Smartocto

Would you like a content strategy that helps you build a strong rapport with your audience?

Press agencies are the first to collect news, spread it to media outlets and thus make news scalable. But in the last decade this service has gradually come under pressure. Smartocto will create a powerful impact model of content and a simple interface, and will send it to multiple media outlets that can easily train the model based on their content and performance data. A segment of the model — on press agency content — can be used to inform and notify agency organisations like PAmedia. At the same time, the exchange of data from one partner to another is not necessary, only trained models increments are exchanged.

Smartocto

Content analytics provider smartocto BV smartocto wanted to simplify the deployment of its machine learning ML models so that it could deliver richer editorial analytics and improve its customer satisfaction. The company had been using a combination of open-source and cloud solutions to self-host its ML workloads, but this combination of solutions was becoming increasingly time consuming to manage. In , smartocto worked alongside the Amazon Web Services AWS team to build a proof of concept to test Amazon SageMaker , which gives users the ability to build, train, and deploy ML models for virtually any use case with fully managed infrastructure, tools, and workflows. A few months later, smartocto decided to migrate all its ML models to Amazon SageMaker, freeing its team to focus on innovation. In less than 3 months, the company developed and deployed a predictive editorial analytics solution called Smartify , which helps its customers create relevant, engaging content and grow their audiences. Founded in , smartocto provides content analytics to newsrooms and media companies around the world through its smartocto system, which features both near-real-time and historical data features. To drive its analytics, the company uses ML, which it supports using a combination of open-source products and AWS services, including Amazon Elastic Compute Cloud Amazon EC2 , which provides secure and resizable compute capacity for virtually any workload. Further, those teams had to complete several manual tasks as a part of the onboarding process, which made the overall process prone to human error. After completing the proof of concept, the company worked to migrate several of its existing ML models to different Amazon SageMaker endpoints, which smartocto completed in a few months. Because smartocto could support predictions in near real time, the company decided to develop Smartify, a predictive editorial analytics solution that uses ML to forecast the expected engagement, such as click rates, likes, and shares, of a news post on a particular channel. Smartocto began developing Smartify in February , and to upskill its staff and accelerate its time to market, the company engaged AWS Training and Certification , which helps participants learn from AWS experts, advance their skills and knowledge, and build their future in the cloud on AWS. The company also relied on the AWS team for technical support. One of the features that smartocto uses is Amazon SageMaker Studio , the first fully integrated development environment for ML. In less than 3 months, smartocto finished developing Smartify, and the company quickly deployed the solution to production—an estimated 6 months ahead of schedule. Using Amazon SageMaker, smartocto has achieved a 10 times lower resource usage per ML model while delivering better predictions.

These customers have been very happy smartocto the insights that they can glean from using Smartify to improve their content and grow their audience. Download the playbook and supercharge your content strategy, smartocto.

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This guide, written in collaboration with user needs evangelist Dmitry Shishkin , is part of a series on writing news stories based on the news needs approach. These six different editorial treatments of a news event, focusing on other details of the story besides the cold, hard facts, can offer more value to the reader. This has been proven on many occasions in various settings. The ultimate goal of the user needs approach is to connect to the audience in a stronger, more meaningful way - creating more engagement and loyalty in the process and increasing the relevance of your brand. We created a new User Need Model in March

Smartocto

Omroep Brabant have been keen pioneers of applying the user needs for news theory to the real world ever since we started our research. In this interview, we spoke to their editor, Janneke Bosch, about how the Dutch regional player incorporated the user needs theory into their newsroom - and share the results of that endeavour. Would you like a content strategy that helps you build a strong rapport with your audience? In that case, the user needs-driven approach is your way to go.

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We use cookies to ensure that we give you the best experience on our website. Disabling these cookies might remove some functionality from the website. Increased monthly cost savings by hundreds of dollars. We couldn't be more satisfied with smartocto. Would you like a content strategy that helps you build a strong rapport with your audience? Read the full review on G2. Necessary cookies are absolutely essential for the website to function properly. It helps the editorial team to get more data driven. Headquartered in the Netherlands, smartocto BV provides content analytics driven by ML to newsrooms and media companies around the world. One of the features that smartocto uses is Amazon SageMaker Studio , the first fully integrated development environment for ML. In that case, the user needs-driven approach is your way to go. This category only includes cookies that ensures basic functionalities and security features of the website. User needs are extremely valuable for our paid content strategy. Aleksandra is certified PRINCE2 Project Manager and currently she is leading multiple different projects which involve more than 60 small and local news outlets. With these savings, smartocto plans to iterate new versions of Smartify that will include more analytics and features for its customers.

Since we launched our comprehensive User Needs Model 2. Update: on 13 December , much of what we have learned about user needs came together in an Ask Me Anything webinar session. We keep receiving the same questions, which is why Dmitry Shishkin and Rutger Verhoeven took ample time to elaborate on strategy, cultural change, implementation, recognition, and artificial intelligence.

Now, the company can complete the onboarding process in a matter of days by using multimodel endpoints and hosting a unique ML model for each of its customers. Aleksandra is certified PRINCE2 Project Manager and currently she is leading multiple different projects which involve more than 60 small and local news outlets. Goran S. A few months later, smartocto decided to migrate all its ML models to Amazon SageMaker, freeing its team to focus on innovation. To drive its analytics, the company uses ML, which it supports using a combination of open-source products and AWS services, including Amazon Elastic Compute Cloud Amazon EC2 , which provides secure and resizable compute capacity for virtually any workload. Ending Support for Internet Explorer Got it. Further, those teams had to complete several manual tasks as a part of the onboarding process, which made the overall process prone to human error. Learn from AWS experts. These cookies are necessary for the correct functioning of the website. Personalisation cookies. This website uses cookies and similar techniques to deliver an optimal end-user experience. These cookies allow for embedding content from third-party websites, such as YouTube.