Data Science, or data science, is the science that studies the extraction of knowledge from the analysis of a large amount of informationknown as Big Data.
In this science, various knowledges such as statistics, computer science, programming and mathematics are intertwined.
The goal of Data Science it is obtain data from a business that can be used to make interpretations that help make good decisions, always in order to reach the maximum potential of a brand. For example, what product should be developed or what new opportunities would be interesting to explore.
What types of data exist?
There are different types of data that can be extracted from the tools that make up the Data Science, such as or Amplitude. The most important are:
- smartdata (smart data): Refers to the data that is unique to a businessfrom billing, purchases and sales to customer information, such as full name, address, DNI or any other information that they complete at the closing of the purchase.
- Identity data (identity data): This information is more than valuable because it ranges from preferences, habits and purchase history of customers and potential customers to the type of interaction with them. In the case of , this type of interaction would be if the user entered the online store through a Facebook advertisement or if they made inquiries through that means, to cite an example. These data are mainly used to observe potential customers, know their behavior and their expectations to attract them to ecommerceY loyalty to users who are already customers. All of this leads to a excellent personalization of the offer of products and promotions, depending on the stage of sale in which each person is. For example, if the user has already made a purchase, they can be offered free shipping for the next one. Unlike those who have not yet bought in the store, where it would be convenient to offer them a discount to encourage their first conversion.
- open data (open data): This data group encompasses all external data of a business and, as such, they are accessible to anyone who wants to know them. For example, in the case of the City of Buenos Aires, there is an open database called where information of interest to businesses can be consulted, such as tax risk, exclusive information for entrepreneurs, etc.
In general, in large companies, data analysis is carried out by the figure of the Data Scientista professional who research and analyze data from multiple information sources and from different angles in order to find patterns between them and predict behaviors.
For that reason, the Data Scientists They are usually curious people, with great analytical capacity and trained with the necessary tools to create meaning and value about the data they investigate.
Advantages of applying data science in your ecommerce
At this point you are already wondering how all this is related to your online store, right? The answer is: a lot.
The large amount of data available and its subsequent analysis allows e-commerce that make use of the Data Science not only improve the focus of your business, but also:
1) Have an efficient database
Since the Data Science It allows more easily track and understand information which comes from different sources, such as , campaign results in , statistics from , among others.
2) Have more control over store stock
Because, as we said before, one of the most important data provided by the Data Science it is know what users buy and, in this case, this can help to better control the stock and always have that product that customers prefer.
3) Make decisions based exclusively on data
This is essential since, unlike “hunches”, decisions made from specific information reduce the margins of error of a business and avoid unnecessary expenses.
For example, if an ecommerce analyzes certain data and concludes that it has some products that users visit but do not buy, then it can determine that it is a product to put on promotion until its stock is eliminated.
Here the .
4) Personalize the customer experience
The objective of applying data science in an ecommerce is stay one step ahead of users. Y the more personalized the actions you implement, the more conversion opportunities you will have.
For example, to personalize your customers’ experience in your store you can make recommendations for products similar to those they visitedadvise products that complement their purchase or even show offers of products that they have browsed before.
Keep in mind that to have this information, your customer must be logged in to your store.
With these actions, the final value of the sale will surely increase! 🙂
5) Improve customer service
In this case, data analysis serves to help identify a problem (complaint about a product) that is being generated in a specific channel (online store, social network, etc.) and provide an immediate solution.
It also helps to identify if it is the same user who, for example, made a query by mail and then replied to or in In this case, help can be offered quickly and effectively.
Keeping this customer history in mind, the attention to them will improve and, also, it will generate more security and confidence in your online store.
6) Be aware of what the competition is doing
Through tools like or , you can analyze real-time data on prices and products from a certain sector in the world of ecommerce. In this way, you avoid losing customers by offering them price and quality!
Apply data science in your ecommerce!
So that you can start taking advantage of the rich information that your business has to give you, we share three unmissable tips, take note!
- Analyze what are the products from your store that your customers often buy together and configure them in the administrator as “related”. This will help your next customers buy them faster (and they’ll be thankful for your recommendation!).
- investigate which products of your business are the most sold to have (always) enough stock. Then you can highlight them within your store through a banner on the main page, for example, and complement it with . 🙂
- If you have integrated in your ecommerce, study the profile of your visitors (age, sex, if they come from a particular social network, etc.). This will help you build well-segmented, and more effective!
You like me?
as you can see, data science brings (huge) power to brands They learn to take advantage of it.
Making decisions based on specific information can improve not only the internal processes of a business but also contributes to maximizing the possibilities of sale.
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