Produce and Promote Better Content in Less Time with Artificial Intelligence
This post is part of our Spotlight series featuring AI-powered companies and products that marketers can use to drive performance and transform their careers.
Editor's Note: In October 2018, Scoop.it was acquired by Linkfluence. Guillaume Decugis has since become the CEO of Linkfluence. Scoop.it remains a standalone product and will continue to operate independently under the umbrella of Linkfluence.
Companies continue to invest in content marketing—yet 55 percent don’t have clarity into the effectiveness of that content. So what if you could use automation to figure out what content best resonates with your audience, use predictive insights to better promote that content, and measure performance of each asset produced along the way? Then, what if you could produce more effective content at scale?
That’s the goal of Scoop.it (@Scoopit), a platform powered by artificial intelligence that makes content publishing more efficient and impactful. We learned how by talking to Guillaume Decugis (@gdecugis), an engineer-turned-marketer, and Scoop.it’s co-founder and CEO.
In a single sentence or statement, describe Scoop.it.
Scoop.it is a content marketing automation SaaS platform that uses AI technology to help marketers grow traffic and lead generation through content.
How does the company use artificial intelligence (i.e. machine learning, natural language generation, natural language processing, deep learning, etc.)?
Historically, Scoop.it started to automate content discovery by building technology that crawls the “relevant web.” This powers our content curation service that helps millions of users find content to share on their various channels.
But in the process, it also provided us with a unique data set: just in a single day, we crawl more than 35 million webpages and collect data. So we started to work on AI technology to leverage this data, our own clients’ data and a set of rules derived from industry best practices to build a predictive insights engine. This “content marketing intelligence” module automatically comes out with recommendations on how to generate more results from content without doing more work.
What do you see as the limitations of artificial intelligence as it exists today?
The main limitation is that building systems where AI replaces humans 100 percent is really, really hard. We still don't have 100 percent self-driving cars, and when we do it’ll be the result of a huge effort by the biggest tech companies in the world.
Luckily, there are lots of applications where AI can be used to empower humans rather than replace them. When AI is used to crunch data to come out with recommendations for instance, it still provides a lot of value if these recommendations are “right” only 80 percent or 90 percent of the time—because humans can quickly determine the correct actions from the incorrect ones.
We think about these types of applications as “humanrithms,” as they combine humans and smart algorithms. I think we’ll see a lot of humanrithm in the next few years, as it’s much easier to build AI that is almost always right (to empower better or faster human decisions) than it is to build AI that is systematically right (to replace humans).
What do you see as the future potential of artificial intelligence in marketing?
Marketing is becoming data science.
AI can solve the old problem of “not knowing which 50 percent of my marketing does work.” By analyzing the vast amount of data that is now available to marketers, combining it with other data that they typically don’t have access to and applying machine learning, AI can help marketers understand how their campaigns and actions work like never before. And even better: provide insights on how to amplify results.
What makes Scoop.it different than competing or traditional solutions?
Most content marketing tools focus on solving workflow problems: how to efficiently move content from stage A to stage B and then stage C, etc., all along the content marketing cycle. We do that too. But we also help with generating more and better content through our research and curation technology, and generating impact with content through our predictive insights and content marketing intelligence technology.
Once you’ve understood the basic content marketing methodology, these two problems are the ones that typically remain as the main challenges.
Who are the prototype customers in terms of company size and industries?
Customers who are looking to generate ROI from content and realize that the odds are against them, as according to Content Marketing Institute, only 30 percent of marketers say they’re effective with content marketing. Customers range from SMBs concerned that they won’t have enough resources to create content at scale, to larger enterprise clients who have invested a lot in content but want to extend its lifetime to generate returns from that investment.
What are the primary use cases of your product(s) for marketers?
Today, it’s still around generating more and better content. A lot of marketers come to us to scale the volume of content they publish on their blogs, social media or newsletters. But as we launch our content marketing intelligence features, it’s rapidly evolving to also finding ways to generate impact with that content.
Any other thoughts on AI in marketing, or advice for marketers who are just starting to explore the possibilities of AI?
As with any new trend, there is and there will be a lot of hype around AI. I’d recommend not to look at using AI for the sake of using AI, but rather to focus on the problem you’re trying to solve. We don’t pitch our platform as an AI platform: we try to be the best at solving problems our clients have around content production and generating content impact.
About Paul Roetzer
Paul Roetzer (@paulroetzer) is founder and CEO of PR 20/20, author of The Marketing Performance Blueprint and The Marketing Agency Blueprint, and creator of The Marketing Artificial Intelligence Institute and Marketing Score. Full bio.