Turn scattered news, mentions, and signals into actionable market intelligence

What is Market Intelligence and Reputation with AI?

AI-based market intelligence enables organizations to move from reactive newsgathering to a proactive system that detects, classifies, and prioritizes relevant signals from their competitive, reputational, and regulatory environment. Q2BSTUDIO designs continuous monitoring solutions that combine agreed sources, entity resolution, thematic classification, contextualized sentiment analysis and generation of executive briefings with links to the original sources.

The starting point is the definition of the monitoring perimeter. Together with the client's team, we identify the relevant areas: direct and indirect competitors, the brand itself and its variants, key products and services, relevant people, sectoral regulations, emerging technologies and market trends. This perimeter is translated into entities, search terms, filters, and relevance rules that the system uses to separate the signal from the noise.

The sources of information are selected with criteria. We include mainstream and industry media, competitor websites, official regulatory sources, specialized feeds, technical publications, and platforms with authorized public access. We do not make claims about full market coverage, because it depends on the sources available and accessible for each sector and geography. We define the scope transparently and adjust it according to the results.

The resolution of entities is a fundamental technical step. When a competitor, brand, or product is mentioned, the system must identify that different variations, abbreviations, or trade names refer to the same entity. This prevents duplicates and loss of information. We use resolution models supplemented by a client entity dictionary that is kept up to date.

The thematic classification assigns each detected signal to categories relevant to the business: product launch, price change, alliance, acquisition, regulation, reputational crisis, customer opinion, relevant vacancy, technological change. This ranking is combined with a level of relevance that prioritizes signals based on their potential impact. Highly relevant signals generate immediate alerts; those of medium relevance are grouped into periodic briefings.

Sentiment analysis is applied with professional caution. It's a useful signal for spotting general trends, but it's not an absolute truth. It works reasonably well in informative texts and explicit opinions, but it can fail with irony, sectoral jargon, ambiguous texts or languages with cultural nuances. We always show the source and level of trust, adjust the categories to the client's domain, and recommend human review for sensitive reputational decisions or crisis communications.

Executive briefings are the primary consumer interface. Instead of a flood of raw articles, the team receives periodic summaries organized by topic, competitor, or market, with the most relevant signals, trends identified, and links to the original sources for further research. Briefings are tailored to the format and frequency the team needs: daily email, weekly dashboard, monthly report, or a combination.

Urgent alerts complement briefings for situations that cannot wait for the next cycle: mentions of crisis, regulatory changes with immediate impact, significant movements of competitors or reputational anomalies. Each alert includes enough context to assess the situation without the need to investigate from scratch.

Reputation monitoring covers brand mentions in media, forums, reviews, and public platforms. The system detects trend changes, mention spikes, recurring topics, and signs of satisfaction or dissatisfaction. However, the final assessment of reputation and communication decisions require human judgment: the system informs and prioritizes, but does not replace the communication team.

From an operational point of view, the system requires continuous maintenance: updating of entities, calibration of relevance, incorporation of new sources, adjustment of filters and periodic review of the quality of the classifications. The Q2BSTUDIO team accompanies this operation with coverage metrics, classification accuracy and satisfaction of the receiving team.