Otto Monitor

Media Management

Objectively identify core media outlets and reporters based on article tone and performance data.

Analyze social influence together with media outcomes to build a data-driven media-relations strategy.

Contact Us

Media Management Overview

If media management in traditional PR teams depended on each staff member's network, this service now supports it from a statistical point of view. It objectively identifies truly friendly media outlets and core reporters based on article tone and performance data, then helps manage them according to results.

It also extends into social media by analyzing audience scale, content tendency, and actual influence comprehensively to discover the key influencers who best fit the brand.

This makes it possible to establish efficient media-relations strategies grounded in data rather than intuition.

Real-world use cases

Case 1

Maximizing media day efficiency through data-based media analysis

Background

Company A held media days regularly for major announcements and new product launches.

But because reporter outreach depended mainly on the existing network and personal relationships of the team, the pool of invited outlets remained limited and there were clear limits to discovering new outlets and reporters.

As a result, there was a constant risk that the event would remain centered only on media already in regular contact.

Solution and outcomes

Company A adopted Monitor Wizard and used it to analyze article volume, article tone, and PR Value related to the company on a monthly or quarterly basis.

It then built media day invitation lists using that objective data.

As a result, the company was able to discover and successfully expand its network to include outlets and reporters that were not in the existing network but had real influence or high relevance.

It also became possible to manage friendly relationships more systematically by identifying outlets or reporters with negative tone and proactively inviting them to events for direct communication.

Even in media networking, approaching the work through objective data rather than personal familiarity helped establish a more strategic foundation for PR activities.

Case 2

Data-based influencer discovery and profile analysis

Background

Company B actively used influencer marketing to maximize viral impact on social media.

But outreach criteria often depended on simple indicators such as follower count, or were limited to lists supplied by a specific agency.

This created high risk of paying heavily for influencers who did not fit the brand image or whose actual follower response rates were weak, and made it difficult to find the optimal influencer for each campaign.

Solution and outcomes

After adopting Monitor Wizard, Company B was able to analyze influencers directly.

The system went beyond follower count and analyzed each influencer's main content tendency, such as beauty, IT, or daily life, along with brand affinity and actual follower-response rates in a more multidimensional way.

As a result, Company B could strategically compose the most suitable mix for each campaign, from large influencers to micro-influencers.

In particular, the dashboard made it possible to set desired conditions and extract candidate lists through simple interaction, dramatically reducing the time and resources required for influencer discovery.

Key features that enable Media Management

Data Collection

Monitor Wizard collects keyword-based data from more than 3,000 news outlets including Naver and Daum, as well as searchable major social-media channels such as blogs, cafés, communities, YouTube, and Instagram.

Through a proven system, it supports either real-time crawling or scheduled crawling up to five times a day depending on client needs, and it also supports stable historical-data collection for trend analysis.

Learn more
N
D
News
blog
C
f
X
IG
Other searchablefully customizable media sources

Data Management

Collected raw data is first cleaned through excluded keywords, excluded URLs, and deduplication, then stored in the database in a form optimized for analysis.

Stored data then goes through a second refinement stage in which AI interprets context and tags each item for positive/negative sentiment, mention importance, and core topics, so the final dataset is managed in a state ready for insight generation.

Learn more

Data collection

News
Social
Blog

Initial filtering

  • Excluded keyword
  • Excluded URL
  • Deduplication

DB storage

AI tagging

Final data

Sentiment analysis

72%

28%

Mention importance

Core topics

Topic ATopic BTopic C

Dashboard

The dashboard presents collected raw data through intuitive visualizations so teams can quickly understand both quantitative and qualitative analysis at a glance. Quantitative indicators such as daily buzz volume and channel share are shown alongside qualitative insight such as positive/negative opinion trends and major keyword trends derived from AI sentiment analysis.

This helps teams move beyond raw scale and identify the key information needed for business decisions quickly and accurately.

Learn more
monitorwizard
1
2
3
4
11
12
13
14

Experience the next generation of intelligencebuilt by Otto Monitor with AI and experts together

Contact Us