Content marketers share a few common problems. They don’t know how their content performance compares to competitors or their industry. They often don’t have a complete picture of the content they have available. And they need help figuring out what content their audience truly desires.
All three problems have solutions thanks to artificial intelligence tool Concured. The solution uses natural language processing and deep learning to score and improve content marketing for enterprises. It can identify content gaps, conduct automated content audits, and recommend high-performance content topics. We spoke with Concured CEO Tom Salvat to learn how the solution works.
Concured's AI-powered content marketing platform tells you exactly what to write about that will cut through the noise, fill your knowledge gaps, resonate with your audience and increase ROI whilst reducing costly waste.
Concured’s product has natural language processing (NLP) at its core. Our platform automatically detects new content published on the web (such as blog posts, news articles or thought leadership reports) relevant to our clients, then tags and categorizes these by identifying their most salient keywords, mapping these to a knowledge graph, then auto-clustering the keywords into a subset of representative topics.
Correlating social engagements (likes, tweets, pageviews etc) on the original content against the topics then translates to a topic score, which ultimately allows our clients to identify the best opportunities for new content creation.
Separately, we use a deep-learning based prediction algorithm to identify how topic popularity changes with time, so that our platform can highlight topics that are forecast to trend up in the coming week.
There is a huge challenge facing marketers in this age of never-ending content being pumped out on multiple channels. The reality is marketers are spending 70% of their time creating content that only works 30% of the time.
AI and the latest advances in tech can help marketers better understand their audience and content consumption so that content performance and ROI increases.
Concured’s vision is to be the number one content intelligence company in the world to help our clients better understand the interests of their audience so they can deliver content that engages, educates, and inspires.
Our tool allows us to help our clients with three core solutions: Content Intelligence that guides the ultimate strategy for success, Content Creation by partnering with the world’s leading writers, and Content Optimization that maximizes the return of content investment through personalization and amplification.
As with many “big data” systems, the more the better!
In our world, the data is content ingested by our system, relevant to our client’s industry. For the content sources analyzed, which are typically a mixture of competitors and industry publishers, we recommend a base of at least 1,000 articles published within the preceding 12 months, then at least 100 new articles ingested per new content brief to be created.
In short, this means that marketers who intend to publish more often will need to track more content sources or more prolific outlets to pull in enough new content ideas.
In terms of ideal customers, we look for SMBs and enterprise level companies in finance, tech, travel, media, and healthcare.
AI today is powerful for drawing statistical inferences, but less capable of structured reasoning or extrapolating to new situations. Thus, whether the AI is making analyses, decisions, classifications, predictions or generating something (e.g. text or images), the results are only as good as the data fed into the system—however smart the algorithms or big the computer.
This can lead to bias and blind spots—failure cases in new situations not covered by the data seen thus far.
The biggest quick wins for businesses engaging AI is the automation of repetitive tasks. An example of this is the use of NLP and machine learning within customer service to answer customer service enquiries in an automated way at scale (e.g. British Airways utilizing an automated chatbot).
Another would be creating narratives around structured data using NLP (e.g. automotive listings, and sport results) as these are all costly, time consuming and repetitive tasks that can be automated.
Finally, gaining actionable insights for huge volumes of big data and being able to structure what is previously unstructured at huge scale would be a massive win and push businesses forward (e.g. Grammarly's proofreading, and social media monitoring).
There are many crucial aspects to consider when deciding whether a new tech is right for your organization. It’s easy to be seduced by the perceived opportunity, but this may represent the best-case scenario ignoring the potential risks, blind spots and hidden costs—of which there are often many.
The decision whether to consider adopting an immature tech is made easier if few stakeholders are involved, a small-scale trial is possible, and most importantly, the organization supports experimentation.
Ultimately, regardless of the technology (AI or something else), any new marketing solution adopted must deliver business value, whether better results or cost savings.