Data mining is an analysis strategy, the execution of which can be quite a time -consuming. Especially for shop operators, this harbors many advantages, which is why Data Mining is one of the best optimization strategies in e-commerce.
What is data mining about? How can you get the best out of your own online shop, even if you just operate a small company? What do you have to consider when DATA mining? We go into all these questions in this blog article.
What is data mining?
Data mining is a useful strategy with which data and information are searched without having a certain focus or a specific goal in mind.
The aim is to discover things that provide new knowledge and help to improve your own business strategy.
With Data Mining, for example, you could search for connections that exist between the different products that buy your customers. With this knowledge, for example, you could use effective cross-selling.
How can data mining help your online shop?
When Data Mining, you start analysis without having defined a specific problem or goal. You don’t know what you will find or whether you will discover something helpful at all.
If you made an evaluation of your data, you would normally look for certain information or a certain data record (e.g. to find out when your customers most frequently buy in your online shop).
On the other hand, if you apply data mining, it is basically about finding answers to questions that you didn’t know about at all.
Data mining is less about finding the answer to a specific question than about discovering useful correlations and patterns in your data, from which the buying behavior of your customers can be derived.
Depending on the information you encounter at Data Mining, there are various ways to use it for your company.
An important advantage is that the knowledge gained will help you to plan an improved and more targeted application of your products.
Let us take the example of the supermarket chain and the correlation between diapers and beer: If you would sell both articles in your online shop, you could use the information in a subtle but clever way and an offer or pop-up for beer Place the product page of diapers (and the other way around).
Another example: The fact is that many customers prefer to shop online at the weekend. Therefore, most of your orders are currently being made during this time, which means that many packages have to be sent at the same time.
If you want to compensate for this logistics storm, you could offer special campaigns for products that are most popular at the weekend during the week.
If you do this, however, you should make sure to announce and apply the sales campaign in advance (e.g. on various social media platforms and in your newsletter).
If interested customers learn about the discount campaign, you’d better wait a few days until you want to make a purchase instead of ordering the product you are interested in on weekends.
How you can use your knowledge from the analysis effectively depends heavily on the information you could find at.
In most cases, your knowledge of improving your advertising strategy serves. Let’s take the example of diapers and beer: Suppose you sell both articles in your online shop, then it would be wise to use these findings for targeted advertising measures.
Example of data mining
With our example, we relate to an experience that is discussed in the book “Creating Value with big data analysis” (by Verhoef, Koogle, and Walk).
An example is a large British supermarket chain Tesco. Tesco dealt with its own data and searched for purchases that were made with the Tesco Club Card.
In the course of the analysis, however, Tucos analysts found that customers who bought diapers tended to buy beer in addition to the diapers.
Another knowledge of the analysis: Beer and chips were mainly sold on Friday evening.
The findings that the supermarket chain gained helped, among other things, to operate more targeted marketing.
Note: This example should give you a rough idea of what you can find out with Data Mining. It is not clear whether the company in our example was actually Tesco since this example can be found in other sources and instead these sources refer to the American supermarket chain Walmart.
Data mining basics
You have now got to know data mining and the advantages for shop operators. Now it is time for you to learn how to start with the best of your data evaluation.
Unfortunately, Data Mining is very time-consuming, especially if you want to do it manually.
However, we recommend that you go through your data step by step. For example, if you want to concentrate on products, you should look at all the orders where more than just one product was bought in your online shop.
Which product is the most popular? Which products put customers who bought more than five products in the shopping cart?
You can also concentrate on certain product categories: if a customer has bought an article from the toy category, which products from other product categories are also ordered?
Also, take a look at preferences and correlations at different times of the day. Which products are particularly popular at lunchtime, which in the evening?
Instead of concentrating on your products, you could also take into account the various subpages of your website: Which pages are most popular at what time of day?
Compare your results with your sales. Is there a connection? This information can help you with your marketing campaigns or your bid strategies on Google Ads or Microsoft Ads.
Helpful tools for data mining
Good to know: There are a few useful tools that support you in data mining. In this way, you do not have to manually carry out the analysis.
However, many tools are quite expensive. Of course, you can simply transfer all the data you can find to an Excel file yourself, but it is easier (and less time-consuming) to use special data mining tools instead.
Weigh whether you want to invest a budget for time-saving data mining tools.
Most tools offer a free test phase anyway, so you have the opportunity to try different tools
For example, Oracle offers a 30-day free test for its data mining tool. Orange, on the other hand, is a 100% free open-source tool (only available in English).
You have to pay attention to this in the data mining
The data mining process and the result are unpredictable. Sometimes what you find cannot be classified so easily. In addition, it may take a long time for you to recognize a pattern at all.
You also have to consider the following:
Even if you find a similarity in the data, this does not necessarily mean that one thing affects the other at all. That sounds very complicated, so we give an example.
On the website Tylervigen.com there is a whole series of data that correspond to a similar pattern, but in the end, there is no connection. Take a look at the following diagram.
On the diagram, you can see that the number of divorces in the US state of Maine is related to Margarine’s per capita consumption.
Can you, therefore, deduce that only people in Maine who divorce eat margarine? Or maybe even: people in Maine, margarine eat?
Or do you assume a coincidence instead?
Of course, there is no real correlation between these two data records. Therefore, you have to be careful how you interpret your results!
You should always include several factors in your evaluation – and don’t just refer to what the analysis spit out.
Suppose they were able to find out that a particularly large number of products from the field of household goods were ordered at a certain point in time.
Then, when you go through your data, you should consider which discount campaigns you may have offered at this time or whether you offered a better price than your competition at a certain point in time.
In addition, external factors such as the corona pandemic should also be taken into account. If you suddenly found an increase in board games, was it due to your discount campaigns or certain advertising measures, or the consequences of the Corona pandemic? Or maybe even both?
Your reviews are also helpful data. You can give you a good idea of why your customers have made a purchase.
Conclusion
Data mining can provide you with surprising information from which your company will certainly benefit. Not only large companies can help with this strategy for optimization measures, but also for SMEs, data mining is extremely useful!
The most important thing is that you find the most efficient way for you to analyze your data. Data mining may not put you on the right track, or what you find only confirms your suspicion.
Also, make sure that you process the answers correctly and do not draw any hasty conclusions. You may have to try out different approaches or tools to find the most efficient method for analyzing your data.
The best thing about data mining is that you have no specific problem that you want to solve. In other words, you have nothing to lose and can only win!
