Editor's Note: In August 2020, it was announced that Smartsheet will acquire BrandFolder.
Managing brand assets is a full-time job for many companies, especially big ones. In fact, you or someone you work with probably spends a ton of time trying to organize and find brand assets.
Artificial intelligence can help with that.
Brandfolder is a digital asset management platform powered by proprietary AI and machine learning. It helps you manage and distribute your assets quickly and easily, so you can focus on the work that's important.
We talked to Brandfolder Chief Product Officer Jim Hanifen to learn more.
Brandfolder’s digital asset management platform leverages a proprietary AI/machine learning model, Brand Intelligence, to allow marketers and creatives to manipulate, distribute, and analyze brand collateral from a single source of truth.
The vast majority of modern digital asset management solutions are built with basic AI functionality (most are solely reliant on Google Cloud’s Vision API and Amazon Rekognition), but few go the extra mile to innovate specialized artificial intelligence and machine learning layered on top of those more generic models.
Brandfolder's proprietary AI/machine learning solution, Brand Intelligence, advances brand management and insights beyond the scope of the competition. With Brand Intelligence, Brandfolder is now the first of its kind to guarantee a brand-specific and bespoke digital asset management machine learning model to every customer—one that gets faster and more discerning with every asset upload.
With Brand Intelligence, every asset is brand-specifically auto-tagged and gets smarter over time based on a user's habits. And, our search is powered by natural language processing to understand the real intent behind a search query.
Brandfolder’s founders were no strangers to the headaches that come with traditional methods of managing brand assets—unintuitive organization, duplicate workflows, incessant "do you have…" emails between team members—so they set out to shift the paradigm.
Brandfolder is a centralized, cloud-based digital asset management platform powered by proprietary AI/ML. Its core mission is to streamline storage, distribution, and analysis of an organization’s assets, and auto-scales to grow with any team. It takes the guesswork out of asset findability with brand-specific auto-tagging and metadata-powered search, restores 24/7 autonomy to global team members, and provides real-time insights to contextualize and inform brand strategy.
Marketers and creatives must manage, share, and evaluate brand assets every day, but their time is wasted when spent combing through folders, attempting to recall file names, or asking colleagues for the most up-to-date versions.
Brandfolder’s intuitive interface and brand-specific architecture ensure team members and stakeholders can access any asset they need, precisely when they need it. Custom and co-branded collections streamline asset distribution and enable users to showcase an elevated, public-facing professional polish. In three years with Brandfolder, one global franchise client saw 260% ROI and 90% reduction in time spent on content creation and distribution.
Though we specialize in mid-market and large-scale enterprises, anyone can benefit from a Brandfolder. We service customers from SMBs to the top Fortune 100 companies. Our top five verticals are retail, technology, manufacturing, CPG, and professional services.
No; marketers and creatives at all companies with various amounts of assets can immediately take advantage of Brand Intelligence. The specialized models Brandfolder can build to cater to each customer’s unique needs—combined with round-the-clock learning from the way assets are categorized as well as used—will give customers across a wide range of industries a competitive edge in real-life use of their digital content.
Brand Intelligence helps our customers realize significant cost savings. In short, we’ve built machine learning for marketers as opposed to data scientists. Unlike many AI/machine learning models available elsewhere, Brand Intelligence is designed to match the workflow that the customer’s team is already used to. There’s no supervised training of the model to make it work—the model adapts to the user and is actively working behind the scenes.
There are two main limitations:
First, data silos block pattern recognition. AI usually runs on badly structured data and recognizes different patterns—at least during the teaching period. But if there are multiple databases where the same data is different, it completely hinders the efficiency of the learning phase. If all the data in a company would be synced and stored in the same place, pattern recognition would be much easier. But most companies face the problem of data silos, where different and similar data are stored in different places and there is no “master data”.
Second, the technological limitations of AI. AI exponentially develops day by day. Still, we are truly at the beginning of the journey. Generalist AIs could give answer to most current problems, but they aren’t that good yet. So we need problem focused AIs, which have limited scope so the solutions they provide to different challenges are limited. This is something that will be solved in the future. Although it arises tons of ethical questions.
Our proprietary Brand Intelligence solution holds massive significance for our organization (and our customers) because it makes good on a long-held promise to marketers and creatives: digital asset management systems will reduce content waste, help transform a brand’s efficiency, and deliver ROI. No longer is AI geared toward data scientists alone. With Brand Intelligence, we’re magnifying our platform’s ability to adapt to our customers and enable optimal success across industry lines. We’re not just helping clients organize their assets more easily; we’re helping them effectively strategize.
Today, many digital asset management systems apply AI and machine learning at a generic level and it often comes with a hefty price tag. If you're looking to personalize content organization and distribution at scale, Brandfolder's AI and machine learning models can help you achieve this starting at the most foundational level of organizing and tagging assets. We’ve used the data from generalized tagging, user-generated tagging, and content analytics to build brand-specific models for clients. This means that the more a client uses the system, the smarter our intelligence model becomes for them; we now offer high-confidence tags that are 100% specific to any given brand.