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What is Big Data Analytics and How It Helps You Understand Your Customers?

Category: B2B News
What is big data?
Big data is the high volume of information that is collected on a daily basis from various channels that include social media, web services and machine-to-machine interactions. When analyzed, big data can provide businesses with insights that allow companies to formulate optimal strategies.

Are you having problems getting new clients or establishing lasting customer relationships? We all know that the latter is the key to customer retention, a term that is synonymous with having a steady revenue stream. Customer retention is not that easy to accomplish, sure you can offer your customer value-added services, product discounts and even freebies and they’d still walk out on you.

So how do you ensure that your business stays relevant to your customers? There are a lot of ways to do this but nothing beats knowing your customers better.

The key to customer retention is boosting customer service by aligning it with customer expectations and needs throughout the purchase journey. And this is where big data comes in. Although a relatively new information analysis method, big data can now be used to study consumer behavior, which in turn benefits customer satisfaction. But for big data to be of use to you, you will need to have a trusty data analytics software to make sense of the information you’ve gathered.

In this article, we will discuss what big data is and what it can do to help you better understand your customers, providing you with a bird’s eye view of what this data analysis tool can do for your company.

what is big data

You may have at one time or another heard or read about big data. It’s the latest craze among corporate data crunchers, the meaning of which, many people have no idea. So what is big data? To spare you the burden of deciphering technical jargon, the simplest big data definition is that it is a term used to describe large volumes of information that organizations collect daily from various sources.

However, data volume is not as important as the way companies use this information. Big data, when subjected to analysis, can provide insights that can be used to come up with data-driven business decisions. In fact, companies that utilize big data have reported profit spikes of 8 to 10 percent.

The Big Brass Dig Big Data

Big data is tied to profits, executives say

79%

Executives who believe NOT embracing big data is risky

83%

Executives who pursue big data to gain competitive edge

Source: Accenture

Designed by

Both corporate and government organizations have been restructuring their processes to work with big data analytics software. These tools can easily make sense of unstructured data that abounds in different information platforms, greatly contributing to the business environment. The competitive edge that these tools offer can leave those who fail to quickly adapt lagging behind. And then there are also business intelligence tools that can further help in the collection and analysis of information.

But using these solutions is not enough, knowing business intelligence KPIs is also a must to ensure optimal results. The need for these platforms arose from the fact that many businesses are having problems with unstructured data, with 95 percent of lacking the capability to manage such information.

Before we dwell on how big data can help you understand your customer behavior, it helps to have the right tool so you come prepared. There are plenty of data analytics solutions out there that scale to your requirements and budget; in fact, a good example is Sisense.

If you want to learn more about the benefits of such a system, you can easily sign up for Sisense free demo here.

Now, let’s find out what constitute big data and how it can help your customer profiling and engagement.

Big Data: The Three Vs

3 Vs of Big Data

Although by no means a new thing, big data which dates back to the 70s and the 80s, only came to prominence in the early 2000s, when analyst Doug Laney first came up with the definition of big data, which involved the three Vs. However, practical applications of big data came up in 2005 when people started to realize how much information is being generated by Internet channels such as Facebook, YouTube, and other sites. It was during the same year when open-source frameworks like Hadoop were developed. These tools were designed to easily process and store tons of data without breaking the bank. Since then, the generation of big data has exploded exponentially as even devices connected to the Internet are now contributing to big data.

Volume

As the term implies, big data involves large volumes of unstructured information. These may include webpage clickstreams, Twitter data feeds or those gleaned from mobile applications. Other sources include social media, business transactions and machine-to-machine interactions. This tremendous amount of information would have posed a huge problem in the past. But thanks to new tech, big data can easily be managed.

Velocity

Velocity covers the speed of data reception and the time it takes to act on them. As data streams are collected in a high-speed manner, they should be processed and analyzed as quickly as possible. Data capture technologies such as smart metering, sensors and RFID tags make it imperative that big data be processed in real time.

Variety

Big data come in different types. There are conventional structured data types that easily blend with databases. However, there are also so-called semi-structured and unstructured data, which require metadata support and preprocessing for successful analysis.

Structured vs. Unstructured

How company data often appear (worldwide)

Structured Unstructured Semi-structured Others
Structured (51%) Unstructured (27%) Semi-structured (21%) Others (1%)

Source: Tata Consultancy Services

Designed by

Understanding Customers With Big Data

Big data is very useful in determining the value of your customers. Structured data such as those of sales in marketing are readily available and can tell you a lot about your clients. What poses the bigger challenge is the management of unstructured information, which, thanks to new technologies is now possible. When used properly, big data can give you the ability to analyze customer behavior and forecast purchases while providing you with a deeper understanding of your customers. The following are ways by which you can use big data to know more about your customers.

Establish Customer Personas

Customer personas are basic qualities that describe different customer segments. Establishing personas will help you in coming up with effective advertising campaigns and target marketing messages. Segmentation tells you a lot about your customers, offering information such as influence sources, demographics and average income, to name a few.

There are a lot of platforms that are great in collecting customer information. Among these is the vast selection of data analytics and business intelligence solutions in the market. Designed to discover and manage information, these software applications automatically generate reports.

These tools also offer valuable insights by analyzing raw business data using different metrics and formulas. These insights help companies get a pulse of how their organizations are performing.

Sisense allows you to run numbers by a variety of segments to enable you to interpret data in a meaningful way.

Identify Your Best Customers

To better focus your efforts, being able to identify your best customers is crucial. By default, the best customers are those who make the most purchases from your business. But studies have shown that these consumers are not only the most resource-intensive to retain but also the least loyal among them. To identify your best customers, big data takes into account a number of factors. These include lifetime value, average purchase cost, acquisition costs, customer satisfaction, and retention costs.

Benchmarking these factors against your current perception of your customers will give you an idea of who the best of them are. This is provided that these metrics coincide with the characteristics of specific customers. Sales systems are very useful in collating information that can help you understand your customers better. Determining customer value requires you to get your hands on customer data, a process that’s a staple of sales tools.

Use Big Data Analytics Software

Having identified your best customers it’s now time to thresh out customer behavior and demographic trends that relate to your best customers and cross match them to the personas that you have created, a process that is effectively managed using big data analytics. Also, you should be on the lookout for customers of value and those have less. Having accomplished these, you should now be able to define customer groups by demographic, behavior and merit.

The value that these customer groups pose to your company should have you focusing on them. To help you in this endeavor, going for data analytics software is the right thing to do. These systems are capable of analyzing and interpreting big data and turn them into actionable insights. This is apart from the fact that these apps can be integrated into just about any of your business systems, allowing you to instantly access them in software environments that are familiar to you.

Data analytics allows you to view sales by category (SAP Lumira).

Collect As Much Data as You Can

Incomplete data often result in blind spots, which can lead to an equally incomplete snapshot of the customer experience. Collecting vast amounts of information would see to it that you have all the needed data to influence both customer behavior and experience. Data collection tools abound in the market, many of which come as part of much larger suites. These include CRM software, BI and marketing software. Using these products can help you gather more data at the shortest possible time, which can lead to richer customer experience.

Sales software is an excellent data collection tool (HubSpot Sales).

Be Ready for Real Time

Big data analytics, that piece of technology that provides you with insights gleaned from big data, gives you real-time inputs. This allows you to gain an understanding of what’s happening in your business as it transpires. Real-time data analysis may not be for everyone but it can be beneficial to companies who need accurate information interpretation as quickly as they are generated.

The so-called real-time big data analytics, which handles big data generated from inside live environments are capable of analyzing massive volumes of information that can be used for a variety of purposes, including fraud detection, natural disaster and disease outbreak management. These critical situations require fast data analysis, a problem addressed using cloud computing and edge devices.  Other applications that require real-time big data analysis include crime prevention, agriculture and disease control.

The best way to prepare for real-time big data is to explore the use of business intelligence tools so as to extract their real underlying value. This is essentially being able to intelligently process information and use the results to arrive at data-driven, real-time decisions.

However, choosing the right analytics tool can be cumbersome. You need to define what real time means to your organization. For companies such as those in the financial and eCommerce businesses, real time means being able to interpret data in a flash. So take time to determine how fast you need data analysis results to be.

Maximize Data Use

Since you have significantly invested in big data analytics, it is but proper for you to maximize your use of the information you have at hand. The granular information that big data offer will tell you things that you need to know about your customers, insights that you can act on to improve customer experience. Also, data quality supersedes quantity in this game. hence, the need for big data analytics software. For optimal results, use information that is relevant and of high quality in your analytics programs. Separating quality from bad data will result in more accurate insights and a better course of action.

Use Any Platform

You have to make sure that you are able to collect customer behavior and experience data from any device. The include laptops, smartphones, desktops and tablets. This way, you’ll be able to capture all relevant customer information. This is where SaaS platforms excel as they support a great number of machines and devices. They can likewise be accessed from anywhere at any time, allowing you to collect the big data continuously.

Big Data Use Cases

The explosion of big data has left businesses scrambling to find potential applications, and found it they have. Big data has indeed left its footprint in numerous industries like manufacturing, healthcare, and retail, among a host of others. The following are big data use cases that have been adopted by numerous organizations.

Improves Customer Experience

One of the greatest strengths of big data is its ability to drive customer experience. Such is made possible by the fact that big data is sourced from a variety of channels such as social media, call logs, website visits to name a few. This gives businesses total visibility into customer experience, which can be used to maximize product/service value and boost customer interactions.

Product Development

Many businesses now make use of big data to pre-empt customer demand. Big data allows these companies to identify the key characteristics and graph them against commercial success. This way, they are able to create predictive models that would likely result in high product/service sellability.

Machine Learning

Big data plays a big role in machine learning, which is a pretty much a burning issue right now, with many people expressing concern over the potential impact of the technology on their jobs. You see, big data has allowed users to teach machines unlike before when machine learning depends on programming.

Predictive Maintenance

The mountain of data may be keeping factors that are crucial to the prediction of mechanical failure. This is true for structured data which often house certain information about a product such as a year, model and make, to name a few. In-depth data analysis reveals possible issues before they even occur, allowing for more efficient maintenance.

In this era of online selling, the role of customers has become more important than ever–by driving business decisions. And for this reason, companies are compelled to try to know their customers more deeply–using big data. For a company to survive, understanding consumer behavior and experience is a must.

You also have to consider BI software benefits if you are to get the most out of big data. All you need to do is look at current business intelligence statistics to see how effective these tools are. Organizations use big data to derive insights, which lead to a deeper knowledge of customers.

Which big data tool should your business use?

As you can see, big data can be beneficial provided you use the right tools to collect and analyze them. For this endeavor, cloud-based systems come highly recommended. Analytics and business intelligence tools that harness the power of the cloud give you that edge when it comes to big data collection and analysis.

These platforms can be accessed from any device, maximizing data collection potential. This is not to mention the accessibility that they offer, allowing you to work on your data anywhere at any time.

But perhaps their greatest attribute is the way that they are priced, which makes them quite affordable even for small businesses. Better yet, you can try them at no cost by going for their free trial or demo. Ready to harness big data? You can start with something that adapts to the needs of small businesses and enterprises: sign up for Sisense free demo here.

By Louie Andre

B2B & SaaS market analyst and senior writer for FinancesOnline. He is most interested in project management solutions, believing all businesses are a work in progress. No stranger to small business hiccups and drama, having been involved in a few internet startups. Prior to his for-profit ventures, he has had managed corporate communications for a Kansas City-based Children International unit.

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