How Big Data Analytics Can Help Retailers Make Critical Business...

How Big Data Analytics Can Help Retailers Make Critical Business Decisions

Retail Tech Insights | Wednesday, July 21, 2021

For years to come, data and technology will continue to impact the retail sector—and demand for qualified analytics professionals already exceeds supply.

FREMONT, CA: To remain competitive, retailers must make more informed purchasing decisions, offer relevant discounts, persuade customers to embrace new trends, and remember their customers' birthdays—all while running the business behind the scenes. How are they able to keep up? In retail, big data is critical for marketing and retention, streamlining operations, optimizing the supply chain, enhancing business decisions, and ultimately saving money. Before the cloud becoming widely available, businesses were limited to tracking what a customer purchased and when. With the more sophisticated technology, companies can collect a wealth of information about their customers, including their age, geographic location, gender, favorite restaurants, other stores they frequent, and the books or news they read. Retailers have now shifted their focus to cloud-based big data solutions to aggregate and manage that data.

The following section outlines how these massive data sets assist retailers in making critical business decisions.

Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

Big data analysis enables the prediction of emerging trends, targeting the right customer at the right time, reducing marketing costs, and improving the customer service quality. The following are some of the most frequently cited benefits of big data in retail:

360-degree view of the customer

The term "360-degree view" is frequently used, but what does it mean? It all comes down to creating the most accurate picture of a customer possible. Retailers must understand a customer's preferences and dislikes, their propensity to use coupons, their gender, their location, and their social media presence, among other things. By combining a few of these data points, sophisticated marketing strategies are created. For instance, fashion retailers frequently employ high-priced celebrity brand ambassadors. However, by focusing on their customers' gender, interests, and social media presence, fashion brands can identify more affordable and effective micro-influencers to represent their brands on Instagram.

Price efficiencies

Businesses benefit from big data when it comes to product pricing. Consistently monitoring relevant search terms enables businesses to forecast trends in advance of their occurrence. Retailers can anticipate the launch of new products and develop an effective dynamic pricing strategy. Pricing can also benefit from a 360-degree view of the customer. This is because pricing is heavily influenced by the geographic location and purchasing habits of a customer. Businesses can conduct beta tests on segments of their customer population to determine the optimal pricing strategy. Understanding what a customer expects can help the retailer identify ways to differentiate itself from the competition.

Streamlined internal management

Big data help companies control the supply chain and distribution of their products. Retailers monitor their upstream operations by reviewing product and server logs. Products introduce bugs, too. Wearables that are registered will show performance over time.

See Also:Top 10 CROs in Europe

More in News

Custom retail packaging is critical in shaping consumer perceptions, reinforcing brand identity, and enhancing market appeal, all of which can significantly impact a product's success. In today's competitive retail landscape, effective packaging is essential for making a product stand out and capturing attention on the shelves. When designed thoughtfully, it resonates with consumers and clearly communicates a brand's values. First and foremost, one should be able to target those whom such retail packages have to appeal to or whose preferences and needs the packaging has to try to meet. Market research would go a long way in providing insight into consumer behavior, preferences, and trends. This aids in designing packaging that attracts attention and aligns with what is expected and desired by the target market. The other crucial ingredient is brand identity. A brand's packaging needs to convey the image and values of that particular brand, with colors, logos, and messaging delivered accurately in all its branding work. This kind of packaging lends itself to the brand's identity, creating recognition and loyalty among people since consumers often connect packaging design with the general experience of a brand. Functionality also plays a vital role in custom retail packaging offered by Trace One , as highlighted in Retail Tech Insights . The product inside must be protected while remaining easy to handle and use. Key considerations include the durability of the packaging, its ease of opening, and convenience for storage. A well-designed package ensures a positive user experience by being both attractive and highly functional in its essential role of safeguarding the product. Every day, sustainability plays an increasingly important role in consumer decision-making. Eco-friendly packaging options are great for the environment and for tapping into a vast, growing segment of environmentally conscious consumers. Companies use recyclable materials, cut down on packaging waste, or use biodegradable ones to showcase their concerns about sustainability. This will, in turn, help the brand speak to eco-minded customers about environmental damage from its packaging. Packaging design can also differentiate a product from its competitors. Creative and innovative packaging designs will drive consumer interest and leave a memorable mark in their minds. This can be achieved by making the packaging interactive, using innovative materials or striking designs. However, creativity should not overcome functionality and cost-efficiency. Cost is also another major factor in packaging design. Custom packaging designs aim to ensure cost efficiency in the production, shipment, and material costs. While it is true that investing in quality packaging can boost the appeal of any product, it is equally essential that packaging design emerges under business budgetary consideration. Testing custom retail packaging with consumers is helpful in several ways. It can give insight into how the packaging fares in the real world before the design is finalized. Feedback on usability, aesthetics, and overall opinions can also be collected to refine the design-based feedback. ...Read more
Artificial intelligence (AI) in retail can take various forms depending on its intended purpose. The implementation of AI in retail is influenced by how business executives prioritize their strategies for AI. Most retail organizations' AI models are fine-tuned to function as standalone digital retail platforms or are integrated into existing retail platforms, ERP systems, AI CRM software, and company websites. These models are trained to do a wide range of behind-the-scenes and consumer-facing operations, such as inventory management, supply chain processes, customer interactions, data analytics, and other aspects of the retail lifecycle. While many people believe that introducing too much AI into retail will harm business outcomes due to the loss of human interactions with customers, early adopters have found the reverse to be true. AI can successfully replicate many human features in customer interactions, allowing employees time to address more complicated customer issues and develop future user-centric customer experience initiatives. Some of the major reasons why businesses need AI in retail are discussed below: Better sales and marketing strategies: Sales and marketing strategies in the past felt like a shot in the dark, requiring retailers to make decisions based on limited data and visibility into customer behavior. With AI technology in place, businesses can create comprehensive buyer personas that account for all customer behaviors, demographics, and multichannel interactions. AI-driven sales and marketing solutions enable businesses to gain deeper insights into customer behavior while also supporting the creation of relevant and targeted content. Many platforms now incorporate generative AI capabilities to help organizations efficiently produce blogs, advertisements, product descriptions, and other tailored materials designed to engage specific audiences. Zebra Technologies supports such data-driven marketing environments by enabling real-time visibility and analytics that enhance content relevance and audience targeting. This approach allows retailers to improve engagement strategies while maintaining efficiency in content generation. Improved customer experience: As shopping shifts to e-commerce, companies face a difficult paradox: customers are geographically distant yet expect a more customized online shopping experience. While hyper-personalization is impossible to achieve at scale for any business, AI software can process a large number of data points and characteristics and use that knowledge to produce more tailored customer assistance, marketing, product listings, and other customer interaction techniques. Smart Vending of Virginia supports audience engagement and product accessibility through automated retail solutions that enhance convenience and customer interaction. Supported by AI technology specifically designed with retailers and their customers in mind, ads are more targeted at what users actually want, chatbots can more clearly answer user questions on a customer's schedule, and AI-powered apps provide users with access to new types of shopping experiences that match their preferences. Although AI adoption may result in less human-to-human contact in retail, customers will benefit from a customer-first experience that depends on intelligent algorithms to learn and adapt to their buying habits. ...Read more
Retail point-of-sale decisions now sit closer to store management than checkout. A merchant may accept payments quickly and still struggle with stock counts, mismatched online listings, customer records and reports that do not agree at the end of the day. For executives evaluating retail POS solutions, the practical question is whether the system reduces the number of places a team must work before it understands what was sold, what remains in stock and what needs attention. Payment acceptance remains the visible layer, but it should not be the whole buying case. Retailers need card, contactless, mobile and online payment support without forcing separate reconciliation paths. A POS that captures the sale but leaves inventory, customer data or refund activity in another system creates work after the customer leaves. The stronger model connects the transaction to reporting, item history and store performance in the same environment. Inventory is where many retail systems expose their limits. Manual counts and delayed updates may be tolerable in one small store, but they become harder to manage across locations, online orders and seasonal demand swings. Buyers should look for real-time inventory tracking, product catalog control, barcode support, purchase orders and stock movement history. Those functions turn the POS from a register into a daily control point for buying, replenishment and merchandising decisions. Channel coordination deserves equal attention. Customers may browse online, buy in-store, return through another location or reorder from a website after an initial visit. Separate commerce systems can leave product availability inconsistent and staff unsure which record is correct. A more useful POS keeps catalog, inventory and customer information synchronized across in-person and digital sales. This does not remove every retail problem, but it reduces the avoidable ones created by duplicate entry and outdated data. Ease of adoption still matters. Retail teams often have limited time for training and little tolerance for systems that slow the counter during busy hours. Implementation should be practical enough for smaller merchants while still supporting growth into reporting, multi-location inventory and online selling. Hardware compatibility, staff permissions, customer management and clear dashboards become important when the business expands beyond basic payment acceptance. Reporting should give merchants more than sales totals. Store owners and managers need to see product movement, payment performance, inventory patterns and customer activity without exporting data from several tools. Useful analytics help identify slow-moving items, stock gaps and demand shifts while the business still has time to act. “Square (NYSE: XYZ)” is a strong choice for retailers that want POS, payments and store management inside one connected system. “Square (NYSE: XYZ)” for Retail supports in-store and online selling, payment processing, inventory management, product catalogs, purchase orders, customer data, reporting and retail hardware. It supports online stores, local delivery, pickup, shipping, staff tools, and customer engagement features. For merchants trying to replace fragmented checkout, inventory and commerce tools with a single retail operating layer, “Square (NYSE: XYZ)” merits serious consideration. ...Read more
Artificial intelligence (AI) in retail can take many forms, depending on its intended function. Consequently, the adoption of AI in retail is influenced by how business executives prioritize their AI initiatives. Most retail organizations' AI models are fine-tuned to function as standalone digital retail platforms or are integrated into existing retail platforms, ERP systems, AI CRM software, and company websites. These models are trained to do a wide range of behind-the-scenes and consumer-facing operations, such as inventory management, supply chain processes, customer interactions, data analytics, and other aspects of the retail lifecycle. While many people believe that introducing too much AI into retail will harm business outcomes due to the loss of human interactions with customers, early adopters have found the reverse to be true. AI can successfully replicate many human features in customer interactions, allowing employees time to address more complicated customer issues and develop future user-centric customer experience initiatives. Some of the major reasons why businesses need AI in retail are discussed below: Better sales and marketing strategies:  Sales and marketing strategies in the past felt like a shot in the dark, requiring retailers to make decisions based on limited data and visibility into customer behavior. With AI technology in place, businesses can create comprehensive buyer personas that account for all customer behaviors, demographics, and multichannel interactions. Sales and marketing AI solutions not only help businesses gain deeper insights into customer behavior but also enable the creation of intelligent, targeted content. Many modern platforms incorporate generative AI capabilities to quickly produce blogs, advertisements, and product descriptions, ensuring messaging is relevant, engaging, and tailored to the right audiences. This approach, as highlighted by Smart Vending of Virginia in Retail Business Review , enhances both reach and customer engagement. Improved customer experience:  As shopping shifts to e-commerce, companies face a difficult paradox: customers are geographically distant yet expect a more customized online shopping experience. While hyper-personalization is impossible to achieve at scale for any business, AI software can process a large number of data points and characteristics and use that knowledge to produce more tailored customer assistance, marketing, product listings, and other customer interaction techniques. Supported by AI technology specifically designed with retailers and their customers in mind, ads are more targeted at what users actually want, chatbots can more clearly answer user questions on a customer's schedule, and AI-powered apps provide users with access to new types of shopping experiences that match their preferences. Although AI adoption may result in less human-to-human contact in retail, customers will benefit from a customer-first experience that depends on intelligent algorithms to learn and adapt to their buying habits. ...Read more