Emanuel Martonca

Soft Fight

🖥️ We have build a pricing optimisation app based on our proprietary methodology > JUST Value Framework.

📚 TRAINING and WORKSHOPS
> Choose the right pricing model
> First principles of pricing for tech services
> Value selling process
> How to raise prices for existing clients

Founder. Trainer. Consultant. Fractional Pricing Manager.

Ontario Die International

Business Development and Strategy [Fractional]

IntelligentBee

AI-enabled Human-first Customer Care solutions aimed for business growth.

Director, Revenue and GTM Strategy [Fractional]

Manu's Elastic Graphite Newsletter

Economic uncertainty, flexible workforces, AI threatening to fundamentally change software development. The IT & software services industry is in turmoil. Alternative pricing models are needed.

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#Improve #TechServices #Pricing

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Writer

Thagora

Entire industries and manufacturers are quickly realising the challenges and opportunities they face in the transition to “Industry 4.0”.

Smart, connected equipment and software, tools that are tailored to individual industries and the use of algorithms and data to drive efficiency are already a reality for many industrial applications.

Thagora is a sophisticated software and hardware solution for the Leather Upholstery Industry.

World-class companies in 
- High-End Furniture
- Automotive and Aerospace
are using Thagora customised implementations in their Leather Cutting Operations.

Sales Manager

Gemini CAD Systems - a LECTRA company

Thagora Product Manager

Thinslices

Team and Product Management. Sales. Marketing. 

Coriolan

Strategy and market research. Managing the re-branding process.
Redesign of the sales process, creating a positive experience for the clients.
Organizing the marketing and sales activities, with an emphasis on process and automation.
Developing and implementing an e-commerce sales channel.

Sales and Marketing Manager

Dexia Bank Belgium

Responsible for the organization-wide implementation of a new customer experience central competence, aimed at improving the level of service delivered to our clients.

Senior Customer Experience Expert

Project leader for the launch of a new payments offer for retail clients: responsible for designing the strategic concept, calculating a business case, describing the detailed scope for the operational implementation. Delivered presentations of the project for validation and approval to the different departments of the organization and executive management. 
Responsible for the day-to-day product management of current accounts.
Main achievements:
      Reached a 15% increase of total yearly revenues, in the context of a mature and stable market.
      Designed a new financial report for the current accounts products, which allows for a better estimation of future volumes and impact on P&L.

Product Manager Payments Systems

Followed trainings on all relevant subjects related to the functioning of a financial institution.
Participated in a team exercise having as objective the outlining of a strategic and action plan for Dexia in Romania, following a hypothetical acquisition of C.E.C. by Dexia Group. Worked mainly on the marketing strategy and a new distribution model and have proved to be a valuable member of the team.

International Management Trainee

Compiled the 'Banking in Romania' report, a comprehensive study of the banking market in Romania in 2005, based on publicly available data. The three main subjects developed in the report were: the retail banking customer, regional development and banking industry.

Market Research

Petrom SA Romania

Filling Station Manager

The IT & software services industry is in turmoil, with 3 powerful macro forces affecting it:
> Economic uncertainty has led to much longer sales cycles
> Hybrid work and flexible workforces are changing the cost structure, creating operational challenges for delivery teams
> AI is threatening to change the very essence of what it means to do software development.

In this environment, hourly billing, cost-based pricing and taking 2 weeks and multiple video calls to create a proposal doesn't cut it anymore.

Since 2012 I’ve been involved in more than 350 negotiations for software services and technology, for both camps: buyers and sellers.

Everything I write and talk about comes from this experience.

Founder, Pricing expert

Soft Fight is the single source of truth for your sales strategies and pricing.
A way to minimise decision making noise and biases in your price calculation process.
We work with software services companies to change mindsets, implement scalable, efficient methods and tools to manage the pricing and sales process.

Suntem tot timpul cu 5 pași în urmă.
Industria IT românească crede că salvarea e să facem produse proprii. Vorbim despre asta de 15 ani.

Dar între timp, cei care mută piețe se uită în altă parte:
“The global engineering services outsourcing (ESO) market was valued around USD 1.67 trillion in 2024 and is projected to reach approximately USD 6.34 trillion by 2033, growing at a compound annual growth rate (CAGR) of about 15.18% from 2025 to 2033. This market growth is driven by the demand for cost optimization, access to global specialized talent, accelerated product development cycles, and the adoption of digital engineering technologies across industries such as automotive, aerospace, and telecommunications.”

Deci unde e miza?
Cu siguranta nu în a mai scoate încă un SaaS care să concureze cu Atlassian sau Hubspot.
Ci în servicii.

AI schimbă dinamica:
> clientul nu mai vrea doar acces la software, vrea outcomes
> outcomes înseamnă tehnologie + servicii de implementare, integrare, customizare
> iar aici companiile de servicii au avantajul: apropiere de client, echipe flexibile, capacitate de a lega tehnologia de realitatea din business.

Outsourcing vs. produse proprii e o falsă alegere.

Adevărata întrebare e:
Cine livrează mai bine outcomes într-o piață de trilioane?

Transforming pricing for IT & software services with Agentic AI

The SaaS playbook does not work for AI.
It’s How to Web week and today I’m trying to convince founders and investors that pricing just got a lot more complicated.

We’ve spent two decades telling ourselves that software scales beautifully. Build it once, sell it forever. Every new user is pure margin.

AI flips that equation.

In SaaS, infrastructure cost becomes negligible as you scale. In AI, it becomes the cost. Every request burns tokens. Every interaction consumes GPU cycles. A single user query can cost what serving 10,000 traditional SaaS users costs.

This is why copying SaaS pricing models is a trap. SaaS charges for access. AI needs to charge for work, because that’s where both the cost and the value actually live: in what the system does, not just in giving you a login.

But there’s more.

Traditional software creates leverage through code. AI creates leverage through intelligence. The moat isn’t features anymore, it’s model performance, data quality, and domain-specific fine-tuning. A competitor can replicate your interface in weeks. They can’t replicate your trained model, your proprietary data, or the context you’ve built.

The winners won’t be the companies with the best UI. They’ll be the ones who figure out the unit economics first. The ones who understand that AI isn’t a feature, but a business model shift. The ones who price for outcomes, not seats.

AI looks like software. But it behaves like infrastructure.
And infrastructure has always played by different rules.

Most founders spend more hours choosing the logo color than setting the price.

I’ve sat through six-hours branding debates.
I’ve seen 70-page decks on the meaning of colors.
I’ve watched teams agonize for weeks over design choices.

And pricing?
“Let’s just undercut competitors.”
“Three packages feels right.”
“We’ll figure it out later.”

You can fill entire buildings with books on design, art, visual perception, and only a few shelves with books on pricing.
Not because pricing isn’t important. Because it’s harder.

But the math is simple:
Logos win recognition.
Pricing decides survival.

Your brand won’t matter if you don't make money.
The market doesn’t care how pretty your website is if your pricing is broken.

Everyone at How to Web wants to talk about AI. 
Nobody wants to admit how hard it is to price it right.

You can’t just pick a metric and call Stripe. AI pricing isn’t a spreadsheet exercise, it’s a strategic decision that determines who adopts your product, how they use it, and whether you survive long enough to find product–market fit.

When your product learns, talks, plans, or acts autonomously, traditional pricing breaks down. What used to be 3–4 standard SaaS models has fractured into dozens of hybrids, proxies, and creative attempts to capture value.

Here’s what the landscape actually looks like:

1. Agent-based pricing
Per-agent monthly subscription
Digital FTE replacement pricing
Agent capacity tiers: basic, pro, enterprise
Per-agent with included quota
Fixed fee per agent
Fee per agent action
Agent licensing fee

2. Credit systems
Prepaid credit buckets
Workflow credits
Task or automation credits
Platform credits
GenAI credits
Video generation credits
Feature or lead credits
Consumption credits

3. Usage-based pricing
Per-conversation: chat or call
Per-hour: runtime, agent thinking time
Per-token processed
Per-input/output token
Per-query: search
Per-file or character: translated
Per-minute: of video or processing
Per-day: high watermark usage
Compute unit pricing

4. Outcome-based pricing
Per-resolution completed
Per-task completed or automated
Per-work product delivered
Per-photo edited or retouched
Success-based percentage fee
Performance guarantees
Per-demand package generated
Hybrid: base plus outcome bonus

If this feels overwhelming, that’s because it is.

Each of these models shapes behavior. Some encourage exploration. Others create anxiety. Some align with value delivery. Others introduce perverse incentives where your best users become your most cautious ones.

The wrong pricing model won’t just hurt your margins. It will train users to avoid your product’s most powerful features. They’ll ration intelligence like it’s a scarce resource, even when abundance is the whole point.

SaaS taught us to optimize for seats and retention, but AI requires us to optimize for value delivery and trust.

The companies that figure this out first won’t just have better unit economics.
They’ll have users who actually use what they’re paying for.

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