Crisis Management

Detect warning signs across news and social media quickly and secure the golden time for response.

Analyze issue-spread paths and shifts in public opinion to support effective response strategy.

Crisis Management Overview

In online crises, fast detection and response matter more than prevention alone. This service secures the golden time by sending real-time alerts the moment negative keywords are captured across news or social media.

When an issue occurs, it supports effective corporate response by analyzing spread paths and issue flow from multiple angles. After the issue ends, it also provides a report that comprehensively analyzes the full process from emergence to resolution, the response strategy, and shifts in public opinion. That report becomes key reference material for future similar crises.

Real-world use cases

Case 1

Securing the golden time for crisis spread through AI-based real-time alerts

Background

Company A had been monitoring major communities and social platforms to manage reputation around its customer service.

But with a workflow where staff searched keywords themselves and checked posts one by one, it was impossible to review in real time every piece of content pouring in by the tens of thousands each day.

As a result, the company failed to detect a small consumer complaint early, and that post was later quoted in the press and escalated into a major issue.

Company A urgently needed a system that could automatically identify real potential crisis signals within massive volumes of social buzz and enable immediate response.

Solution and outcomes

Company A adopted Monitor Wizard's crisis-management system.

It configured AI to perform first-pass positive and negative sentiment classification on all social posts collected through company- and product-related keywords.

After launch, when a negative customer-service experience was posted in a specific community, AI immediately detected it as a negative issue and sent a mobile alert to the person in charge.

The team was then able to understand the situation and respond quickly within the golden time before the post spread to the media or other channels.

This allowed Company A to build an early-response structure that did not miss real crisis signals hidden in large volumes of buzz.

Case 2

Identifying potential crisis patterns by building a real-time negative-issue dashboard

Background

Company B sold a typical high-involvement product, so a wide range of customer VOC around product defects and service complaints continued to appear primarily in major communities.

Because content ranged from simple expressions of dissatisfaction to serious claims of defects, it took significant time to determine which issues required an immediate response.

Even when complaints were gathered together, it remained difficult to identify the pattern of what kinds of negative issues were newly appearing and spreading.

Solution and outcomes

Through Monitor Wizard, Company B not only collected major community posts in real time and used AI to identify negative posts, but also built a system that automatically summarized the core of each issue and grouped it by type.

For example, issues automatically classified as after-sales-service complaints, delivery errors, and product-function defects were visualized through a dashboard.

As a result, the team was no longer buried in individual posts and could instead see which negative issues were gradually growing and which new issues were being created.

This enabled not only potential-crisis response, but also a proactive management framework that used collected data to improve products and services.

Case 3

Producing an issue-spread and response white paper after a major crisis ended

Background

Company C experienced a major negative issue due to owner risk.

The immediate fire was put out, but the original issue spread through social media in numerous fragmented branches.

Because of this, the company had great difficulty understanding the overall flow of public opinion, how press coverage and social-media reactions interacted in detail, and how much real brand-image loss the issue had caused.

Solution and outcomes

Once the official issue had ended, Company C used Monitor Wizard to run a comprehensive post-issue analysis project.

It collected all related news articles, community posts, social-media buzz, and netizen reactions, then reconstructed the full lifecycle of the issue from occurrence to spread to disappearance in chronological order.

In particular, it compared news volume and social-buzz volume from multiple angles to identify which channels and messages had the most decisive effect on public opinion.

It then quantitatively and qualitatively analyzed the actual brand-image loss and published a comprehensive issue-response analysis report, effectively a white paper, that organized the full process systematically.

This material became an important internal response manual that Company C could reference and use when similar crises arise in the future.

Key features that enable Crisis 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.

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News

blog

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Other searchablefully customizable media sources

Real-Time Alerts

Real-time alerts collect data continuously on the critical issues you define, such as specific topics or negative issues, and use AI analysis to notify you immediately.

Alerts can be sent not only by email but also through mobile channels such as MMS, Kakao notifications, and Telegram, so teams can recognize issues quickly from anywhere.

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MMS

Delivers images and content together by text message

Kakao notification

Notification messages sent through KakaoTalk

Message delivery to Telegram channels or groups

MMS

Delivers images and content together by text message

Kakao notification

Notification messages sent through KakaoTalk

Message delivery to Telegram channels or groups

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.

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Crisis Management