Intelligent Workflow

Intelligent Product and Service Recommendations

Interpret customer needs, interest signals, and business context to recommend relevant products and services through AI, personalization, and connected sales workflows.

Recommendation Intelligence Recommendations based on context, intent, and real opportunity.

Next Best Action Sales actions prioritized by customer need and timing.

Personalization Experiences tailored to behavior, history, and customer journey.

Conversion Intelligence More relevant propositions to increase response and revenue.

Intelligent workflow

From customer signals to actionable commercial recommendations

The objective is not to display products, but to understand needs, detect intent, prioritize opportunities, and activate personalized propositions with full commercial traceability.

Signal capture

CRM
eCommerce
Analytics
Campaigns
APIs

Customer context

Consolidates history, purchases, interests, browsing behavior, interactions, segment, lifecycle stage, and commercial data.

AI: need detection

Interprets behavior
Detects intent
Correlates history
Identifies needs
Recommends options

AI CRM Analytics

Offer-customer fit

Matches products, services, availability, value, compatibility, commercial timing, and likelihood of interest.

Recommendation ranking

Prioritizes recommendations by relevance, margin, need, recurrence, customer journey stage, and conversion potential.

Personalized proposition

Generates the message, offer, sales argument, content, or proposition adapted to the most appropriate context and channel.

Commercial activation

Trigger n8n
Update CRM
Send proposition
Create task
Notify opportunity

Follow-up

Monitors response, conversion, acceptance, rejection, interaction, feedback, recurrence, and commercial outcomes.

Oversight and improvement

Sales teams review strategic recommendations, refine criteria, and validate sensitive propositions.

Signals → context → need → fit → recommendation → activation → follow-up → learning

From Digital Challenges to Intelligent Workflows

From guiding customers to personalizing commercial decisions

Intelligent recommendation is not about showing more products, but about better understanding each customer’s need, timing, and commercial context.

This Intelligent Workflow transforms customer signals into relevant propositions, sales actions, and continuous learning around conversion and loyalty.

Operational need

Too many options, limited relevance for each customer

Products, services, campaigns, and opportunities are often managed generically, without sufficiently connecting history, behavior, interest signals, and journey stage.

The limitation of the traditional model

Recommendation is not the same as personalization

Offers based on generic campaigns.
Cross-selling without real need-based context.
Customer data scattered across CRM, eCommerce, and analytics.
Propositions poorly aligned with the customer’s commercial moment.
Limited learning about which recommendations work and why.

Connected architecture

Systems and technologies involved

CRM

ERP

eCommerce

Analytics

CDP / Databases

APIs

n8n Workflows

Email / Campaigns

Generative AI

Operational benefits

More relevant recommendations, higher conversion, and stronger loyalty

Need detectionbehavior, history, and intent interpreted with business context

True personalizationpropositions adapted to each customer, moment, and channel

Next best actionsales actions prioritized by opportunity

Higher conversionrecommendations designed for response and commercial value

Stronger loyaltymore useful, relevant, and consistent customer relationships

Revenue opportunitiescross-sell, up-sell, and retention with stronger decision criteria

Continuous learningimprovement based on acceptance, rejection, conversion, and recurrence

Turn your customer data into intelligent commercial recommendations

We design Intelligent Workflows that connect CRM, eCommerce, AI, behavior, and sales workflows to recommend better, convert more, and build loyalty through greater relevance.

The classic challenge of guiding customers towards your products and services.

Use your historical data to personalize your products and services as much as possible.

Remember that the people who buy from you are more important in your business than the products and services you manufacture. The key is more to satisfy the specific needs of a certain customer profile than to manufacture the best of the products. In the case of services, things are even clearer.

For this you can and should use the information you already have about your customers. Customers tell us about their preferences every time they interact with us, whether they buy or not, and we must listen to them, we must dive into our historical data and try to answer questions such as: What needs do our customers have? Are they functional or emotional? Or a mixture of the two?

The answers show us what should be the orientation of our products and services. If we know what problems our clients have, we can guide our services to give them the most appropriate solutions. If we stay with a product focus, it is more difficult to offer differential value and it is easier to end up in a price war.

utilizar datos historicos para personalizar tus productos

Make customer service a priority

Customer service is today an added value to products and one of the most appreciated by customers, that is why you must take care of it so much. It is important to note that customer focus is both an attitude, a disposition, and an aptitude, a capacity that we must develop and practice continuously.

We must try to know the customer’s expectations regarding the service they want to receive, as they are as important as those they have on the products. For this we can also use the historical record of the interactions you have had with our company, both positive and negative.

In any case, quantifying the perception of customers about the level of service received is an even more complex task than knowing their perception of our products. Some clues to achieve this can be the following:

Listen to your customers: offer communication channels and check their comments.
Set and meet satisfactory response times for incidents.
Take care of automatic response systems, above all, reduce waiting times.