Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
    data mining to find the right poly bag makers
    Using Data Analytics to Choose the Best Poly Mailer Bags
    12 Min Read
    data analytics for pharmacy trends
    How Data Analytics Is Tracking Trends in the Pharmacy Industry
    5 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: 4 Ways R Developers Are Solving Business Analytics Challenges
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Exclusive > 4 Ways R Developers Are Solving Business Analytics Challenges
Exclusive

4 Ways R Developers Are Solving Business Analytics Challenges

Rehan Ijaz
Rehan Ijaz
5 Min Read
SHARE

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.

Contents
  • Improving omnichannel marketing strategies
  • Optimizing customer service delivery
  • Fraud prevention
  • Identifying employee and human resources concerns

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.

More Read

image fx (71)
The Power of AI for Personalization in Email
Cloud Technology Advances Make Telecommuting Highly Viable
5 Ways To Use Big Data For Small Businesses
Discover The Power of Big Data And Learning Analytics For Education
AI Helps Businesses Save Money with Better Financial Management

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.

Share This Article
Facebook Pinterest LinkedIn
Share
ByRehan Ijaz
Follow:
Rehan is an entrepreneur, business graduate, content strategist and editor overseeing contributed content at BigdataShowcase. He is passionate about writing stuff for startups. His areas of interest include digital business strategy and strategic decision making.

Follow us on Facebook

Latest News

microsoft 365 data migration
Why Data-Driven Businesses Consider Microsoft 365 Migration
Big Data Exclusive
real time data activation
How to Choose a CDP for Real-Time Data Activation
Big Data Exclusive
street address database
Why Data-Driven Companies Rely on Accurate Street Address Databases
Big Data Exclusive
predictive analytics risk management
How Predictive Analytics Is Redefining Risk Management Across Industries
Analytics Exclusive Predictive Analytics

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

CDN and big data
Big DataExclusive

Big Data Creates Greater Divide Between CDN & Traditional Web Hosting

7 Min Read
data backup plan
Data Management

Why Your Business Needs a Data Backup Strategy

6 Min Read
data-driven seo
Big Data

A Beginner’s Guide To Data-Driven Technical SEO

9 Min Read
data science job interview questions
Data Science

Preparing for The Most Common Data Science Job Interview Questions

5 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

AI and chatbots
Chatbots and SEO: How Can Chatbots Improve Your SEO Ranking?
Artificial Intelligence Chatbots Exclusive
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?