One of the biggest challenges facing our clients - from government agencies to industry associations to large commercial enterprises – is managing the volume of complex technical data they have and delivering it to their different audiences. agencyQ developed a solution for this challenge that we call “Find-it-First.” It is a unique combination of proprietary APIs and software that leverages machine learning and natural language processing to efficiently ingest, analyze, and categorize large volumes of technical data - and couple these technologies with a digital experience platform to deliver more relevant content across a variety of unique audience segments.
The result? An experience that can “know” that an academic researcher needs data tables and report annotations when they search for “Ultrahigh Frequency Sound Waves” whereas a high school physics teacher would benefit more from syllabus suggestions and recent discoveries associated with the same search query.
How does it work? There are three main components of the experience:
FiF tackles the challenges of ingesting, analyzing and categorizing complex, technical and specialized scientific data and content. This is done by using an integrated system of AI, natural language processing, visual recognition (for images), search functionality and content management tools tied together. FiF’s natural language API uses a unique semantic analysis process that categorizes content via dynamically inferred context rather than relying on traditional keyword methods.
Content Relevance Analysis
FiF uses proprietary algorithms developed by agencyQ integrated with an intelligent automated analysis and recommendation engine. These drive the critical information and strategic insights necessary to deliver the highest value, most relevant personalized content for each target audience. The agencyQ algorithm continually measures and optimizes content elements based on a user’s observed engagement with every piece of content across all digital channels, refining the content to match the “intentionality” of the user.
FiF leverages personas and customer journey maps to automatically guide desired interactions with users, create personalized content based on the most likely persona of the user and provide trigger signals for marketers to take human interaction when desired. The secret sauce in FiF is a system of proprietary and repeatable algorithms that continually looks at known user data (demographic, firmographic, etc.) and intentionality data in near real-time to continuously “nudge” users back into the customer journey path to create the best chance of desired outcomes.
FiF journey map overlays can be customized to any customer experience use case where there is (1) a mappable desired outcome, (2) a system of digital interactions and, optionally, (3) a system of desired human interactions. The result is that different types of users will automatically see different types and styles of content displayed on the website and returned in search results based on how they engage with and search for information.
The benefits of FiF range from 50x greater speed to ingest and categorize content, to 50% reduction in user search time – with substantial impact to saving time in managing content, as well as substantial improvement in user satisfaction, reduced bounce rates, and time on site. We at agencyQ developed FiF because we believe in the power of personalization to improve our clients’ digital performance and their audience’s satisfaction – and through FiF we put ourselves in a position to prove this value.