At PublicRelay, we work with the best and brightest academics and practitioners of artificial intelligence (like MIT Media Labs) as we continue to build out the most comprehensive media intelligence solution in the market. Software developers around the globe are finding new and effective ways to apply various forms of AI to make their solutions smarter and faster.
Accuracy is Everything
From its inception, PublicRelay has lived by one golden rule — accuracy is everything.
Our clients are some of the most recognizable brands in the world who have tried fully automated systems and found them to be lacking when it comes to accuracy.
That’s why at PublicRelay we employ a type of AI called supervised machine learning, in which a human is required to train the algorithm by labeling the raw inputs. At PublicRelay, the raw input is your organization’s media which is toned and tagged correctly by humans who can account for context that AI doesn’t understand. This is where the human-assist in AI is crucial. As humans tell the machine which articles are relevant, the machine starts predicting which new articles are likely to be relevant, and analysts provide feedback all the while – validating or correcting the machine’s assumptions. It’s a constant feedback loop and makes for the ultimate human-computer team up. Our systems at PublicRelay can take in tens of millions of articles per week, a humanly impossible task, but with human-assisted AI, the computer makes increasingly smart decisions about which articles are relevant, ensuring that our analysts never miss a story and reach maximum efficiency.
What's in It for Me?
Applying AI in just the right points of the process means our analysts have more time to spend on getting to the insights that are trapped within the context of an article. With human-assisted AI, our customers get the speed and efficiency of artificial intelligence without sacrificing accuracy or the insights that only a highly trained individual, who is attuned to their specific business goals, can uncover.
Having human analysts in the mix enables us to add more insightful data points from each and every article. These data points can help you answer questions like these:
- Which of our spokespeople appear most in our top tier outlets?
- Are there authors that consistently cover our peers on the topic of Workplace Environment but not our brand?
- Do our Innovation messages get shared more on Twitter or Facebook?
- How does our positive share of voice (SOV) on CSR compare to our top three competitors?
- Which influencers will help us decrease our negative SOV on the topic of product quality?
With answers to questions like these, your team can focus on the relationships and outreach that will move the needle on the key goals of the business.
In the world of textual media analytics, there are best practices as in any other industry. If your provider is not following them, it could have serious consequences for the accuracy of your communications data.
Nowadays, AI is in just about everything and business leaders are quick to get caught up in the hype.
Data found through machine learning, combined with professional hunches and experience, can help PR experts superhuman powers. We learn more about AI and media intelligence in this Q&A with PublicRelay’s CTO, Bill Mitchell.