The retail industry witnesses a massive volume and flow of data. It generates data in a colossal volume, variety, and velocity. While the industry is slowly adopting data analytics in their operations, they are facing some challenges. Data analytics companies are helping the retail industry adopt data-centric technology to make smart decisions and appreciate sales. However, there are certain issues faced by the retail industry with data analytics.
So, today, we’re up for discussing the hurdles faced by data analytics in retail. Recognizing these challenges will help you understand them well and overcome them eventually.
Challenges Faced by Retail Businesses in Data Analytics
Businesses face a difficult time in understanding what data to gather for analysis. Data generally brings with it a lot of unfiltered data that needs to be removed. If such data is not been taken care of, there are high chances of error in analysis. Also, it leads to unpredictability in the insights drawn.
As a result, it becomes important to collect accurate data to get more customized information. This information can be crucial for the growth of the business and help businesses take immediate necessary decisions if and when the situation demands it.
Data security is a prime concern for the majority of retail consumers. To address the issue of misuse of data, the European Union had introduced the General Data Protection Regulation. This regulation empowers the retailer to request a copy of the data that organizations might be saving. Data analytics service providers should ensure the security of data and compliance as well.
Though efforts like hardening servers, implementing continuous penetration tests and internal security audits have been carried out, data breaches still exist. This loss of trust by misuse of consumer data becomes one of the major hurdles for data analytics in the retail industry.
Businesses rely heavily on numbers because numbers don’t lie. They help in understanding the trends and reveal the patterns. This simplifies the decision making processes. But the catch is that if these numbers are not correctly made use of, it has the potential to ruin any business.
For example, when a company is looking forward to a product launch, it takes the help of retail analytics to identify its target customers. The stakeholders should know to understand which data is significant and the possible ways to consume that data. To get the precise output, it is necessary to keep a check on the data to be consumed.
Data governance strategy for data analytics services in retail deals with the authenticity of the data as well as the data source. The source from where you gather the data should be true-blue and data should be clean, secure, usable, and accurate. Also, a limit should be set which addresses how much data to use and what purpose it should serve.
It is rightly said that the most powerful firm is the one that has the right data. It is a valuable asset and can help the firm to figure out the behavior, preferences, budget, and taste of the customer.
For every problem stated above, the solution lies in the effective use of mature tools with expertise from developers and data scientists. We are a one-stop solution for all these issues. Should you want to talk about it, we’d love to connect with you.