Why recommendations don't reach the agent
1
Too many recommendations, too little relevance
A long list of suggestions eats up the agent's attention and reduces trust in the system.
2
Opportunities detected too late
A customer's decline or a re-order moment only becomes visible after the revenue has already been lost.
3
No feedback to the model
Without knowing whether a recommendation was useful or ignored, the system cannot be improved operationally.
Designed for recommendations that reach the agent and get used
Next Best Action does not just produce a list of suggestions. It produces recommendations that are contextualized, prioritized and explainable.
- Combines customer context with products, history and commercial rules
- Separates the recommendation from its priority, timing and action channel
- Filters out suggestions that break the configured restrictions or rules
- Explains why an action is recommended and which data influenced it
- Lets the agent accept, ignore or correct the recommendation
- Uses feedback for measurement and further optimization
Key features
Upsell
Identifies where a customer can buy more within a relevant category.
Cross-sell
Suggests complementary products based on history, compatibility and rules.
Repeat sales
Detects recurring purchases that should have repeated by now.
Declining accounts
Flags accounts that are buying below their usual behavior.
Prioritization
Opportunity score with an explainable reason.
Feedback loop
Relevant, not relevant, completed: feedback becomes a signal for improvement.
MODULE PREVIEW
Four different commercial problems, not a single algorithm
An upsell opportunity is not the same thing as a retention signal. A customer who should be reordering consumables is different from a customer whose total purchase volume is declining. AI Sales can treat these cases independently and prioritize them based on the data available and commercial rules.
- upsell and cross-sell
- re-order / repeat purchases
- declining customers
- priority, explanation and feedback
THIS IS A MODULE OF AI SALES 2.0 PLATFORM
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Simplified architecture
From data to controlled action
Your ERP and CRM remain the source of truth for operational values. AI Sales adds interpretation, rules, prioritization and workflow on top of your existing systems.
ERP + CRM + history
Signal detection
Rules + scoring
Next Best Action
Human agent
Feedback → prioritization
Benefits delivered by the platform
1
The agent sees what is worth doing now
Not just a score, but an action: call, follow up on the quote, suggest replenishment or wait.
2
The recommendation comes with a reason
The system explains the signal: recurrence, a drop in purchasing, an unanswered quote or a new opportunity.
3
Commercial rules filter the suggestion
Stock, margin, credit and permissions decide which recommendation actually reaches the agent.
Comparison
From simple rules to Next Best Action
Not every recommendation needs the same level of AI. AI Sales can keep simple rules where they are enough and add scoring or agents only where the complexity produces value.
| Level | Static rules | ML recommendations | AI Sales Next Best Action |
|---|---|---|---|
| Trigger | Fixed condition | Pattern in data | Pattern + rules + operational context |
| Explanation | Rule triggered | Varies by model | Signal, evidence and commercial reason |
| Action | Manual | List of recommendations | Priority + prepared action |
| Feedback | Rarely | May exist | Explicit part of the workflow |
A BONUS FOR YOU
Step-by-Step Seller: Next Best Action in B2B with Google Cloud, CRM, and Business Rules
In B2B sales, the role of a Next Best Action module using artificial intelligence is to tell the sales agent what to do at each step. Call the customer? Send a quote? Propose a replenishment or a complementary product added to the order? In essence, it is a step-by-step seller.
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ADDED IN AI SALES 2.0
You can run AI agents on top of your data!
The agent can turn commercial signals into concrete actions, without letting the CRM turn into just a list of tasks.
- tracks changes in orders, opportunities and activity;
- identifies the right moment for the next contact;
- explains why it recommends a particular action;
- can prepare the task, message or quote for the human agent.
Other connected modules
Conversational Analytics & Business 36
Identifies signals in customer history, orders and commercial performance.
See the module
AI Lead Generation & B2B Account Intelligence
Prioritizes the companies and leads worth bringing into the sales process.
See the module
Intelligent B2B Order Taking & Technical Sales
Turns the commercial recommendation into a concrete quote, connected to real products and prices.
See the module
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The AI Sales 2.0 platform includes nine modules. Book a 30-minute presentation.
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We look at the problem, the systems involved and which KPIs can be reached.
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Last updated: 6 November 2026
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