A growing number of retailers are turning to big data analytics tools to help them gain insights about their customers and how they shop to meet their needs better, attract new customers and increase revenue.

According to a recent study by McKinsey, big data analytics can help retailers improve their operating margins by up to 60 percent. It is extracting valuable insights from large data sets. When applied to the retail industry, it can help businesses better understand their customers and make more informed decisions to improve the shopping experience.

Moreover, it is getting a lot of interest from retail marketers these days. Retailers are looking for new ways to get more and more data to improve their businesses marketing efforts. In this blog, we will seek the advantages of Big Data Analytics in the Retail Industry and how these businesses are growing with Big data analytics.

Before starting this, let’s seek the expectations of a retail business from big data analytics …

In this modern era, many companies have set the wrong goals for their big data analytics projects and failed to succeed in the long run. Have a look at some important goals below:

To Improve Customer Experience

Big data gather customer insights and then uses those insights to improve the customer experience. For example, retailers can use big data to understand what customers say about them online and use that information to improve their products or services.

To Increase Sales

Big data identifies trends and patterns that further increase sales. For example, retailers can use big data to understand what products are selling well and stock more of those items.

To Improve Operational Efficiency

Big data helps streamline operations and make them more efficient. For example, retailers can use big data to track inventory levels and change their stock management processes accordingly.

To Reduce Costs

Big data identify areas where costs can be reduced. For example, retailers can use big data to understand where they are overspending and then adjust their budgets accordingly.

If retail businesses keep these goals in mind, they will be more likely to get the most out of their big data analytics projects.

Also Read: Big Data VS Business Intelligence: Must Watch Differences Between The Two Platforms [Infographic]

Role Of Big Data Analytics In the Retail Industry

Retailers are no longer trying to predict what you might be interested in buying. User behavior is being looked at to know what they want. They’re using algorithms and predictive analytics to understand their customers better. By doing this, they can offer a unique shopping experience that stands out from the crowd and keep customers coming back for more.

Big data analytics analyzes large data sets to find patterns and trends. Retailers can use big data analytics to understand their customers better, what they want, and how they behave. It helps in making better pricing, product selection, and marketing.

Big data analytics is already having a transformational effect on the retail industry. Retailers using big data analytics can make more informed decisions that improve profit and a stronger competitive position.

Read Related Blog: 10 Effective Use of Big Data and Analytics for Business Ventures

Advantages Of Big Data Analytics

The data-driven strategy has become the norm for successful businesses, and the retail sector is no different. Big data analytics help retail businesses make better decisions, understand their customers, and ultimately improve their bottom line.

Easy and Cheaper Storage facility

Big data is becoming easier to store, with storage space becoming cheaper daily. Now you can invest in ample data storage on a large scale. Managing the data effectively and making it useful for analytics is the core focus for retailers at this point.

Data Available From Every Device

The increasing number of devices, such as mobile phones and tablets, has increased the amount of data being created. Every level of customer interaction is recorded in big data for retail.

Every customer’s purchase history can be observed and analyzed to understand what he prefers to purchase. The volume of data is very large, and this has to be segregated to be made more useful.

Improved Level Of Personalization

Understanding the exact preferences of the consumer is now possible with big data solutions. The return on investment shoots up considerably with increased personalization for the consumer. Since consumers are interested in offers and discounts, they do not find it difficult to share their details. The best-suited offers can be provided to the customer based on business intelligence.

Customer Segmentation

Finding the most profitable customers is one of the most challenging aspects of retail. Making sure that the most important customers get the attention they deserve is a must. One of the major advantages of big data is that it enables you to make proper customer segmentation in place to provide relevant offers to those customers.

Right People, Right Time

Big data reaches the right set of people with the right messaging effectively. Big data uses specific audiences to bring out the best conversion rate for a retail business.

Many retail marketers cannot bring out the right results for the business because they lack an understanding of making the data usable and analyzing it. We must fully prepare the technology for big data usage and integration.

The Internet Of Things & Big Data

The Internet of Things is one of the most popular and recent trends in big data that is helping the retail industry and driving consumer engagement. The IoT devices easily connect with the in-data systems to generate data about consumer behavior and actions. IoT technology has been a boon for retail, making it easier to gather customer data.

Provides Targeted Communication To Customers

Personalized marketing is 20% more effective with ‌Big Data Services than traditional marketing practices. Data analysis helps companies track the buying process and capture past purchases of customers, which they used to target them with personalized communication.

A lot has changed in retail since manufacturers started using data to make their products better tailored towards specific demographics or needs; now, it’s not uncommon that marketers will crack open your credit card history before jumping into an online checkout flow!

Predicts Demand And Managing Inventory

Data analytics and Big Data development enable retail companies to understand the customers’ buying needs and focus on areas with high demand. The conclusion derived from the data has helped many retailers. They get a better sense of what their target audience wants to strategically plan out the inventory levels — keeping themselves ahead in this fast-paced industry.

Optimizes The Price

The retailer stage depicts the price of a product that gradually reduces after demand has subsided. However, it becomes more effective if you don’t reduce your prices during off-season periods or timeframes.

Using big data analytics, retailers can track customer spending patterns and preferences in order to gauge what prices will be most appealing to their customers.

They can also use big data analytics to track inventory levels and sales rates in order to make sure they are not overstocking or understocking products.

If you want to leverage the perks of all of this booming trend, you can embrace Big Data development services in upcoming years. However, embracing it as soon as possible is admissible to gain competitive advantages.

Enhances Customer Experience

Data analytics help retailers analyze how customers shop and use this data to produce a seamless customer experience. From choosing the product and updating account details like shipping address or payment method, all these tasks become easier with Data Analytics.

Many companies nowadays make it easy for their clients through convenience features. It features within each platform they provide access to, such as online order processing, where you can select from available options before buying.

Moreover, you can buy without entering personal information besides what’s already there. Plus, just check out quickly by providing basic info about yourself (like Order ID) if needed.

This process saves time and effort in entering new data over again with allocation at other places during busy work schedules.

Retain Customers

Retaining customers is not an easy task. It requires constant attention and focuses on what will keep them interested in your brand. It requires how you can engage with their needs or interests long-term. In this way, they become loyal patrons of yours instead of someone who spends time elsewhere doing business (sleepless nights).

Data analysis helps identify those people who disengage by identifying patterns. An example of this includes frequent buying habits. These insights give retailers insight into introducing offers that may interest the customer to make purchases again while retaining current ones.

Related:Applications of Big Data Marketing Analytics

Real-Time Use Cases Of Big Data Analytics In the Retail Industry

1. Walmart uses big data analytics to track inventory levels and predict customer demand. This has helped them reduce out-of-stock by 20%.

2. Target is using big data analytics to personalize its marketing campaigns. They send customized coupons and ads to customers based on their purchase history.

3. Amazon uses big data analytics to recommend products to customers and optimize their search results.

4. Nordstrom is using big data analytics to improve the in-store experience for customers. They track customer movements throughout the store and use this information to make layout and product placement changes.

5. Best Buy uses big data analytics to price match competitors and offer personalized deals to customers.

As you can see, big data analytics is already having a big impact on the retail industry. In the future, it will only become more important. Retailers who embrace big data analytics can understand their customers better and give them what they want. This will be key to surviving in the competitive world of retail.

Future Of Retail Industry With Big Data Analytics

IMg src: Statista

The future of retail is here, and it’s being powered by big data analytics. This cutting-edge technology is transforming retailers’ operations, allowing them to make real-time decisions based on customer behavior and trends.

Big data analytics gives retailers a wealth of insights into their customers, including what they want, how they shop, and when they’re likely to make a purchase. This information is then used to improve the customer experience, drive sales, and increase profitability.

There’s no doubt that big data analytics is revolutionizing the retail industry. With its ability to provide insights that can improve every aspect of a retailer’s operations, it’s clear that this technology is here to stay.

Conclusion

The retail industry is transforming thanks to big data analytics. By harnessing the power of data, retailers can gain valuable insights into customer behavior and preferences. This allows them to make more informed inventory, pricing, and promotions decisions. As a result, the retail industry is becoming more competitive and efficient.

Big data analytics is also helping to create new experiences for customers. Retailers are using data to personalize the shopping experience and offer targeted recommendations. Big data analytics is changing the way the retail industry operates, and it is revolutionizing the shopping experience for consumers.

Leverage Big Data Services Benefits From ValueCoders

ValueCoders is a leading offshore software development company with over 18 years of experience providing software development services to clients from various industries, including retail. Some of the big data analytics benefits that retailers can expect to see from working with ValueCoders include:

Improved customer targeting and segmentation: By analyzing large amounts of data (including customer demographics, purchase histories, and social media insights), retailers can get a better understanding of who their customers are, what they like to buy, and how best to reach them. This allows for more accurate targeting of ads and promotions and more personalized customer service.

Increased sales and profitability: By taking advantage of predictive analytics capabilities, retailers can identify trends and patterns in customer behavior that can boost sales and drive profits. For example, they can identify which products are selling well and stock up accordingly or target customers likely to make a purchase based on their past behavior.

Improved supply chain management: Big data analytics can help retailers track inventory levels and demand patterns in real time, making more informed decisions about production and distribution. This can lead to reduced costs and improved customer satisfaction thanks to shorter delivery times.

Enhanced security: Retailers can use big data analytics to monitor suspicious activity, such as unusual behavior patterns or purchases. This can help them flag potential fraud or security threats before they cause any damage.

There are several reasons why retailers might want to take big data analytics services from ValueCoders. Here are some key reasons:

1. We have a team of experienced big data analysts who can help you make sense of your data and extract valuable insights that can help you improve your business performance.

2. We have the latest big data technologies and tools at our disposal, so we can help you harness the power of big data to get better insights into your customers, their buying behavior, etc.

3. We are experts in tailoring big data solutions to meet the specific needs of retail businesses, so you can be sure that you’re getting the most value from your analytics investments.

Contact us today if you’re looking for a big data analytics partner to help you take your retail business to the next level. We’ll be happy to discuss your specific needs and requirements and tailor the right solution for you.

Frequently Asked Questions

What are the areas in the retail industry that can benefit from big data analytics?

There are a number of areas in the retail industry that can benefit from big data analytics, including customer segmentation, price optimization, inventory management, and fraud detection.

• Customer segmentation is the process of dividing customers into groups based on their similarities and targeting each group with tailored marketing messages.
• Price optimization refers to the use of big data analytics to identify the best prices for products and services in order to maximize profits.
• Inventory management involves using big data to track inventory levels and forecast demand so that the correct amount of stock is maintained at all times.
• Fraud detection uses analytics to identify patterns in customer behavior that may indicate fraudulent activity.

How can big data change the face of the retail sector?

The retail sector is primed for big data because it has customer data. Retailers have been collecting data on what their customers buy and how they pay for it for years.

Now that big data technologies are available; retailers can analyze all that data to find patterns in customer behavior. For example, a retailer might use big data to figure out that most of its customers buy blue shirts on Tuesdays. With that knowledge, the retailer could stock up on blue shirts for Tuesday and adjust its marketing accordingly.

Big data can also help retailers identify trends before they become mainstream. By analyzing social media data, retailers can see which products people are talking about and then stock those products in their stores.

In addition, big data can be used to personalize the shopping experience for each customer. By analyzing a customer’s purchase history, retailers can make recommendations for other products that the customer might like. For example, if a customer buys a lot of men’s clothing, the retailer might recommend women’s clothing to the customer.

How do retailers use customer transaction data?

Retailers use customer transaction data to understand customer behavior. Customer transaction data allows retailers to see what items are being bought together, how much money is being spent on different items, and where customers are dropping off in their shopping journey.

This information can be used to improve the customer experience by predicting what customers might buy next and by designing store layouts that encourage shoppers to purchase more items. Retailers can also use customer transaction data to target customers with customized advertisements.

Why is retail analytics important?

Retail analytics can help businesses better understand customer behavior and preferences. With this information, retailers can make more informed decisions about what products to stock, how much inventory to order, where to open new stores, and more.

Retail analytics can also help identify opportunities and trends in the marketplace. For example, if a retailer notices that a particular product is selling well, they may want to consider increasing their inventory of that product. Or if a retailer notices that sales are increasing during a certain time of year, they may want to adjust their marketing strategy accordingly.

Ultimately, retail analytics can help businesses become more efficient and profitable by giving them a better understanding of what customers want.

The post How Big Data Analytics In Retail Industry Is Transforming The World appeared first on ValueCoders | Unlocking the Power of Technology: Discover the Latest Insights and Trends.

BI aims to collect, clean, and enrich structured or semi-structured data and then store it in different SQL databases. Data from various sources is stored in a data warehouse. Its goal is to support business decision-making with reports and dashboards.

To clear up your doubts once and for all, look at the given infographic:

Infographic Showing Big Data VS Business Intelligence War:

Top 3 Open Source BI Tools:

BIRTH:

BIRT was first launched in 2004 and is an open-source analytics platform that helps produce visually appealing reports.

JasperReport:

Written entirely in Java, JasperReport is one of the most prominent and widely-used open-source reporting tools and can use data from any type of data source.

KNIME:

KNIME is an open-source business intelligence testing tool that integrates various data mining and machine learning components. The data can be enriched with the help of various business extensions that can be used here.

As its name suggests, Big Data refers to extremely large data sets that will be complex to manage with conventional databases. In Big Data, we often talk about the 3Vs theorized by Gartner, which are volume, speed, variety.

The strong evolution of the masses of data, the speed at which your data travels, and the diversity of its sources will push us to use powerful tools to exploit all the data for better decision-making.

Top 3 Open Source Big Data Tools:

Hadoop:

Created by Apache, Hadoop is an open-source software framework that facilitates the distributed processing of a multitude of data sets across hundreds of servers that operate accordingly. Many companies have been using Hadoop for a long time to sort and analyze big data.

Open Refine:

OpenRefine is an open-source data management and visualization tool that enables you to quickly clean data sets and transform them into a workable format. Even non-technical users can use this solution. OpenRefine also allows you to create links between data sets instantly.

Cassandra:

Apache Cassandra is a highly scalable NoSQL database. You can monitor large data sets across multiple server clusters and in the cloud. Originally developed by Facebook to meet the need for a database powerful enough for the inbox search function.

Conclusion:

The big data big picture won’t replace your existing BI system, but it does provide unique opportunities if you manage to combine the richness of both technologies. It will expand your data view, allowing you to analyze much more detailed and complete data.

Now, if you are also thinking of doing your next project using any of these technologies, you can contact ValueCoders for business intelligence integration or big data application development.

The post Big Data VS Business Intelligence: Must Watch Differences Between The Two Platforms [Infographic] appeared first on ValueCoders | Unlocking the Power of Technology: Discover the Latest Insights and Trends.

Companies using Big Data & Analytics experienced an 8% increase in revenues and a 10% reduction in costs. – bARC

Entrepreneurs found that Big Data cut expenses (49.2%) and create new avenues for innovation and disruption (44.3%)- fORBES

95% of the businesses’ data is unstructured.- FORBES

Let’s go back from the internet era, the time when businesses used newspapers or magazines to advertise and gain sales. Was it possible to track your business conversions or generated sales from that particular advertisement! No, you can’t even track the impressions that your ad made.

But now, with the internet or e-media advertising, everything is possible. The Internet made all this easy. You can even track the behaviour of users towards your product or services that you are offering through Big Data in business and it can help to create and predict the experiences, services, and products.

Business is all about making decisions and then facing its consequences. Sometimes they are profitable, and sometimes their effects are hard to digest. Most of the time, ventures make decisions on instinct & intuition rules. But, what if you can get an edge against these negative consequences! Is it even possible!

Use of Big Data and business analytics has been a revolutionary technology utilization that has totally changed the way of managerial competency. According to BARC, over 40% of companies worldwide are getting benefited by Big Data & Analytics.

This revolutionary technology offers 69% better decision making and the operational processes get improved by 54%. Big Data in business has changed the way of marketing as well the technology pushes your business towards boosted sales with customer satisfaction.

It’s not a get-rich-quick scheme but its integration with business processes for the forecast reliability and the acceleration of promising innovations can lead to greater efficiencies.

A number of companies are working on its integration with business to make the managerial processes efficient. There are multiple effective uses of Big Data analytics for business processes. Do small businesses have the same access to that data as big enterprises! The answer is yes! But, how can a small business or venture can make most of it?

Create new Experiences, Services and Products

Relevant information is really important for businesses to point the start of their services. Big Data is a great way to figure out the growing demand and other information like customer expectations for that demand. It helps the businesses to launch craving products at the right moment. 

From entrepreneurial enterprises to multimillion startups, all have the same access to data. This data is a great way to gather relevant information for finding out the in-demand services or products to go for. Businesses can then target their workforce and resources to get all the possible benefits and opportunities for delivering a new experience to the market.

According to Forbes, 53% of the companies adopting this technology. Using big data descriptive and predictive statistics, any business can perform research & development for knowing the in-demand services and the best vertical to work on. The use of Big Data and business analytics and the adoption of this technology are vital for business-survival and brand success.

Analyse & Predict Consumer Behaviour

Predicting consumer behaviour is the responsibility of each marketer. But, what is your strategy to predict the behaviour of your consumer or customer towards your service? Is it market research! Because it will help you to explore consumer intentions but to forecast the consumer behaviour, data-driven predictive analysis can be helpful.

The sophisticated predictive analytics tools can help your business to produce useful data. This data-driven predictions with digital footprints provide exact data to reach your consumer in the right way or with the appropriate manner.

Big data analytics in business can be used to analyse all the consumer behaviour like buying habits, frequency of usage, purchase, and even factors affecting the decision to purchase your goods. This research and study can help businesses to better understand their consumers as well as the audience to target.

Identifying Risk & Fraud During Audits

For identifying and increasing the fraud detection rate, businesses can integrate Big Data with their systems. It can help your companies mitigate risks and can serve the requirements of risk management systems by providing required information. Big Data Analytics let businesses prepare for the mishappenings based on the information mined from the old and real-time data. 

By having access to a large amount of historical data, old transactions, and customer information, Big Data can be used to identify patterns. The use of Big Data and business analytics let the organizations eliminate the risk by predicting the fraud, or any disruptive event that can create a gap between business and its goals.

Businesses can use this technology for many purposes like to reduce their employee attrition, for identifying potential risk or fraud, to predict customer churn rate and potential reasons for that, or to identify any kind of activity that can harm their business.

For Determining Product and Offer Launches

Stage-Gate process or new product development is always aligned with market demands.  Big Data is a great way of developing a proactive approach that defines all the perfect launches and development strategies. Data mining, predictive analysis and various other in-techniques can be used along with the traditional methods to generate relevant insights.

All thee insights are good to make better NPD cycle for developing products that meet customer needs and increases the customer value. The products developed using these insights and the proactive approach are also associated with less risk than the traditional-way developed products.

A business can utilize Big data & Analytics to make customer involvement better. This way customers can be helpful for the brand to gather more knowledge and information to improve the product development and to determine the best product or offer to present at the right moment.

Improve Working Process & Reliability

To improve the working process and for analysing the going-on things at every business process, the use of Big Data and business analytics will be really great. The fusion of data analytics and business processes offer the most-efficient working processes at reduced costs.

It helps the businesses moving forward by focusing on the information-driven process. In the current scenario, the integration of IoT and these sophisticated tools have generated a huge amount of data that have opened the way for analysis. The insights generated from these analyses are providing a great base for decision making and improving the working process on a huge scale.

These changes or predictive programs can bring significant benefits to any organization. In turn, the businesses get improved and reliable working processes with greater efficiencies. Big Data in business also brings increased productivity and a lot of other advantages that provide a healthier bottom line for the whole organization.

Improve User Experience

For forming a great user or customer experience, businesses can use the immense amount of the data that customers or their service users generate. This data could be their social media comments, the purchase history, buying habits, or even the rate of usage. All these data footprints across the omnichannel can be used to generate a tailored experience that the customer would love to get.

Use of Big Data and business analytics can help to identify the contact or connection centres that need improvement. It gives improvisation of communications and enhances the whole user experience by removing organizational & consumer connection issue.

“80% of consumers are more likely to purchase if the brand offers a personalized experience.”- Epsilon. For improving the customer experience, businesses can also focus on customer emotions. This could help to earn the loyalty of the customers towards brands. For getting an information base multiple data sources like social media comments, forms, feedbacks, review calls, etc can be used to give a personalized experience.

Predict Customer Demand Fluctuations

Analysing customer behaviour can help your business to predict customer demand fluctuations. This also strengthens the company’s supply chain to tackle demand fluctuations. Big Data along with demand-driven planning can balance your business’s customer demand fluctuations easily.

Use of Big Data and business analytics with sales & financial reports, marketing polls, macroeconomic and economic indicators, social media indications like shares, likes or hike in followers, and more to generate insights that are reliable and accurate predictions in complex business situations.

This not only predicts the demand or sales but also lets the businesses know what drives sales, and what circumstances are favourable to improve customer & business relationships. It allows the companies to gain an edge of competition over their competitors.

Boost Sales or Influence Customer Behaviour

The way of marketing is totally changed. The modern marketers are using modern methods over traditional solutions to drive sales. To know or predict all the potential opportunities, and for getting high-value targets for your business, historical data can be used.

If we take a look at current situations, the companies are targeting customer preference, purchase history, their feedback, social media activities, and all the possible digital tracks that can help them give the best-personalized experience to influence them to buy their goods or purchase their services. This way the companies can also find opportunities where they can offer or sell their services.

Use of Big Data and business analytics can also be seen in different marketing aspects. It can help businesses to form an optimal pricing structure, refining the messaging or notifications, visualizing the data for monitoring metrics, and a lot of aspects that can help businesses drive revenue.

Eliminate Operational Risks

Operational risks take place whenever there is human dependency or error. For reducing the operational risk, predictive analytics can be used. It works on the different data sources to save a company and its internal & external data from operational risks.

Advance use of Big Data and business analytics technology with great visualization can convert basic pieces of information from email, call records, social media handles, websites, images, communicational patterns, and other data units into operational insights that can help businesses make impactful decisions to eliminate operational risks.

Companies’ unstructured data sources are helpful to generate meaningful insights. Organizational pattern and behaviour analysis are also possible using these datasets and it allows to eliminate most of the risk factors from the business operations usually carry with them.

Re-Develop Your Products

Big Data is one of the best ways to collect and use feedback. It helps you understand how customers perceive your services and products. Thus, you’re able to make the necessary changes and re-develop your products. When you analyze unstructured social media text, it allows you to uncover general feedback from your customers. You can even disintegrate the feedback in various geographical locations and demographic groups.

To work in order to achieve customer satisfaction, it is important to work on the feedback and the desires of customers. It helps the businesses to better understand “how customers look at your services and goods?” This allows the businesses to make the required changes or to reform the product as per customer feedback.

To get insights or analyze the feedback and requirements, various data sources can be considered for analysis. Use of Big Data and business analytics allows going through different social media channels, forums, feedback forms, etc to uncover useful structured insights to decide the necessary changes in the product.

Using Big Data in business, entrepreneurial enterprises can raise productivity and efficiency of various production operations. It allows businesses to go for enormous amounts of computer designs within a second to choose from. The companies can also get all the information like the cost of material, lead time, estimated product performance after launch, and many other metrics that can help to re-launch your product successfully.

Sum-Up

These are 10 effective uses of Big Data and business analytics for all the business ventures from entrepreneurial enterprises to multimillion startups. The evolving nature of technology will help Big Data to stay long. As per Statista, the Big Data market is forecasted to grow about $103 billion by the end of 2027.

Most of the people had this misconception that Big Data is only for big shots or multinationals. But, I’ve tried to break this myth. You can use Big Data in business whether it is small, or medium, or a large one. Anyone can take help of this next-generation analytics solution for forming the best insights to boost productivity and profits for the business.

Are you willing to develop analytical solutions or software for your business that are compatible with Big Data? Share your requirements with one of the best IT outsourcing companies in India to get expert solutions.

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