use it to create patterns.

Have you been thinking about implementing machine learning?