Data analytics: Understand its impact on packaging

Recently, NRF 2020 —which is one of the world's leading retail fairs and known for revealing trends in this industry—highlighted the importance of Google Analytics and several other data analytics solutions for business optimization. That's because, based on these studies, a retailer has access to information that can help you understand how to improve your company's processes. This is reflected in inventory optimization, store environment and customer service, for example. One of these improvements is the automation of the processes of companies, which has already been made by some brands. This change serves, for example, to increase the efficiency of their service by offering customers valuable experience during the purchase journey. And all this based on the analysis of data relating to consumer preferences and needs, which can reveal which processes need to be optimized. To perform this automation, brands have been using advanced technologies, such as Artificial Intelligence, which can offer more convenience and autonomy to consumers. As an example of this, we can mention the stores that offer shopping services without intermediary from sellers. In them, the transaction happens only with the identification of the customer through a QR Code and payment is made by card. In addition, there are already online stores that scan customers' bodies through an app, to reduce the need to change clothes. After all, how does data analysis work? All companies, to a greater or lesser extent, produce information that is useful for your business. And they can be collected in a variety of ways. For example, in customer satisfaction surveys or security camera footage, which shows which sections of the store were the most visited. And this data can be collected and analyzed with agility, allocating the most relevant information to the retailer and identifying some consumer trends. This can be done through a process called Big Data, which can be applied to any retail segment. It is made up of five pillars —volume, speed, variety, value, and veracity—and, with the use of appropriate tools, is able to handle even unstructured data. Thus, information relevant to the decision-making of brands can be obtained. As a result, production time and costs are reduced and the development of new products can be boosted, for example. And how to apply it to your business? Data analysis can be a positive influence for all retail segments, including the packaging industry. In this case, Big Data can show which packages and times of the year sell the most, as well as profile consumers. Consequently, companies can use this information to think about new materials and a design that best suits their customers, packaging that can be recycled or reused, and even easy-to-open lids. Another important application of data analysis is related to the prediction of demands and trends. One of them is related to the fact that consumers increasingly make their purchases through various channels. That is, using physical stores and online platforms. In this sense, companies can use after-sales data to understand how to optimize their packaging, which is the main point of contact of the brand with its customers. The automation of processes can be applied in the production, storage and transport of packaging. Thus, there is a logistical improvement and, consequently, reduction of costs, time and raw material necessary for the manufacture of products. In addition, the technology can be used in packaging to strengthen the relationship of brands with their audiences. What can be done with the use of a QR Code that directs promotions or interesting information to consumers and can involve them with the brand, for example. Learn a few steps to take advantage of Big Data When we have a huge amount of data to evaluate, it is a fact that this task becomes more difficult. Thus, to do a more in-depth data analysis, using broadly all the relevant information available in your company's equipment and processes, it is very important to follow a few steps: Set clear goals. Would it be a new package or a redesign? Focus on the main data. If it's a redesign, what aspects of the packaging did customers comment on the most? Work as a team. After all, packaging production also involves other areas, such as marketing and the purchasing sector. Analyze the data regularly. Trends change and packaging needs to be updated. Monitor production windows. Different combinations of packaging raw materials allow for greater or lesser inactivity of the equipment. Pay attention to efficiency metrics. The amount of packaging waste may indicate, for example, how well the production process is being used well or not. Upgrade your equipment. To get the data you need, install new software. Make a historical assessment. By drawing a timeline, you can better visualize the gaps in the packaging production process. While the benefits of data analytics are clearly visible, most companies still don't use Big Data in the best possible way, perhaps because of a lack of resources or knowledge. Therefore, the tool is today a great differential for companies that want to improve their processes. And, more than that, invest in the production of efficient packaging that awakenthe desire of consumers.