Social listening and reputation: 20 questions to turn conversations into decisions.

It is the ongoing process of collecting, classifying, and interpreting public conversations about brands, topics, competitors, and communities. It combines sources, tool, taxonomy, alerts, analysis and consulting.

Resolve blinded to conversations that do not label the brand, emerging reputation, recurring questions, competitive movements, and cultural changes. It also provides evidence for content and service.

A timely report describes a period; sustained listening maintains consultations, baselines, alerts, and learning. The tool retrieves data, but does not determine for itself what a change means.

It makes sense when reputation, market or communities change frequently and decisions need to be made. Also in launches, crises, regulated sectors or brands with a lot of conversation volume.

It is not a priority if there are no questions and no ability to answer. Monitoring everything without accountability creates dashboards that no one uses and can raise the alarm without context.

Objectives, entities, vocabulary, languages, sources, exclusions, risks, frequency and recipients must be defined. Also what is an alert and who can act.

Public mentions, comments, media, forums, reviews and own data authorized according to the scope are used. Each source has limits of coverage, access, representativeness and privacy.

Participate communication, social, attention, insights, brand, risk and business according to the question. An expert must validate taxonomies, irony, context and impact.

The AI can classify themes and sentiment, summarize volumes, group narratives, and prepare alerts. Their categories need proof because languages, sarcasm, and context can produce errors.

People decide impact, response, priority, crisis communication and business changes. They also determine whether a conversation is representative or just a noisy episode.

Tools are chosen by coverage, languages, history, export, queries, permissions, cost and integrations. No platform covers the entire internet; gaps must be made explicit.

It connects with dashboards, alerts, calendars, attention and crisis processes. Integrations must bring context and evidence, not just an automatic score.

An initial setup may be available in weeks, but taxonomy needs calibration. The baselines and interpretation improve with various periods.

It depends on sources, volume, brands, languages, historical depth, frequency and consulting. It is necessary to separate license, configuration, analysis and support.

It is measured with useful coverage, classification accuracy, detection time, informed decisions, evolution of topics and use of reports. The volume of mentions is not a result.

Mistakes are confusing feeling with reputation, ignoring source biases, presenting samples as if they were the market and automating alerts without threshold. We also collect data outside of the purpose.

It is tested with a delimited query, manual sample, category validation and comparison of results. The alerts are simulated before activating a crisis circuit.

It needs to review queries, dictionaries, sources, competitors, dashboards and managers. Changes in platforms can alter coverage and must be documented.

Yeah. A SME can listen to a small set of topics and competitors, with a periodic review. You don’t need a room if the decision is monthly.

Karmina combines ad hoc tool, multi-network listening, reputation, benchmark, trends, metrics and consulting. Agents can prepare classification and summaries; the team interprets and recommends.