You have certainly heard of Big Data, and you are probably using it in your company. However, are you familiar with Small Data? Small by name, this type of data mining and analysis can produce huge results when applied to a virtual store.
In this article, we are going to explain this concept and show why Small Data in e-commerce is a powerful tool for the success and growth of your business. Let’s go!
Let’s begin by explaining the concept of Small Data and how it fits your business strategy. Unlike the generalist interpretation of a huge quantity of data, (Big Data), Small Data refers to snippets of information from this cake, providing a more in-depth overview of who the customer is and how they behave.
This type of content can be obtained by watching just one person, or as many as necessary, to define the more relevant buyer personas for your business. Along with the tools that track and analyze the use of e-commerce, one can extract strategic insights to enhance the entire user experience.
Small Data x Big Data
In other words, while Big Data provides quantity and examples of mass behavior, Small Data assures the quality of the data and a more personal interpretation of your clientele’s needs.
Mining your customers’ data today in quantity and quality is the difference between successful virtual stores and those with a lot of difficulty in converting – which is the answer to all the problems your e-commerce may have. Therefore, allocating some time to these two types of gathering is essential for a more assertive market strategy and better preparation for the future.
There are different ways of collating Small Data in order to understand and interpret that data, whether via interviews, direct surveys, or even specific filtering in your Big Data content.
But a good part of the success of this strategy lies in discovering how this information can effectively improve conversion capacity, higher average tickets and the reduction of abandonments in the process. Let’s look at some examples of how to apply Small Data:
Product recommendations in an e-commerce operation could be both an effective tool for increasing the average ticket, and a reason for your customers to have a negative impression and back off.
The difference in this case is due to “what,” “when,” and “how.” It’s a question of recommending the right product at the right time and in the most practical way for the customer.
To answer all these questions and entice them to spend more, a general idea of behavior is not enough. Small Data assures more intimate familiarity with each type of user: the sites they most often access, the social networks they most often use, and the manners in which they communicate with each other. It is by adapting your strategy to these characteristics that you win the customer over.
Practicality is a requirement highly valued by users visiting a virtual store for the first time. They want to find the product they are looking for, experience the most convenient process, and pay in whatever manner is most convenient for them.
To offer these advantages in a single e-commerce operation, working with generalized behavioral data is not enough. Directors looking to give the virtual store site greater notoriety need to go deeper, to really get to know the difficulties and wishes of the profiles representing their clientele.
With a more personal idea of their user, it is possible to make changes that are relevant and able to produce good results, like changing the registration process, adjusting the product search, or offering more practical payment methods for your type of customer.
One of the major efforts by companies that invest in e-commerce is to work with customers who quit in the middle of the process — they are people who were interested in the product, were willing to buy it, but for some reason did not close out the process.
Small Data can give you more insight precisely on this issue: the reason for quitting. Observing and analyzing the individual behavior of users is a way of identifying difficulties in the process, insufficient information that confuses them, or stages of the process that do not appear as secure.
In addition, understanding the reason why specific profiles do not complete the conversion can give you more ammunition to understand how to make them return and complete the purchase, in the same manner as the products recommended in the first topic.
Winning over and winning back are victories for an e-commerce business that you don’t just achieve with volumes of data, but with a greater understanding of each person’s characteristics.
Therefore, it is not only Big Data that has an important role in the success of an e-commerce business. The union of Big and Small, each with its defined scope and well-designed analysis methodology, is the strategic solution for more conversions and higher visibility. This is, of course, provided that your collation and study process is well integrated with the company’s ERP system.
The very creation and study of buyer personas are an example of how the analysis of Small Data can be the beginning of more future-oriented planning, with the objective laid out and a good idea of the path for achieving it.
This knowledge is powerful when used along with the marketing and sales sector to attract your clientele in the correct manner and provide all the tools to close out the sale, free of obstacles.
In summarizing, the use of Small Data in e-commerce is a search for opportunities. A better understanding of the clientele, their desires, frustrations, and purchasing habits is the origin of new products, services, and even market niches.
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