4 Ways R Developers Are Solving Business Analytics Challenges

R Developers are solving business analytics issues in increasingly c ways. Here are some of their most interesting techniques.

September 16, 2018
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R developers have played a crucial role in developing applications predicated on big data. There are numerous fields that have benefited from their work. Healthcare, construction, law enforcement and academia are just a few of the countless sectors that have become dependent on applications developed by R programmers. However, business analytics may be the field that is most affected by their work.

There are a number of ways that R programmers develop applications that have helped improve business analytics and subsequently increase the effectiveness of most business models.

Improving omnichannel marketing strategies

Omni-channel marketing has become crucial to the success of most retailers. They have discovered that viewing online and brick-and-mortar retail distribution strategies as competitors rather than supplements have been a mistake. The most successful brands are merging the two, while companies like Sears, a former pioneer in omnichannel marketing that has since lost its way, are struggling to stave off bankruptcy.

R developers have helped these retailers integrate data from their online marketing strategies into their brick-and-mortar approaches. Nordstrom is one of the companies that has done this, which has explained why they are thriving as competitors struggle. A case study by HubSpot found that this approach lifted their ROI by 164% by utilizing data blending and other strategies.

Optimizing customer service delivery

CustomerThink discussed the role that business analytics is playing in customer service. The most important way that it is influencing customer service is by segmenting behavioral data across different customer groups and tailoring their customer service strategies accordingly. Brands are collecting valuable data on millennials and baby boomers to see what their behavioral tendencies are. This has helped create more effective customer service approaches.

Some brands can use this data in more obvious ways, because they tend to have more homogenous customer profiles. Brands that primarily serve millennials can easily corporate their behavioral data. However, some brands have more diverse customer bases. They need to utilize this data in other ways. This usually involves adding additional dimensions to their data profiles.

Most conglomerates have different child brands and products that are targeted to specific demographics. They can segment their customer service departments according to these internal divisions.

This is one of the reasons that R is such a popular language for customer service analytics. It is a very deep level programming language that can handle multi-dimensional arrays. This means that it is a good language for developing applications that need to take a very nuanced look at customers.

Fraud prevention

Fraud is a very real concern that countless businesses face. Cyber fraud is especially worrisome. Over 60% of small businesses that are victims of a cyber security breach are forced to close their doors within six months.

While technology has created lots of new security threats to businesses of all sizes, it also is the best defense against a new generation of criminals. Business analytics has helped numerous companies improve their cyber security models.

This will significantly reduce the risks of online crime in the future. Companies with a strong online presence are most likely to benefit because they tend to attract the most attention from online criminals.

R developers are playing an increasingly important role in this regard. The R programming language is very adept at collecting real-time data since earlier generations were entirely predicated on RAM memory.

Identifying employee and human resources concerns

Human resources issues are a major cause of frustration for many companies. Fortunately, R developers have helped develop a number of applications that can alleviate them. These applications are able to track employee responses over the course of a year or more.

This can help organizations better understand the issues their employees and respond to them appropriately. This can help reduce turnover, which is a massive concern for most businesses.

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