Questions
What people need to understand, including recurring questions, follow up questions and knowledge gaps.
Clicks show movement. Surveys answer the questions a company decides to ask. Dialogue reveals how people connect their needs, doubts, language and intended next steps.
From dialogue to direction
People rarely think in the categories used by websites, departments or reports. A technical question can become a discussion about everyday use. A price question can reveal uncertainty about value. A request for product information can lead to a service need or a clear commercial next step.
PulseDialog preserves this conversational context. It helps teams understand what people are trying to resolve, where the brand experience creates friction and which improvement deserves attention.
The PulseDialog method
PulseDialog begins with a decision that needs better evidence, not with a desired marketing conclusion. The data scope, signal model and review process are defined before findings are interpreted.
Signal model
The exact taxonomy is adapted to the business question. The following signal families provide a durable foundation without forcing every project into the same categories.
What people need to understand, including recurring questions, follow up questions and knowledge gaps.
What a person appears to be trying to achieve, compare, decide, use, resolve or do next.
The real situations, constraints and priorities that turn a generic product fact into a personal decision.
Where information, terminology, process, service or the conversational experience makes progress harder.
The words, comparisons and expressions people naturally use when they describe needs and uncertainty.
Evidence that can inform knowledge, content, product, service, marketing or the next version of the AI interface.
Cross sector field notes
The same method reveals a different route in every category. PulseDialog keeps the relationship between the first question, personal context, comparison and the next practical action visible.
01 · Industry · Automotive
Finding
People connect specifications and price with the way they drive, the space they need, their budget and the action that would move the decision forward.
Paraphrased examples
Observed in conversations from Peugeot 2008 AI Ambassador, Peugeot 3008 AI Ambassador and the current Leapmotor conversational interface.
02 · Industry · Gaming
Finding
People describe what they remember or feel like playing, refine the choice through genre, popularity or social context and expect a direct route to the right game.
Paraphrased examples
Observed in conversations from current PlayBuddy conversational interfaces.
03 · Industry · FMCG
Finding
People move from a meal idea or ingredient to practical preparation, personal constraints, seasoning choices and the products needed to complete the task.
Paraphrased examples
Observed in conversations from Kotányi AI Chef and Mojster AVE.
The value is not in any single question. It is in the patterns that reveal what people are trying to decide, where they hesitate and what would help them move forward. PulseDialog turns those patterns into priorities for content, products, services and the conversational experience.
From finding to ownership
Clear findings with scope, context, confidence and limitations.
Documented categories and metric definitions for consistent interpretation.
Eligible, appropriately protected examples that explain why a pattern matters.
Each finding connected to a possible action, responsible team and intended outcome.
Prioritised changes to knowledge, content, service, product or the AI experience.
A defined reference point for later analysis after an improvement is introduced.
Business application
Customer language, content priorities, comparison context and communication gaps.
Unmet needs, feature questions, use cases and emerging product opportunities.
Recurring difficulties, ownership questions, handover needs and clearer guidance.
Missing knowledge, weak answers, safety boundaries and conversational improvements.
Quality, privacy and limits
PulseDialog analyses only the dialogue included in the agreed purpose and scope. The method documents what the evidence can support and where another form of research is still required.
Documented applications
PulseDialog is informed by Retoba's work with real brand owned conversational interfaces. Each case demonstrates a different path from dialogue to organisational learning.
Business impact30%increase in sales opportunities recorded for the Peugeot 2008 project.
View the Peugeot case studyEngagement and product insightNearly 40%of conversations reflected emotional engagement. Three new product proposals were also identified in under five months.
View the Kotányi case studyScale and conversation depth20,000conversations analysed with Retoba PulseDialog; 73% of questions developed into a discussion.
View the GYM24 case studyIndependent recognitionAI GamechangersPlayBuddy was featured as a personalised game discovery assistant whose conversations reveal player preferences, frustrations and unmet content demand beyond conventional analytics.
Read the AI Gamechangers interviewWays to work
A defined business question and an agreed conversational dataset, analysed to establish the main signals, limitations and priorities.
Repeated analysis that tracks emerging questions, changing needs, recurring friction and the effect of updates over time.
Findings connected directly to changes in knowledge, content, service, product or the AI interface, followed by a new review.
Clear answers
Method and reference layer
PulseDialog methodology developed and maintained by Retoba. Each analysis starts with a defined business question and turns conversational patterns into actionable insights for improving content, products, services and customer experience.
Begin with a business question
We begin by defining the question, eligible data and decision the analysis should support. PulseDialog can analyse conversations from brand interfaces developed or managed by Retoba, or from other agreed sources under appropriate safeguards.