A Graph Neural Networks (GNN) is a class of artificial neural networks for processing graph data. Here we need to define what a graph is, and a definition is a quite simple – a graph is a set of vertices (nodes) and a set of edges representing the connections between the vertices. There are many data sources which produce data that can be organically presented in a graph form. For example, we can consider social network users as graph vertices where two vertices are connected if corresponding users are friends.Read More
Every person who works in machine learning (ML) sooner or later faces the problem of crowdsourcing. In this article we will try to give answers to the questions: 1) What is in common between crowdsourcing and ML? 2) Is crowdsourcing really necessary?Read More
Packaging is an integral part of the production process, especially for the FMCG industry.
As packaging is a crucial strategic factor for brand differentiation and identity, it’s no wonder that the global spending on packaging now exceeds US$500 billion.
To increase efficiency, the logistics and distribution systems usually require secondary and tertiary packaging. The unit pack is also considered the primary package, and it plays an essential role in product protection and shelf life and presents information and sales incentives to consumers.
Stages of Packaging
Compared to the primary functions, which mainly care for the technical requirements of the packaging, secondary functions relate to communications. There are three categories of packaging functions, each divided into specific sub-functions:
Protective function – One of the main goals of packaging is to protect the goods from the environment and vice versa.
Storage function – The packaging containers have to be stored in multiple diverse locations before the goods’ packaging and after the package contents have been used. As a result, packaging must fulfill a storage function.
Loading and transport function – Handling FMCG goods involves designing transport packaging so the products can be held, lifted, moved, set down, and stowed quickly, efficiently, and safely.
Sales function – This type of packaging enables the sales process and makes it more efficient.
Marketing/promotional function – Promotional material on packaging plays an important role; its purpose is to attract the potential buyer’s attention and positively impact purchasing decisions.
Service function – Here, we can find the essential information about the contents and use of the particular product, such as the number of dosage units, list of the active components, and the benefits.
Guarantee function – An undamaged package is the manufacturer’s guarantee that the details on the packaging correspond to the contents.
Additional function – This function relates to the extent to which the packaging materials may be reused after the contents have been utilized. e.g., the recycling of paper, paperboard, and cardboard packaging as waste paper.
How much does an average FMCG company spend on the packaging?
Manufacturers spend over $150 billion every year on product packaging. We can calculate the cost of the packaging as a percentage of the total selling price. The result will vary greatly. This percentage typically ranges from 1.4 percent to 40 percent, Roughly the average cost of packaging is $1 for every $11 spent. We pay around nine percent of the amount we spend on any product for its packaging.
In 2019, the FMCG Packaging market was estimated at over USD 710 billion, and it is expected to go over USD 935 billion by 2025. The market is estimated to grow at a CAGR of 4.6% over the next five years.
As packaging represents a big part of the overall cost, FMCG companies are always exploring alternative methods to package their product to offer packaging on par with the changing trends.
As a result of the recent changing consumer preferences, FMCG companies are looking to adopt new technologies and measures to put them ahead of the competition and stand out. Packaging vendors embrace modern packaging technology to enhance the quality of packaging to serve a broader range of customers (FMCG companies) and to empower them to differentiate their products.
Smart technologies can decrease the complexity, time, and cost of package designing.
To give you an idea of what’s new on the market, we have reviewed several technologies that can transform your packaging value chain.
Computer vision is one of the latest packaging technologies that helps engineers achieve things that were not possible before and do it quickly.
The main advantage computer vision brings to packaging is its ability to guarantee an error-free finished product. This technology can compare files, scanning pixel-by-pixel to catch any printing errors, thus allowing FMCG companies to reduce overruns and prevent misprinted packaging from getting shipped to the customer.
Based on Statista’s findings, the computer vision consumer goods market will almost double in just one year, going from $9.4 billion this year to $17.7 billion next year.
Beyond the ability to see errors that humans cannot, computer vision enables apps to identify products by their packaging, allowing them to find that product and quickly purchase it. For example, Amazon Flow can recognize products on a physical retail shelf, in your friend’s fridge, at the office, or wherever you will go. Then it offers you options for buying that product, conveniently delivered by Amazon.
The designing and testing phases of a new packaging used to take months. Now, packaging designers can take advantage of virtual reality technology (VR) to create a 3-D virtual mockup. Instead of spending hours designing, printing, cutting, and folding mockups, they can present their virtual mockup on a screen or through a headset. Changes can be performed almost instantly, while the new concept can be inspected from all angles, even in a virtual store.
Kellogg has launched a new campaign and used virtual reality (VR) merchandising solutions. It used eye-tracking technology embedded into a mobile VR headset in order to obtain deeper behavioral data. During the testing phase, Kellog discovered that placing its product on lower shelves was better than displaying it on top shelves. The position adjustment resulted in an 18% increase in brand sales during the test.
Through augmented reality (AR), consumers can use their phones in-store to see what the package will look like.
Even though the consumer adoption of AR adoption is in its early phases, FMCG companies can try the technology, as it offers a lot of contextual evidence as to how the product packaging will look in the real world. In addition, this technology can save time, as companies will no longer need to set up and shoot product photos at different locations, for testing and for selling purposes.
Speaking of teleporting, confectionary brand Kinder provides shoppers a unique virtual experience with their “Jump into Africa”. The 3D augmented reality portal took consumers to explore the African Savanna right in the middle of a supermarket. Once inside the portal, consumers were able to admire animated 3D safari animals alongside fun infographics.
The same way connectivity changed the way consumers shop, it has also shaped how the packaging industry operates. The connected world we currently live in has given companies a better idea of who their customers and competition are, allowing employees to communicate and connect brand leaders with suppliers in real-time. Connectivity has the ability to solve issues before they turn into real problems.
Connectivity enables the entire value chain to communicate with increased responsiveness, which means a higher quality of work and greater speed.
With the right automation tools, your packaging process will become more seamless and transparent. Automation is the key to solve any snags or bottlenecks to find problems, thus saving you valuable time, increasing speed, and cutting costs.
As the world shifts towards superior and sustainable methods, packaging manufacturers and buyers will also benefit from the efforts. As a result, the FMCG industry will be able to revolutionize customer experience, manufacturing, and environmental protection.
Organizations and brands capable of anticipating these future trends and incorporating them into their packaging strategies will reap the benefits of being ahead of the curve.
Natural language processing has been considered by most as an emerging technology under the subfield of artificial intelligence. It’s the discipline of integrating and working on the relationship between computers and human language. It involves repetitive tasks such as summarization, ticket classification, machine transition, and more.
Since being founded in 2003, ISS Art has been striving to help the world’s top companies and organizations turn their dreams into reality. Based in San Francisco, our team is filled with experts who can deliver bespoke solutions using artificial intelligence, software, and more.
Clutch’s 2021 research shows that ISS Art is the global leader in natural language processing. Clutch is a rapidly-growing B2B market research firm from Washington, DC. Their platform is hugely looked up to in the space for its data-driven content, client review directories, and its commitment to helping clients and service providers connect.
Each year, Clutch awards the best from different agencies, so it’s massive news to us that we were recognized for our work. According to Clutch’s Leaders Matrix, ISS Art is among the top 15 companies in this category.
Our dedication to this craft is paying off, and we are grateful for each and everyone who made this possible for us. We want to take this opportunity to advocate the importance of natural language processing and our work.
Our team wants to thank our clients who help us continue charging in the right direction. We appreciate their reviews on our Clutch profile. Their words serve as proof of our hard work and dedication to our clients.
“ISS ART is extremely responsive and capable of resolving any development issue. They were just an email away if the site went down or a specific feature didn’t function properly. Their consistent efficiency is why we engaged them for so long.” — CEO, Casting
“I’d be out of business if it weren’t for them. Maybe I could find someone else, but I don’t think I’d be able to find someone better. We’re small and we’re just getting out of the startup phase, so if they hadn’t done a good job, we might’ve failed as a business.” — Executive Director, Non-profit
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In the last few years, outsourcing has become a successful and widespread business strategy, with enterprises only using internal staff for core business functions while asking external actors to complete an array of secondary tasks. The outsourcing industry represents 31% of IT services in the world, and the global outsourcing market generated an average of $92.5 billion in revenue between 2000 and 2019 (Statista).Read More
A recent study has shown that a lack of skilled talent is the top hiring challenge, as 87% of HR professionals say that there were few qualified applicants for the positions they were trying to fill.
This is the reason why there’s currently a war for talent raging on, and companies have to go out of their way in order to attract and keep skilled people.
The screening and hiring processes are also complex and challenging. Companies receive avalanches of CVs for every vacant position, and it’s time-consuming to review every single one of them.
However, thanks to artificial intelligence (AI) and HR software, it’s much easier to find and hire the right person for the job.
Cracks on the surface are a major defect in concrete structures. Early crack detection allows preventing possible damage. There are various approaches to solving this problem. It can be manual inspection or automatic detection methods. But nowadays automatic detection methods include not only laser testing and radiographic testing. Progress in neural networks and computer vision allows us to use image processing for concrete surface crack detection.
In this article, we will share our approach to solving the problem mentioned above.
In this article, I want to talk about the use of convolutional neural networks for the classification of images by style.
The goal of our project is to build software to identify whether an image is in the “BMW style”. In other words, we are faced with the task of classifying images. It is important to note here that images could be of any content, with and without cars. So, the main interest here is not to identify a car object, or identify a BMW car, rather identify a BMW look and feel – colors, composition and so on. But we can’t select these attributes of style manually. To solve this problem, it was proposed to use a neural network, in which such complex features will be found automatically in the learning process.