Intelligent Workflow

Intelligent Customer Data Relationship Mapping

Connect customer data, history, interactions, and signals to uncover patterns, opportunities, risks, and actionable insights through AI.

Customer Intelligence Graph Customer data connected into a relationship network that drives business value.

Relationship Intelligence Connections across activity, history, contracts, orders, and incidents.

Customer context A contextualized view of each customer, account, opportunity, or situation.

Actionable insights Insights designed to support commercial and operational decisions.

Intelligent workflow

From scattered data to customer relationship intelligence

The objective is not to display customer information, but to connect it, contextualize it, and transform it into actionable insights for sales, operations, and customer experience.

Data capture

CRM
ERP
Analytics
Databases
APIs

Consolidation

Unifies customers, contacts, orders, contracts, opportunities, incidents, interactions, campaigns, and digital behavior.

Identity and context

Resolves duplicates, connects entities, and groups accounts, contacts, locations, history, and operational context.

Relationship correlation

Connects sales activity, purchases, incidents, contracts, interactions, digital signals, and customer evolution.

AI: patterns and signals

Discovers patterns
Detects anomalies
Correlates events
Contextualizes changes
Generates hypotheses

AI Customer Graph BI

Opportunities

Identifies sales opportunities, expansion potential, recurrence, loyalty opportunities, potential services, and growth signals.

Risks and anomalies

Detects declining activity, recurring incidents, falling engagement, churn risk, and signs of dissatisfaction.

Actionable conclusions

Generates summaries, conclusions, explanations, recommendations, and next steps tailored to each customer context.

Activation

Trigger n8n
Update CRM
Create task
Notify signal
Connect systems

Oversight and improvement

Sales, operations, and management teams validate relevant insights, refine criteria, and improve the model.

Data → context → relationships → patterns → opportunities → risks → conclusions → action

From Digital Challenges to Intelligent Workflows

From viewing data to understanding customer relationships

Customer data does not create value simply by being stored, but through the relationships it reveals across activity, behavior, history, opportunities, and incidents.

This Intelligent Workflow transforms scattered information into a customer intelligence graph focused on insights and action.

Operational need

Lots of customer data, limited actionable context

CRM, ERP, analytics, contracts, orders, and incidents often contain partial views of the customer relationship, but rarely provide a connected and explanatory perspective.

The limitation of the traditional model

Customer 360 does not always mean customer intelligence

Consolidated data with limited relationship mapping.
Duplicates or inconsistencies across systems.
Sales history disconnected from incidents and operations.
Opportunities and risks that are difficult to detect in time.
Insights dependent on manual review.

Connected architecture

Systems and technologies involved

CRM

ERP

CDP / Databases

BI / Analytics

Interactions

APIs

n8n Workflows

Generative AI

Sales Tasks

Operational benefits

More context, better insights, and more precise commercial decisions

Complete contextcustomer, history, signals, and interactions connected

Pattern discoverybehaviors, anomalies, and relationships detected by AI

Visible opportunitiescommercial potential and growth signals identified

Anticipated riskschurn, declining activity, or recurring incidents detected

Actionable insightsbusiness-oriented explanations and next steps

Enriched knowledgeprogressive improvement of each customer profile and relationship

Continuous learningongoing improvement from signals, actions, outcomes, and decisions

Turn your customer data into actionable relationship intelligence

We design Intelligent Workflows that connect CRM, ERP, analytics, AI, and sales workflows to uncover real relationships, insights, and opportunities.

The classic challenge of relating this information with other customer data and drawing conclusions

Analyze the information that the client provides you.

There are customers who clearly show their interest in your products and services. There are also others who do not, who answer things like: Right now I have no need, it is only to know the offer for the future, etc.

You must analyze all the answers that the potential client provides, taking good note of what they explicitly state and trying to figure out the things that only hint.

To achieve this, the preparation of the questionnaires is key, the formulation of the questions that you have raised in them: if they are open questions, that help you to know the client better or if they are closed, that allow you to better evaluate if they really have the need and the intention to buy.

analizar informacion a traves de cuestionarios

Relate this information with the other customer data that you have.

The first thing is to check if we already have information about that potential customer, if they have previously purchased any of our products or services.

Then you have to analyze it: If you are already a customer, see the history of contacts with the company and the products you have bought in the past, in order to better understand their needs and motivations.

There is a special case: that the potential customer has previously contacted us but has not purchased any of our products. In this case, it is essential to try to know why, what made you not decide on our offer: the price? The benefits of the product? Has it been our brand-company that has not convinced you?

relacionar informacion con datos del cliente

Draw conclusions: Deduce if the lead is a real opportunity.

When we cross the existing data with those obtained by qualifying, we can make more informed decisions and know if the operation is really a business opportunity or not. If we decide that it is, it must be registered in the commercial management system, so that the commercials can start working on it as soon as possible.

It is also important to get an estimate of the potential profitability of the opportunity, both in the short and long term. This will help us see how much commercial effort we can and should put into the opportunity.

You have to be careful because many times today’s opportunity is small but the client is big and winning it would open a very fruitful path for us in the future. Consider these cases as an investment and dedicate a greater effort than the opportunity alone would recommend.