1. B2B sales as a casino?

Imagine you enter a casino for the first time. You pull the lever of the first slot machine - and you immediately win. Euphoria, endorphins, success. What will you do next? You'll likely stick with the machine that worked. But maybe that's a trap. Perhaps right next to it stands a machine that would bring you double the winnings, but you will never try it.

This analogy perfectly captures the behavior of many B2B salespeople. In practice, they often stick with one proven tactic that "worked": telling a worn-out joke, making small talk about the weather, wearing an expensive Boss suit, or a revealing blouse. Since it worked once, why try anything else? But by doing so, they close the door to new, often more effective options.

2. Multi-Armed Bandit AI tactics

This is exactly where our approach at Omnicrane and the multi-armed bandit algorithm comes in.

At Omnicrane, we use principles from machine learning - specifically the multi-armed bandit algorithms known from reinforcement learning. This algorithm allows us to continuously balance two key activities: exploration (testing new options) and exploitation (using what has proven effective).

Our platform works as a smart recommender of a wide range of sales tactics and next best sales actions (NBA), constantly processing anonymized data about what works across multiple users, customer segments, and channels. The result is recommendations such as:

• "For this customer and this product, don't call right away, but invite them via SMS for coffee - this has a high chance of conversion."

• "Then send a WhatsApp message with a link to more product information - this works great with similar customers."

• "After that, send the offer by email and request internal discussion."

• "Invite the client for lunch to assess if you have a chance to win or just strengthen the relationship."

• "Ask for a referral to help secure another meeting."

Image 2: Exploration and Exploitation (Created by AI)

3. What benefits this approach brings to salespeople

• Expanding the repertoire: Salespeople gain inspiration for new approaches they might not have tried on their own.

• Customer context and creativity: The same tactic can be applied to different customers, and different tactics can be used for the same customer depending on data context.

• Time savings: Instead of thinking about how to break stereotypes, you get specific recommendations based on big data insights.

• Revenue increase: Better tactics mean higher conversions and thus higher revenues.

• Augmentation, not automation: AI does not replace the person - it supports their decision-making and creates a synergy between data and human judgment, not manipulation or random casino play.

4. Beyond Personalization and GenAI

Personalization in B2B sales long revolved around simple email tweaks or customer segmentation by company size. The rise of AI, especially large language models (LLMs), brought new impulses - but also new limitations.

Generative models like GPT-4, Claude, or Gemini can generate content, summarize information, or create communication scenarios based on input data. But from the sales team's perspective, what is often missing is the ability to decide what next step to take. Without deeper business context, these models cannot distinguish whether to contact the client, propose an upsell, or let the client "mature."

This is where systematic personalization through Next Best Action (NBA) comes in. NBA combines data sources - from CRM, through transactional and product data (PIM), pricing policies, to current customer interactions - and recommends specific actions for each situation.

According to a May 2025 McKinsey analysis, NBA strategies have been implemented by over 40% of large B2B organizations in technology, finance, and telecom. Key reasons for adoption include increased conversion rates, shortened sales cycles, and more efficient sales team utilization.

This is exactly the principle we build on at OmniCrane - combining generative AI, robust product data, and decision algorithms that provide sales teams with practical recommendations for next steps. The salesperson doesn't just interpret data but receives specific advice on who to approach, with what offer, and at what time to maximize the chance of success.

NBA systems are not mere CRM add-ons. Their efficiency lies in data orchestration and priority management. Generative AI can generate proposals, emails, or presentations, but most importantly, the system gives clear recommendations on why and who to focus on now.

Thus, personalization in B2B sales shifts from simple content customization to orchestrated sales decision-making, where AI not only writes but helps to decide.

Image 3: Sales Orchestration (Created by AI)

5. Conclusion: AI is not just GenAI

While the world talks about generative AI, at OmniCrane we go further. We combine methods - from reinforcement learning to behavioral models - to address real challenges in B2B sales. The result is not just a smart tool but a sales partner that helps people grow, learn, and win - even beyond the casino.

About the author:

Richard A. Novák is an expert in ethical AI, digitalization and IT management. He graduated from the Czech Technical University in Prague and received his Ph.D. in Big Data Ethics from the Faculty of Informatics and Statistics at the University of Economics in Prague. He founded the Prague Data Ethics Lab with his colleagues and teaches courses related to Ethical AI and IT Governance at the VŠE. He founded and currently serves as CEO of Omnicrane, a startup focused on applying AI to SalesTech and MarTech. Previously, he held the position of Vice President at telecommunications companies T-Mobile Czech Republic, GTS Czech and Director of IT Services at Slovak Telekom.

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