Since 2010, when Siri launched, we’ve seen increasingly pervasive AI technology in everyday life. AI became mainstream again, and huge promises were made. Siri, Watson, and other assistants made us think it wouldn’t be long before we had a human-like AI to interact with.
This lead to warnings from thought leaders like Elon Musk and Stephen Hawking that the AI research trajectory might lead to human extinction (as if unemployment isn’t bad enough). That being said, we shouldn’t let these fears hamper our ideas about how best to use great technology. Building momentum on how to use AI to save time will allow us to do what insights managers do best: think creatively.
Let’s look at a few key ways that AI can help insights teams to achieve that.
A typical insight task is to dig through documents, reports, projects, etc. to find answers to business questions. If you’re looking through a folder or drive, hunting for results takes ages. You have to open each file, search until you’ve found the page you need, and extract your content. If you’re not already familiar with the file, it takes even longer.
Models now exist that extract answers from text in seconds. Just type or ask the question, hit the search button, and the AI-powered search instantly finds the exact answer in the most relevant report. While many reports could contain a possible answer, the search engine sorts your results so the report with the highest topic overlap shows up first. The end result: valuable time and energy are saved, to be put into more fulfilling activities.
Sometimes, you don’t have an exact question. To get information and findings from a report, you have to read it.
While reading, your brain automatically associates what you already know with what you’re learning. AI can do this for you as well. The best AI systems build knowledge graphs that reflect the topic of interest to imitate your thought process: by learning new concepts as they “read,” and associating these with previously learned concepts.
At Market Logic, our knowledge graph understands the domain of marketing to support you in two ways: by telling you the key concepts in the report (brands, drivers, barriers, benefits), even if you don’t have the time to read the whole thing, these findings will cover the most salient topics; and it can tell you, on a timeline, what new contributions this report adds to the overall Knowledge Graph, so you can detect unexpected relationships and trends.
Google is great for finding videos and images, whether it’s photos of your dream vacation spot, a kitten video, or an image of a product you want to buy. In market research, the task is a little more sophisticated, as most images and videos are associated with complex semantics. The question isn’t “What does the product look like?” but “Can you find the image in the context of an abstract semantic context?”
For example, real-world market research questions are things like “Can you show me bottles that look environmental-friendly”, or “Find product labels that communicate simplicity as a benefit” and even “Find people who influence a certain segment based on their look”.
That’s not what you expect to get when you ask a generic, corporate insight platform a question. But because Market Logic’s knowledge graph is focused on the marketing domain, images and videos are semantically represented in the same way as your auto-tagged research reports. Their meaning is associated with the report, and the report’s meaning is associated with its pictures, so you get much more than just an image.
When you ask about key product drivers, you don’t want to drown in insights that mention “drivers.” What you really want is a way to analyze the most important drivers based on their salience to your product and see them listed accordingly.
This allows you to browse through them in a structured way and get a consistent picture in minutes. That’s exactly what the Market Logic Knowledge Graph allows: not only is all knowledge stored, it’s also structured in key marketing dimensions familiar with your business world and language.
That structure lets the machine analyze and report back to you, quickly summarizing what you need to know. Less time searching, more time for creativity.
There are many more ways AI is improving everyday insights tasks, so stay tuned for more. For now, let’s conclude with the agreement that this is how insights tasks were always meant to be. Boring, repetitive tasks are creativity-killers.
Instead of spending time on those, AI is freeing up time for us to creatively solve problems. AI isn’t a threat to any of us. It does what technology was always meant to do: make our lives easier so we can spend time on new and better things.