Have you ever wondered if there will be a day when consumers choose sustainable products or packaging over low-priced goods? Recent research on consumer behavior indicates a growing interest and readiness among consumers to spend extra on products that are produced in an eco-friendly and sustainable manner. With the manufacturing industry leading the global pollution chart, there is an urgent call among world leaders to tackle the carbon footprint. The integration of IoT is a significant accelerating factor in achieving a socially responsible manufacturing environment. From collecting data through its sensors to monitoring the raw material sources, IoT-enabled devices serve as the primary lever in adherence to sustainability, proving the IoT analytics report on IoT-based connections to be around 29 million by 2027.

With the circular economy gaining momentum for its reuse and recycle concept, IoT connections are likely to support manufacturers in the long run, from tracking resource usage to facilitating timely recycling to monitoring waste bin levels for the correct accumulation of waste. It also lets consumers know about the entire history of the material and how to recycle or return products at the end of their lives. This part of IoT is a small application in the whole manufacturing unit.

This blog post navigates you through the intricacies of IoT architecture layers and their significance in advancing sustainable manufacturing. Delve in to recognize the potential roadblocks to integrating IoT-driven connections and devices. Alongside the challenges, we’ve discussed solutions to pave the way for a smooth transition to smart manufacturing with the guidance of Indium Software, which excels at building an agile and resilient business.

Understanding IoT architecture in sustainable manufacturing

The IoT architecture has multiple layers responsible for various functions, each with significance. Let’s explore the four prominent layers and how they assist each department of manufacturing with a sustainable approach.

Perception layer (Sensing layer) 

Function: The layer that houses IoT devices like sensors, actuators, and other embedded systems is the primary source for data acquisition. From monitoring waste in the production line to detecting defects in the assembly line to tracking the conditions of materials in the supply chain to supervising asset health and optimizing the logistic route, the significance of the perception layer is unmatched.

Network layer (Transport layer) 

Function: Responsible for transmission of data from the sensing layer to the processing unit; this layer embodies communication protocols, gateways, and network infrastructure. Its application is visible in the whole manufacturing sector wherever it senses a deviation or variation; the network layer ensures it carries the data immediately for processing.

Processing layer (Middleware layer) 

Function: The layer that processes the data from the network layer for actionable insights comprises servers, storage solutions, and data processing tools. Its application is carried out at all divisions of the manufacturing unit that generate data related to energy, materials, and assets.

Application layer 

Function: The layer where actionable tasks are performed with the help of user-end applications and interfaces. The application layer immediately acts on the derived insights by giving alerts or signaling the manufacturer with the detected deviation.

The challenges in implementing IoT connectivity 

1.Technological integration

Manufacturers in power since the dawn of Industry 1.0 through their antiquated systems and devices find it challenging to come to terms with Industry 4.0, where machine-to-machine communication is functional. The legacy systems that are in operation today were not built for IoT sensors or any other embedded systems, thus having an entirely different interface and architecture from modern devices. This hinders the manufacturing unit from upscaling its sustainable operations, as IoT connections are imperative in achieving an efficient and optimized manufacturing process.

2. Data overload

Known for their massive data generation, IoT-based devices generate data every second, from sensors on machinery to wearable tech for workers. The data flow is inevitable as its storage, where data needs to be processed and analyzed in real time to gain insights into machine operations, energy consumption, and waste management. For example, if a machine is drawing more power than usual intake, it needs to be rectified immediately, for which data is imperative. Also, storing data helps in historical prediction pattern recognition for machine learning to predict future mishaps if detected. Thus, on the road to sustainability, data plays a major role that must be carefully stored and analyzed for erroneous or half-stored data, leading to wrong decisions.

3. Security concerns:

With the transformative potential for eco-friendly measures, the utilization of IoT devices is welcomed in large numbers. However, lacking robust security features can wreak havoc on the whole manufacturing environment, leading to malware functions or unauthorized access and compromising sustainable goals. As the IoT sensors are sourced from various manufacturers, the security standard imbibed in each differs owing to a potential data breach attack. As data transfers from the edge to the centralized server wirelessly, end-to-end encryption is essential for data to escape from ransomware attacks. Any compromise on the IoT sensors will surely disrupt the manufacturing process, which might not accurately detect mishaps or inefficiencies.

4. Infrastructure and connectivity 

For an effective transfer of data and analysis, the IT environment in the manufacturing unit should have high connectivity, for it influences sustainability performance. Imagine a factory operating under solar energy for its operations in a remote location. IoT sensors are essential to monitor the solar panel’s efficiency and streamline its energy distribution  to record the necessary parameters that support optimizing solar operations. What if the sensor fails to monitor the ambiance temperature panel health or other necessary criteria? The whole manufacturing process will halt, disturbing the entire cycle. Thus, a high connectivity infrastructure that supports IoT-based devices with an uninterrupted data flow and processing supply is a challenging requirement.

Bridging the IoT gap: Practical solutions for modern challenges 

Pilot projects: A prior feasibility study on a sustainable approach in the manufacturing unit will assist in ascertaining specific areas where sustainable measures can be implemented, and the result generated can be recorded for further enhancement. Thus, a phased approach allows companies to refine their sustainability initiatives regarding cost, performance, and benefit.

Bosch’s integration of IoT in its production line is the best example of phased implementation, where it started a pilot project that utilized IoT for real-time analysis of machine performance to reduce unplanned downtime. Thus, the IoT-based sensors assisted the company in predictive maintenance that monitored the machinery for an advanced maintenance schedule to cut down on unexpected service charges and disruptions to production. The integration of IoT further improved Bosch’s sustainability goals by supervising energy optimization. The company further developed an IoT suite for other companies to assist them in improving their operational efficiency.

Training and skill development: Investing in curricula programs or collaborative partnerships with academic institutions assists manufacturers in learning new technologies or tools that are a significant add-on toward their sustainability goals. They can invite industry experts to the manufacturing facility to conduct workshops and other programs that serve as a two-way opportunity. Besides organizing workshops, continuous in-house training for employees and certification programs can be conducted to foster their innovation in upskilling sustainability practices that adhere well to breakthrough technologies.

Events like “The Greener Manufacturing Show and Plastic Waste Free World Europe” are excellent examples of international conferences that welcome industry experts from various industries and locations. Citing its two previous edition successes, Mike Robinson, CEO of Trans-Global Events, shared his anticipation for the forthcoming event, saying, “We are thrilled to announce the return of The Greener Manufacturing Show and Plastic Waste Free Europe in 2023. As we progress, we aim  to develop an even more vibrant platform that promotes dialogue, highlights innovative solutions, and catalyzes meaningful change.” The show is expected to be an incredible opportunity where like-minded individuals share their insights, trends, and updates on the circular economy, recycling practices in the manufacturing sector, and other latest trends.

Robust data management: The importance of data and its role in sustainable measures cannot be overstated, as they are the driving force of IoT-based devices. Data collected from various sensors for analysis and readability assists in energy optimization, performance streamlining, material management, and other efficient alternatives. Thus implying the significance of the data governance framework for a data-driven sustainable manufacturing unit.

General Electric shines brightly with its manufacturing facility, recognizing the importance of IoT connectivity. The company collected data from its manufacturing unit’s production line, assembly line, and environmental factors through IoT sensors that assisted in optimizing its gas production and distribution processes. This helped them save 10% of gas consumption and $70 million annually.

Partnering with IoT vendors: Collaboration with the experts offers the manufacturers tailored solutions that address their needs directly, helping them tightly adhere to their sustainable goals. Harnessing practical methodologies related to IoT-connected devices is easy and effective for implementation and integration with various departments of the manufacturing sector. Directly dealing with IoT-based vendors fosters rigid energy, material, asset, and logistics management planning.

Audi’s partnership with Cisco showcased the power of IoT in manufacturing, as the company witnessed resilient and scalable production. Audi developed the Edge Cloud for Production (EC4P) platform, which aims to virtualize production assets to manage and optimize its production assets, leading to more efficient and sustainable manufacturing processes.

IoT’s role in driving sustainability in manufacturing

Energy efficiency: As a primary application, IoT devices are significant in real-time monitoring and assist manufacturers with alerts for spikes in voltage or more energy consumption. It also helps regulate the power of equipment based on its performance. For example, the IoT device automatically sets to low-power mode if the machine is idle, contributing to a greener environment.

Predictive maintenance: The unplanned downtime is reduced significantly with the utilization of IoT-based connections, which specialize in predictive maintenance. Continuous monitoring of assets’ health provides a comprehensive view for future analysis. Incorporating advanced algorithms helps analyze the data from sensors, historical data, and other patterns to predict the repair in advance, thereby optimizing resource allocation and enhancing safety measures.

Supply chain optimization: The disruption from sourcing to delivery is combated with IoT sensors that help track inventory management levels and optimize logistics routes. A visible approach in the supply chain is mandatory in the manufacturing unit to avoid last-minute delays in stocks, energy, or other deviations. Blockchain technology integration and IoT devices provide a tamper-proof record of every transaction and movement in the supply chain, ensuring product transparency, trust, and authenticity.

Water management: The integral part of the manufacturing unit needs meticulous attention in allocating and utilizing water; low availability will halt the entire production process. IoT deployment is successful as it detects water usage in real-time, ranging from quality to any production or assembly line leakage. It is also believed that IoT-based water meters are accurate in measuring water consumption, assisting manufacturers with monthly bills. The sensors can track wastewater management’s final destination, preventing penalties and other environmental harm.

Harness IoT solutions with Indium Software’s expertise

Partner with Indium Software for a strategic transformation encompassing the seamless integration of IoT connections and sensors. The diverse team of seasoned professionals at Indium Software is dedicated to transforming your manufacturing facility into a data-centric powerhouse, underpinning the shift toward sustainable manufacturing. With their deep domain knowledge, the experts craft innovative solutions, ensuring optimal utilization of technology. Step forward into the era of Industry 4.0 and intelligent manufacturing, promising increased revenue, augmented productivity, refined resource management, and amplified operational efficiency.

Conclusion 

Adopting agile solutions through IoT-based devices proves to be an imperative and innovative factor for manufacturing sectors whose main concern is sustainability. From optimizing energy efficiency to waste reduction to streamlining operations, the manufacturing industry can reap amazing benefits that add value to the business and help focus the company towards an environmentally friendly landscape. Furthermore, as technology continues to evolve, the synergy between IoT and other emerging technologies, such as blockchain and artificial intelligence, will further amplify the benefits, driving innovation, transparency, and sustainability in manufacturing operations. Thus, IoT is a transformative tool bridging the gap between traditional manufacturing practices and the future’s sustainable, efficient, and responsive manufacturing processes. Start your sustainable evolution with Indium Software, which designs tech solutions aligned with your business’s long-term vision.

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What’s a smart factory?

A smart factory represents a modernized manufacturing facility that employs digital manufacturing techniques, equipment, and systems to gather and exchange data continuously. This data is the foundation for making informed choices to enhance operations and tackle manufacturing issues. The smart factory embodies an innovative phase in the industrial revolution, emphasizing the utilization of real-time data, connectivity, automation, and machine learning. It seamlessly integrates the digital and physical worlds to oversee the complete production cycle, from supply chain management to the operation of manufacturing equipment.

Why should you embrace smart factories?

According to the Marketsandmarkets report, the smart manufacturing market is expected to grow to USD 241.0 billion by 2028. Across various industries and sectors, most enterprises view smart factories as immensely advantageous and indispensable. Here are a few advantages:

Measure KPIs: Smart factories offer managers precise and automated data, empowering them to assess key performance indicators efficiently.

Anticipate future events and plan: Smart predictive maintenance in smart factories enables managers to forecast and address maintenance issues more efficiently and rapidly.

Optimized demand handling: Through more precise forecasting, it minimizes waste, facilitating efficient demand management.

Enhanced productivity: Managers can improve productivity by accessing seamless data regarding machine maintenance and identifying potential bottlenecks.

Smart factories—real-life use cases

John Deere’s 5G network and digital twin innovations: Revolutionizing manufacturing in the Midwest

John Deere, a farm equipment manufacturer, established its private 5G network by acquiring 50 MHz bandwidth rights. This network is specifically designed to enhance operations in its Midwestern factories, facilitating the analysis of production line data for assembly process improvement. John Deere has plans to introduce collaborative robots working alongside human employees within these facilities. Furthermore, the company is creating 3D models, often called digital twins, for its production machinery. These models serve multiple purposes: performance monitoring, technician training, and equipment servicing. They are conveniently accessible on tablets and smartphones, ensuring always easy availability.

Ford’s 5G-enabled production and AI-powered welding: Transforming electric vehicle manufacturing

In Ford’s Dearborn, Michigan factory, which manufactures the electric F-150 lightning pickup truck, workers on the production line use tablets connected to the factory’s 5G network. This connectivity enables them to access critical material supplies and equipment status data. Meanwhile, in Ford’s electric vehicle factory in the UK, sensors play a pivotal role in capturing images of the welding process. It is of utmost importance in producing electric vehicle motors and batteries, as it involves thousands of welds. Subsequently, artificial intelligence (AI) systems determine the quality of these welds. If a weld fails to meet the specified standards, it is rectified before the part proceeds to the subsequent production stage. This innovative approach saves time and minimizes waste by recovering parts that might otherwise be unusable.

Manufacturing landscape transformation and its potential impact on our work processes

A smart factory harnesses the capabilities of sophisticated data analytics and artificial intelligence, allowing it to fine-tune production parameters for optimal efficiency and profitability dynamically. It maintains seamless connectivity with suppliers, partners, customers, and its workforce through a unified communication system. Furthermore, the smart factory is equipped with sensors and software that systematically gathers data about its operational environment and internal processes. This data is then leveraged to identify issues and initiate corrective measures as necessary.

Smart factories are particularly well-suited for enterprises leveraging robotics and other advanced technologies to create their products. Such companies require seamless and reliable communication channels connecting their robotic systems with central command centers. These advancements are poised to enhance manufacturing organizations’ efficiency and profitability significantly. The transition to smarter and more productive factories will be driven by improved data utilization and artificial intelligence integration. As manufacturing evolves into a data-centric and intelligent industry, manufacturers will be better prepared to stay competitive.

“Each customer’s decision while designing their product leads to modifications in our manufacturing workflow. Addressing this within the process layout becomes highly sophisticated to manage. We recognized that overcoming this complex logistics challenge requires implementing autonomous mobile robots.”

Kurt Oberparleiter, Vice President—Operations, Sunview Patio Doors

Smart factories are reshaping the manufacturing landscape in five key areas

1. Inventory management

Effective inventory management is critical for manufacturers, as it requires locating materials, determining their quantities, and monitoring their consumption. By integrating a comprehensive tracking system, businesses gain insights into the precise whereabouts, quantities, and conditions of materials throughout various production stages. This level of visibility empowers companies to optimize their inventory management by anticipating demand, reducing instances of stockouts, and mitigating overproduction, all of which contribute to improved customer satisfaction. This tracking system can encompass tools like barcode scanners, RFID tags, or other inventory management software to strengthen supply chain and warehouse operations. In smart factories, sensors are pivotal in continuously monitoring and analyzing inventory levels and product consumption. For instance, sensors fixed to conveyor belts can efficiently track products. This approach offers several advantages, most notably eliminating manual data entry and monitoring by workers while ensuring real-time inventory tracking.

2. Robotics

The integration of robots in manufacturing is on the rise, propelled by the continuous development of advanced technologies and the declining costs associated with robotics. Progress in fields like vision systems, artificial intelligence, and others will further enhance the role of robots within smart factories. When manufacturing companies are engaged in products suitable for automation, they can leverage robots and automated machinery to streamline their production processes. These robots can be programmed to execute tasks more efficiently and reliably than their human counterparts without requiring rest periods. Automation systems enable manufacturers to boost their production output with fewer human resources and within reduced spatial requirements, consequently decreasing operational expenses and boosting profitability.

Various technologies, including sensors, cameras, and other monitoring tools, are employed within a smart factory environment to assess and analyze the performance of robots and automated equipment. This proactive approach enables identifying and preventing issues before they occur, allowing manufacturers to address equipment concerns remotely.

3. Data analysis

Data gathered by sensors within a smart factory can be transmitted to a centralized data platform, where it is stored, analyzed, and visualized. This data catalyzes productivity, efficiency, and customer satisfaction, as it aids in monitoring product defects and the status of shipments. Automated data collection and analytical dashboards enable manufacturers to identify operational inefficiencies, including machinery breakdowns and production bottlenecks. For instance, a manufacturing facility can analyze the time required for material reception and producing and delivering finished goods. The factory can identify the root causes of bottlenecks in the production process through data analysis and initiate corrective measures.

4. Quality control

Ensuring product quality is pivotal for enhancing customer satisfaction. Within manufacturing operations, the application of sensors for real-time production monitoring, material tracking, and on-the-fly product testing is an effective strategy to mitigate the risk of defects. To illustrate, sensors can be fixed to machinery to identify abnormal readings promptly and prevent potential defects. Automated quality assessments are executed through sensors, cameras, and other technologies to collect data, identify issues, and initiate corrective measures.

The data analysis derived from this process reveals discernible patterns in product quality. Manufacturers can leverage this information to instigate necessary alterations in their production processes. Automated quality control systems offer the advantage of inspecting a higher volume of products per hour than manual inspections, ultimately translating into elevated product quality and increased customer satisfaction.

5. Remote manufacturing

Effective communication and collaboration among employees and various departments are pivotal factors for a company’s success. Adopting collaboration tools and software, such as team communication applications, video conferencing platforms, and team task management systems, empower companies to enhance communication and nurture collaborative efforts. In today’s technologically advanced manufacturing settings, workers wield the power of their smartphones to engage with the production process and access real-time data. They can traverse the production line using tablets to visually inspect products and input data. Furthermore, integrating robots allows workers to remotely supervise and address issues with the production floor through their mobile devices. This remote troubleshooting capability saves employees time and financial resources, as they are not required to physically visit the equipment on-site to resolve problems.

Final words

The future of the manufacturing industry is exceptionally promising. Advancements in technology have steered the era of smart factories, where manufacturers operate within a networked, data-centric, and highly automated ecosystem. These forward-looking enterprises employ a combination of sensors, robotic systems, and collaborative software to gather data, inspect operations, and enhance productivity and efficiency.

Smart factories are replacing conventional, static manufacturing facilities, evolving into digital entities capable of tracking, managing, and optimizing industrial assets. Through continuous monitoring of automated resources, optimized resource allocation, and automation applications, manufacturers can significantly enhance production efficiency and expedite introducing new products to the market. Smart factories benefit the environment and the workforce and increase productivity, cost reduction, and customer satisfaction.

Manufacturers now have a wealth of data at their disposal, with the ability to conduct real-time data analysis and detect trends. To fully harness the potential of this data-rich landscape, manufacturers must develop tailored applications and systems for data utilization and analysis, effectively leveraging the advantages of smart manufacturing. Maximizing the potential of smart manufacturing practices can increase profits and optimize operational performance for companies.

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Explore the bustling landscape of the retail holiday season through our concise infographic, offering key insights and trends that define this festive shopping period.

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But what exactly is Unified Commerce, and what does it entail? Unified commerce represents a significant shift in how technology supports the retail industry. When various front-end and back-end technologies seamlessly merge into a single unified platform, technology ceases to be a separate entity. Instead, it seamlessly integrates into the retailer’s business infrastructure, providing an agile system for delivering intelligent and efficient service at every touchpoint in the customer’s journey.

The evolution of shopping: 2013 vs. today

A decade ago, in 2013, my shopping journey involved a visit to the physical mall. Fast forward to today, and I start by launching a video conference with a store concierge, all from the comfort of my home. Thanks to the wealth of data, augmented and virtual reality (AR-VR), and the Internet of Things (IoT) infrastructure, the concierge suggests items by superimposing their images onto my digital avatar. I open another browser tab to research customer reviews and pricing, only to discover better offers at a different store, prompting me to place my order there. This shopping experience continues as I make one online purchase and then digitally visit another store to explore more options and find the perfect gift.

How do you predict an unpredictable customer?

Hearing a customer say, “I was just strolling by and noticed this, and I had to have it,” is music to a retailer’s ears, whether in a mall or a retail store. It’s a testament to the merchandising team’s exceptional job in curating gift options, making the shopping experience delightful. The customer finds a perfect gift basket more quickly than expected, and the checkout process is the final step to complete their visit.

As I reflect, engage in reading, and hold discussions with retail experts like  Kushal Kumar – Vice President of Strategic Delivery Organization at Indium Software – on how retailers aspire to craft extraordinary and personalized “unified” customer experiences, I believe that creating serendipitous moments like the one described above plays a crucial role.

As retailers navigate the opportunities and challenges presented by the COVID-19 pandemic, the seamless integration of digital and non-digital strategies becomes instrumental in gaining a competitive edge and future-proofing their businesses. Here, we explore three trends shaping retailers’ adoption of a unified commerce strategy.

#1 An Irresistible Opportunity – The Emergence of New Fulfillment Options

Prior to the COVID-19 epidemic, the proliferation of Buy Online, Pick Up In-Store (BOPIS) and curbside pickup was already on the increase. Nonetheless, the crisis has spurred consumer acceptance of these services. Online holiday sales in the United States climbed from $257 billion in 2021 to $270 billion in 2022, but worldwide holiday sales stayed flat at $1.14 trillion year on year. According to Salesforce, the development of the “buy online, pick up in-store” (BOPIS) option was a big cause behind this rise, with roughly one in every five worldwide online holiday orders.

An efficient unified commerce framework handles the inherent difficulties of operational management, from storefronts to the back office. Customers, for example, may always get real-time price and product availability. Integration with order and financial data provides clients with a complete record of all their cross-channel purchasing actions, including purchases, refunds, and exchanges made in physical stores and online.

Retailers are better positioned to improve the consumer experience by collecting data across the shopping journey by meeting customers where, when, and how they choose to make purchases. Furthermore, it gives useful insights that allow for the execution of a unified and seamless consumer and brand experience, both online and in-store.

In the words of a customer: “The app indicated that there were only two remaining – and there were two on the shelf.” Customers in the alternative situation just hope that the system’s accuracy matches the in-store reality when they arrive to make a purchase.

#2 Meeting the Demand for Personalized Experiences – Preparing for Tomorrow

Brick-and-mortar stores need a technological architecture that delivers insights akin to online experiences, extending beyond inventory display. Providing such information is paramount in today’s consumer landscape, where purchases are driven by lifestyle, value, and individual preferences. Customers now expect immersive shopping experiences enriched by virtual and augmented reality.

Retailers that tailor their services to individual customer preferences can offer personalized recommendations at every stage of the buying journey, guiding customers toward a successful checkout. To ensure a seamless experience, retailers must ensure the most relevant products are readily accessible, from fitting rooms to endcaps to BOPIS pickup points. Real-time sensor data, machine learning (ML), and artificial intelligence (AI) can revolutionize these processes, providing live inventory information, SKU-specific stock levels, and insights into consumer interactions with products.

Unified commerce amplifies the in-store shopping experience by consolidating consumer data from various channels into a single view, accessible to store executives through mobile POS devices. Yet, true success relies on the ability to collect and translate data into meaningful insights. Integrating intelligence at every stage of the commerce journey is vital for delivering unique and context-aware shopping experiences.

#3 The Growing Tech-Savvy Millennial and Gen Z Customer Base

As consumers entrust more of their personal information to their smartphones, digital payments are swiftly becoming the preferred payment method. Mobile payments offer immediate checkout, as a mere touch of the payment app icon triggers the transaction. In contrast, traditional POS systems take several seconds to approve and process chip credit card payments. Though seemingly minor, these seconds hold significant value for the modern omnichannel customer.

Beyond saving time, mobile payments profoundly influence a retailer’s brand. Retailers that are slow to adopt cutting-edge technology risk being perceived as outdated and out of touch. This is a critical concern, especially considering the preferences of a new, younger generation of customers who favor contemporary technology and expect businesses to keep pace.

A unified commerce framework’s adaptable design forms a robust foundation for engaging with state-of-the-art mobile technologies. By extending digital wallet support to various payment providers, unified commerce ensures the fulfillment of essential payment needs and provides comprehensive support for seamless purchasing experiences. Consolidating data and processes affords retailers the visibility needed to gain deeper insights into customer-facing aspects of their business, enabling continuous improvement and effortless integration with modern mobile technologies.

Concluding Thoughts

“I misplaced the receipt but can quickly find it on my app.” This level of convenience is exemplified by industry leaders like Amazon, Alibaba, Starbucks, Macy’s, and Lowe’s. Retailers must shift their focus from just the product to the individual customer, continuously monitoring customer share-of-wallet and lifetime value, transcending omnichannel strategies to excel in the intense competition.

To achieve this, retailers should adopt an open, secure, and agile platform that amalgamates retailer and third-party data sources and deploys advanced technologies such as AI and ML. This approach offers unparalleled visibility into operations and invaluable shopper insights. Regardless of their purchasing intent, whether it’s finding the perfect gift, selecting the ideal outfit, shopping for groceries, or decorating their homes, consumers crave surprise and delight. They desire hyper-personalized experiences.

Notes

Global Online Sales Top $1.14T During 2022 Holiday Season, Salesforce Data Reveals

The post 3 Serendipitous Ways Unified Commerce Wows Shoppers with Hyper-Personalized Experiences – Retailers Have a Catch! appeared first on Indium.

Some of the key drivers will be the increasing disposable income that has led to an improving purchasing power of people. The convenience of ordering products online on e-commerce platforms and retail stores will further stimulate market growth.

To meet this growing demand and understand its customers better, e-commerce businesses are increasingly investing in advanced business intelligence and analysis tools. This can provide insights into which products are moving fast, in which markets and how to improve their operations to service the customers better, maximize profits and gain a competitive edge.

3 Focus Areas

E-commerce analytics falls into three main areas:

• Data Visualization and Descriptive Analytics: Dashboards created using historical data of customer behaviour and sales records provide snapshots of all key metrics for improved decision making
• Predictive Analytics: Using churn prediction, market-basket analysis and the like, e-commerce marketplaces can predict the demand for products and design promotions to cross-sell and upsell for improving sales and customer engagement
• Cognitive Analytics: Video and images are analysed for product classification based on predefined parameters to quickly upload new products and avoid errors and time delays associated with manual intervention

Challenges and Benefits

For e-commerce platforms and online stores of retail outlets, an understanding of which products are moving, where their customers are coming from and what their customers are saying are very important.

When a product is performing well, they can boost it further by creating suitable marketing collaterals and also pair it with likely related products to increase the overall sales and growth.

A product which is not performing well will need equal efforts to promote and special offers and discounts to increase its visibility can be designed to improve its sales.

Based on geographies, retail businesses can also plan their campaigns for their stores in those locations and step up promotions for those geographies where they have a presence but not as many footfalls.

Machine learning and artificial intelligence can be used for cross-selling and upselling of related products. For example, when someone is purchasing a mobile, relevant accessories can be displayed to encourage customers to purchase a mobile case or headphones, and so on. When a customer purchases a particular model, they can be tempted with a higher model with better and more features.

Analytics can also be used to understand conversion rates from footfall to sales and the insights used to improve the conversions. Reviews, both positive and negative, are a storehouse of information on what works and what doesn’t.

Negative Review Analytics helps to build the product line with quality to meet customer expectations. Sentiment analysis allows the e-commerce players to build on their strengths, rectify their weaknesses and retain the unsatisfied customer.

For instance, in an e-commerce site, a particular bag was very popular but soon, negative feedback started pouring in. On analysis, it was discovered that the bag was still good but a flap that was added as a design element was made of a different material that did not last long as expected. This is valuable input for the e-commerce marketplace as well as the manufacturers to improve.

Competitor analysis can also be used to devise marketing and, more importantly, pricing strategies to improve the edge over business rivals. Marketplaces and FMCG can especially benefit from this.

Use Cases

Indium used sentiment analysis for a sports retailer where the reviews were analysed to understand customer perception and feedback of the products. Indium’s proprietary data extraction tool, Tex.Ai enabled extracting key phrases to gain insights on customer views. This helped the sports retailer improve on its design and customer service.

For an e-commerce aggregator, Indium used teX.Ai to automate product classification.

Chats with customers, either on chatbot or by a customer executive over the phone can be another rich source of insight into customer satisfaction levels. Using data extraction, the discussion can be analysed for what the customer needs, how it was responded to and if it had been concluded to satisfactorily. This is crucial in building customer loyalty and training the executives and the chatbots to ensure there is a closure.

Analytics can also be used for resource optimisation to reduce the waiting time of customers trying to reach a representative.

Indium Advantage

Indium Software, in its more than two decades of existence, has been providing holistic solutions on cutting edge technologies. It has carefully built a team that is a judicious mix of domain and technology experts.

Our e-commerce team can set up and run a marketplace from the ground up using the latest technologies including in-build analytics. It can also build solutions for analytics on existing platforms using machine learning and artificial intelligence. Strong solution architects, subject matter experts and expertise in analytics make Indium an ideal partner for e-commerce platforms and retail brands seeking to leverage the World Wide Web.

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