How to Automate Supply Chain Risk Reports: A Guide for Developers
Do you use Python? If so, this guide will help you automate supply chain risk reports using AI Chat GPT and our News API.
Media monitoring and media intelligence are a crucial part of any marketing mix. Media intelligence platforms were purpose-built to analyze billions of online data points and synthesize insights into content performance, industry and social trends, and brand equity.
Media intelligence was designed to plumb the depths of a brand’s share of voice and reach, offer guidelines for crafting effective influencer strategies, provide crucial benchmarking of competitors and audience demographics, and shape customer experience management, topic analysis, and PR impact analysis.
However, if your media intelligence platform is a finely-tuned Formula One racecar, then public, social and editorial media content is the high-octane racing fuel that keeps it far ahead of the other cars on the track. And without that fuel…a racecar is nice to look at but won’t win many races.
That’s why savvy media intelligence providers are increasingly choosy about the data with which they feed their platforms.
With new content posted every minute, keeping up is no joke. A media intelligence solution needs to literally scan millions of stories from media platforms, blogs, and influencers – as well as looping in accurate readership, audience, sentiment, engagement, and other metadata. This is a LOT of data – and it needs to be easily accessible via the right News API with the right data.
How can you tell which News API is the best fit? Start with these three criteria for evaluating data for media intelligence:
It’s worth zooming in on two additional aspects of data coverage (discussed above): content diversity and history.
Brand buzz happens across a wide range of formal news sources and informal media. It’s crucial that your media intelligence data feed cover the full and rich scope of the online content ecosystem – including:
Also, today is relevant only in the context of yesterday. This means that to be effective, media intelligence needs access to historical data, even if that data is no longer publicly available at its original source. This is crucial to not only identify media mentions today but also to deliver insights based on historical trends. To that end, choose a data solution that has been scanning and archiving data from news, blogs, online forums, and reviews over time.
You can’t run a Formula One car on diesel. For media intelligence solutions to work, they need fuel they can use – i.e. web data they can read. A reliable stream of quality and contextual web data, delivered in a machine-readable format that can be easily digested and integrated (like that provided by our News API), is critical.
The fact is that much news data is unstructured at its origin. This content only gains structure after various data extraction techniques are applied. One study found that up to 73% of the content in English articles needed to be cleaned up in order for media intelligence and other solutions to be able to use it.
This means that media intelligence providers need to choose their data providers carefully, to ensure that the insights their solutions deliver are based on the right quality and quantity of data. By choosing a professional News API (like Webz.io’s) providers can focus more on their core competency – creating outstanding media intelligence solutions – and less on structuring data or ensuring that it is sufficiently enriched.
To maximize insights and minimize efforts, it’s best to leave the news data collection to the experts – and use a simple API to start scaling. Webz.io’s News API constantly consumes news data from millions of sources, in over 170 languages from across the web. It uses NLP to distill the meaning and sentiment behind every article, story, and image – in near real-time. This data is structured and enriched to make it quickly and easily readable by media intelligence platforms. The end result: better media monitoring insights based on better data.
To see how Webz.io can provide your media intelligence solution with the fuel it needs to roar past the competition, talk to one of our experts today!
Do you use Python? If so, this guide will help you automate supply chain risk reports using AI Chat GPT and our News API.
Use this guide to learn how to easily automate supply chain risk reports with Chat GPT and news data.
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