Media indexing with Wedia’s Digital Asset Management Artificial Intelligence services

How to easily index your media using Wedia DAM AI indexing Services

As your media library grows, so does the work needed to sort through it. But that’s work you no longer have to do on your own. Which Artificial Intelligence (AI) services exist to help you free up manual time spent tagging your marketing content and indexing your DAM? How can you set up a specific AI learning and manage it on a daily basis? Discover our how-to video on how the Wedia Digital Asset Management (DAM) solution can help you accurately index your digital assets thanks to its artificial intelligence (AI) services.

Indexing your media files is an important part of successful Digital Asset Management – so much so that there are dedicated teams and trained staff such as reference librarians or indexing services responsible for this undertaking. Without the proper tagging of assets, your DAM users would be unable to retrieve the files they need for their creative, marketing or sales operations. In other words, your DAM platform would lose its fundamental purpose, which is to help all stakeholders of your company easily and quickly find, share, reuse and ultimately get more value from your digital assets.

Indexing: an instrumental yet often underestimated field of Digital Asset Management

Imagine you want to find a new pair of sneakers on your favorite eCommerce site or online marketplace. To refine your search and find the product that matches what you’re looking for, you’re going to apply a few filters: by brand, by shoe type, by color, by shoe size etc… Ensuring your assets are organized in your media library works in the same way and is a pursuit that should be just as important as making your products easy to find for your online customers. Consistently adding the right information or « metadata » to your media files according to your organization’s specific search criteria or taxonomy will let you properly segment content in your DAM and help any user, business unit, local office or partner narrow down their search. These metadata fields can describe the technical properties of an asset, such as the media type and format, but also its descriptive or administrative features such as the shooting date, its location, or information about its usage rights.

Indexing improves the usability of your DAM and its ability to make content easily discoverable or available, but it is also oftentimes the source of significant time and cost savings. By successfully locating a specific asset, such as an image, video, graphic, PDF etc., you reduce costs related to reshooting or reproducing it. After centralizing to one central hub, A DIY Wedia customer found that 30% of the content it was managing was duplicate. The company now saves significantly on the corresponding production and management costs. An automotive customer, prior to implementing the Wedia DAM, also noted that up to 5% of existing visuals were reshot because international business units were unable to find them in time, resulting in unnecessary agency fees.

Indexing your assets is a continuous, and understandably tedious process, but when done well, makes your DAM platform an intuitive and useful destination for all users – especially as the volume and diversity of content housed in your DAM grows. Still, it can represent hundreds of hours of work. So how can you make media tagging easier? Which artificial intelligence services exist to help you free up manual time spent sorting through your marketing content?

DAM Media indexing powered by AI (Artificial Intelligence) services

As an add-on to its Digital Asset Management module, Wedia provides artificial intelligence (AI) services built around Google AI services and Microsoft Azure Cognitive Services. Thanks to a wide variety of AI-powered capabilities, customers can save time manually tagging images and videos, improving the discovery of media i.e. performing effective searches across your media, but also search within the media file itself.
How to search for assets in your DAM using AI filters
To find a specific asset in your Wedia DAM, you can apply several AI filters: you can search by “people” (media files with or without people in them), as well as “age” (babies, children, adults, seniors). If you’re looking for an image or video with a particular brand ambassador or employee for example, you can refine your search by selecting the appropriate age group of that person. Another available AI filter describes the “situation” of the asset – whether it was taken indoors or outdoors. With the help of Wedia, you can also create AI filters that are unique and useful to your specific brand or content – for example you may want to apply “wears a safety helmet” if a construction company wants to find an image that complies with the rules at a construction site, or “without the marker detection of a cigarette” if your oil and gas company is searching for assets displaying a gas station.
How to search within your assets in your DAM using AI
The AI can also identify and analyze content within images and videos to help users explore and extract more information from them.

  • Insights:AI converts speech and extracts textual elements in a video in order to generate time-coded sentences or a ‘transcript’. Clicking on any text will bring you to the corresponding part of the video where that text can be heard or read. For long-form videos, you can easily jump to different parts of the video thanks to this time-coded transcript, and quickly find the exact moment of the video you’re looking for.
  • Emotion & Sentiment Analysis:AI also identifies positive, negative and neutral sentiments of people based on their voices, voice tonality and facial expressions, generating time-coded sentiments. It can go even further to categorize them into different emotions: happiness, sadness, surprise, anger or fear. This can be especially useful when moderating your own branded or user-generated content (UGC).
  • Labels and Keywords:The AI identifies various visual objects, actions and colors displayed in a video and lists them as time-coded « labels ». Using labels, you can quickly find an object or place – such as a « building », « sunglasses » or a « cell phone », but also identify parts of the video where someone is « smiling » or « walking ».The AI can be trained to also automatically associate keywords with a new asset. These are words or concepts that may not be explicitly said or seen in the video. For example, words like « internet » or « cuba » may be difficult to detect and list as labels, but can appear as keywords.
  • Face Detection:You can enable face tracking in order to search for specific people as well as celebrities in a video. The AI identifies and groups faces that appear in a video, so that you can quickly find all the segments where a specific person appears, simply by clicking on the individual’s face from the available list.

With the help of reliable and automated indexing powered by AI capabilities, DAM customers can reap several benefits. It allows DAM users to increase efficiency when finding and retrieving assets, boost their productivity as they spend less time on the actual categorization and enrichment of content, and automates the moderation and compliance of content in order to protect the brand’s image. By saving hundreds of hours of administrative work and enhancing the search experience across your DAM platform and within your media files.

While artificial intelligence may not be entirely new to the digital asset management industry, today, the key difference between two DAM vendors is the ability to combine multiple AI technologies in a way that is transparent to the customer, and the capacity to create a specific learning for that need – more specifically, to propose a learning service that the customer can manage themselves on a daily basis. Wedia’s AI services are positioned to guarantee the most efficient, advanced and customizable services in order to make your content more accessible, more reusable, and ultimately increase the business value for your brand.

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