Big Data in E-commerce and Retail: Getting Ready to Business Transformation

We live in a time when the volume, variety, and velocity of  the data is increasing every day. While processing an enormous amount of data produced by each industry is a challenging task, it is worthy of saying that with the right approach and adequate preparation, it can bring significant value to both the business owners and their clients. One of the most notable makeovers resulted from the use of analyzed data belongs to the retail and e-commerce industry.

This blog post aims at showing the main benefits a business can enjoy when using Big Data analytics in retail and e-commerce. Besides, we decided to provide information on the steps that have to be taken before a Big Data project starts.

Benefits of Big Data Applications in Retail and E-Commerce

Use of Big Data in the retail and e-commerce industry allows businesses gaining a competitive advantage. With a great number of advanced tools and technologies carefully analyzing and smartly sorting information on how products are manufactured, shipped, stocked, advertised, purchased, consumed, etc., business owners can significantly improve shopping experiences and tighter connections between customers, brands, and retailers. So what are the main advantages of using end-to-end analytic solutions for the retail industry? Here are the main benefits to be expected:

• Identification of customers’ purchase patterns, which results in increased sales.
• Awareness of upcoming trends and ability to broaden sales opportunities through social media analysis.
• Improvements to inventory management achieved through greater visibility into the product pipeline.

Apart from these tangible advantages, Big Data in eCommerce and retail has a promising future proved by statistics.

Both benefits and forecasts intensify the importance of implementing Big Data solutions into retail and e-commerce business strategies. But how business owners can prepare for transformations? Let’s find it our overviewing some initial steps.

Big Data in E-Commerce and Retail: Starting a Project

There is no doubt that Big Data analytics in retail and e-commerce changes the face of the industry, and business owners have to adjust to the new environment. Nevertheless, this does not mean making rash decisions. Big Data in the e-commerce industry or retail is requires to get prepared for transformation.

In general, a preparation process includes 7 steps.

1. Identifying Bottlenecks

Why would you need a Big Data solution if everything in your business runs smoothly? Probably, there are some problems, at least minor ones, and it is very important to identify them and get a clear idea of what should be solved.

2. Taking Into Account All Data Sources

Although there are some obvious sources of information such as POS (point-of-sale) systems, it is necessary to identify all of them, including less obvious ones. These include but not limited to:

3. Identifying Data Connections

You can find out that it is possible to get great benefits by connecting different sources of data. For example, by combining data from supply chain and social media, you can reach your customers with information on upcoming product supplies on social media. Thus you will ensure preorders, increasing profits from a particular supply.

4. Pointing Out Metrics Requiring Improvements

Whether it is Big Data and eCommerce or Big Data and retail, it is very important to determine metrics that need to be improved. Preferably, improvements should be measurable. For example, you can calculate incomes or savings outgrowing from the use of Big Data in retail or eCommerce.

5. Considering Usability

You don’t need a solution that will slow down your business processes because of its ill-conceived UX/UI. So before you start the development, make sure you have considered and specified all usability requirements. For example, if Big Data solution you want to develop is aimed at helping your employees in decision-making, make sure its design will allow easily finding all needed information, and this information will be displayed in a clear and useful form.

6. Re-Engineering Business Processes

Get ready for some change! Big Data retail use cases show that the implementation of such solutions often change the way people do their jobs. Generally, there are two possible scenarios:

• The first one is a total simplification of all processes.
• The second is a bit more complicated: it is when your workers need to adapt to changes caused by the use of a Big Data project to enjoy upcoming advantages.

Anyways, it is wise to consider all possible ways in which Big Data can affect your business.

7. Making Decision

After you go through all the above-listed steps, it is time to sum everything up and decide if a Big Data project you want to start completely meets your business goals and is worthy of development. Such a decision-making step will help you to find out if there is a need in adding or excluding some functionality.

Conclusion

At SCAND, we strongly believe that any solution developed has to bring notable improvements to businesses. With practical experience in Big Data, we offer both our deep technological expertise and understanding of our clients needs to provide full-cycle Big Data development services outgrowing in the delivery of advanced custom solutions helping our clients in reaching their objectives. Feel free to contact us with any questions!