How AI can benefit your data collection

Printers are collecting data about everything from costs to customers and inventory. But how can AI help you to make the most of that?

Embracing new technology is vital for many printing businesses who risk running the chance of being left behind if they fail to do so. Today’s most talked-about tech, AI, offers numerous opportunities for innovation, efficiency and doing things differently. From personalised products in web-to-print ventures to mass customisation and virtual fitting in the garment industry, AI-driven solutions have the potential to revolutionise traditional processes.

But “you only get out what you put in” with AI, so you’ll need to train it by using your datasets to make the most of these opportunities. But what are these opportunities? By leveraging your data with AI, you can unlock insights, streamline operations, and enhance customer experience. Whether optimising marketing strategies, predicting sales trends or enabling seamless virtual try-ons, the potential applications of AI are vast. 

While you can generate a lot with AI – like millions of people, you’ve probably tried using ChatGPT – it works much better with clearly defined inputs and a raft of relevant information. Give it something to work with and it can be truly transformative, in numerous ways. For example, if garment printers want to reduce the cost of returns, virtual fitting rooms are being refined all the time – Google recently launched a virtual try-on for clothing that shows how clothes look on a wide range of body types, with all-important fabric details such as creases and folds captured. 

How can AI help you make the most of your data?

AI tools have various applications that can leverage your data in ways that will be useful, time and money-saving. Here are some examples of what you can do with your data.

Improve print quality: By studying past jobs, AI can determine the best settings for new print jobs, making sure they are consistently good quality. This means happier customers who keep coming back.

Equipment maintenance: By keeping an eye on machine data and studying past maintenance records, AI can predict when something might go wrong or prompt you to undertake proactive maintenance before a major issue. This results in less downtime and lower repair costs. We wrote about Durst’s predictive maintenance model here. 

Cutting costs: AI can determine how much material you’re using, energy costs and staff expenses. By spotting areas where you can save or scale down, AI can help with efficiency, cut down on waste and, ideally, reduce expenses and therefore increase profits.

Customer service: By looking at what customers like, what they have ordered before and their purchasing behaviour, AI can help you to offer them personalised service. This could mean special offers or suggesting prints they might like. Targeted marketing is made easier with segmentation, while always-on chatbots means you can operate 24/7 across all time zones.

Stock management: Managing stock is another area where AI can help your business. By studying past jobs and predicting future usage, AI can predict what materials you will need and when. This can help with ordering, but also with ensuring you’re not carrying too much inventory. 

How to get started training AI on datasets

Asking AI to manage your inventory, for example, only works if you tell it what inventory you currently have and how much, historically, you’ve used on various print jobs. While it’s an undoubted time saver, you can’t expect AI to pull figures out of the air. You’ll also want to use the right software for the right job. There’s an ever-growing range of specialist AI tools covering everything from video production to project management, image generation to print-on-demand. Here’s how to give your chosen AI platform accurate, relevant data so you can achieve the best results. 

Be precise: Whatever your chosen AI platform, you’ll need to give it clear objectives. For example, if you wanted to use AI to look after your equipment maintenance needs or manage inventory, you need to define exactly what it can do for you. 

Add data: You may have more data than you can handle. AI can truly help in this instance. Whether it’s past print jobs, invoices, an inventory database, settings for print machinery, customer information or anything else of relevance to you as a print company, the more relevant and usable the data, the better. While AI can seemingly work wonders, you or one of your team will have to do the thinking with regards to what data you want the AI to process for you. 

Choose your model: It can get technical here, but many of the best AI solutions will walk you through a lot of this – or do much of it ‘under the bonnet’. If your chosen AI is clear about what you need to input to get the best result out of it, fine. Other options may need you to choose the AI model that best fits your data and the task at hand. This can include machine-learning algorithms or deep-learning models. Certain models work well for certain tasks – for example, you might want to use clustering to gather data into groups based on criteria that you set.

Train and test your AI: There are different ways to train and test your AI helper, depending on what it is you are working with. Broadly, however, you will need to load it with data and then carry out validation. This is basically a way to see how well your AI model handles data it has not seen before, because sometimes they can work wonderfully on old data it’s familiar with, but not new data. It is important to fine tune it so that it can handle both with equal accuracy. The main difference you can make here is to ensure your data is of high quality and properly tagged. Once you’ve evaluated the performance of your AI model, you’re ready to make it work for you. If any of this seems like something you simply can’t do, don’t worry. There’s a increasing number of experts in machine learning and AI data that you can hire or collaborate with. Outsourcing data handling is also an option if the benefits will be big enough. 

Deployment and data updates: The manual labour you have to perform to ensure the AI is useful to you might seem challenging, but much of it is front-loaded, and once you’ve deployed the AI, it will just need to be integrated into what you do. After that, you will need to monitor it, add new data where relevant and enjoy the fruits of what it can do.

As you can see, there’s little point in using AI in print unless you have a clear goal in mind. Once you know what benefits you can enjoy from AI, and how that can transform how you operate, that should guide you as to how you approach training it on your datasets. Help is available from AI experts, but there are also an ever-growing number of intuitive AI models you can try out for free.