reduced sales effort by 60–70% by architecting a global GTM

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AVEK developed and commercialized NORMEL, a voltage normalization technology designed for facilities operating under unstable or excessive voltage conditions in low-voltage grids. The product delivered value across three pillars: equipment protection, extended asset life, and reduced energy consumption.

At the start of commercial scaling, the venture was effectively a startup: it had an engineering base, patents, and a functional product, but lacked a scalable commercial framework. My task was to turn a complex engineering product into a repeatable international business model.

I architected and deployed an expert GTM system that integrated an international representative network, a proprietary CRM/DMS platform, a shared knowledge base, and predictive analytics for more accurate market entry.

The system supported the deployment of more than 5,000 devices across numerous projects, the development of a 60+ partner network, and expansion across the CIS, Europe, Southeast Asia, and North America.

The market required a highly targeted approach to client engagement. Commercially, the product relied on three primary value drivers:

• protection of equipment and technological processes; 
• asset life extension through more stable power supply; 
• energy savings through the reduction of excessive voltage. 

Most projects involved a combination of these drivers, but their relative weight varied significantly. In some cases, protection was the dominant argument. In others, the entry point was energy savings or lower depreciation. This required a precise, site-specific commercial narrative rather than a uniform pitch.

The primary barrier was the difficulty of scaling sales for a technically complex product.

Remote selling was highly ineffective because it required deep analysis of the client’s local grid, load structure, and industrial processes. In parallel, on-site engineers often approached the solution with skepticism because they did not immediately understand the physical mechanism behind the effect and found the claimed result difficult to reconcile with the device’s compact design.

Market heterogeneity added another layer of complexity. Different tariff models, infrastructure conditions, and industrial densities meant that a universal narrative converted poorly. There were other stabilization-class solutions on the market, but they did not address the same combination of client problems and did not offer the same commercial logic of implementation. The system therefore had to preserve engineering credibility, accelerate presales, and convert local expertise into a shared commercial asset.

I served as the architect of the entire commercial ecosystem, coordinating the resources required for its design and launch.

My contribution included:

• designing the GTM model and partner selection logic; 
• architecting the CRM/DMS platform’s operating logic; 
• establishing interaction rules between representatives and the manufacturer; 
• developing the knowledge transfer model; 
• enforcing territory management and channel conflict resolution; 
• implementing predictive analytics to improve market entry accuracy. 

We built an expert-led distributed network. The core principle was to build the model around technical specialists rather than generalist sales agents. We recruited electrical engineers, integrators, automation experts, and other adjacent specialists who already understood the pain points of unstable power supply and could speak the client’s professional language.

This approach created three immediate advantages:

• it lowered the trust barrier; 
• it shortened onboarding time; 
• it improved the quality of initial site qualification. 

1. Expert Representative Network

The network was built around technically relevant partners already active in segments where power quality was a critical issue. This resulted in a network of 60+ representatives across multiple regions.

2. Proprietary CRM / DMS as the Management Center

To align the network, we developed a custom platform optimized for performance, internal coordination, and data protection. This CRM served as the operational hub for:

• Data Exchange:     centralizing orders, technical site data, and analytical requests; 
• Presales Analysis:     allowing partners to validate solution applicability with the central team  before issuing quotes; 
• Knowledge Base:     accumulating cases, standard solutions, and technical rebuttals; 
• Collaboration:     enabling partners with different specializations to co-manage complex projects; 
• Channel Conflict Resolution: enforcing territory management to prevent internal competition and preserve trust; 
• Coordination:     aligning marketing and exhibition activities to prevent regional duplication; 
• Analytics:     tracking partner activity, demand patterns, and weak zones in coverage. 

3. Knowledge as a Commercial Asset

For NORMEL, technical understanding was the primary driver of trust. Once a client understood the physics of the solution, resistance decreased sharply. By making this knowledge scalable through documentation and case studies, we reduced dependence on individual sales experience and improved the quality of client meetings across the network.

4. Predictive GTM Layer

Using CRM data and external sources, we built an analytical model in R and Python to transfer success patterns between regions. If a specific industrial profile or tariff model proved successful in one city, we could identify similar demand patterns in comparable cities. The model incorporated geotagged enterprise databases, grid infrastructure, generation structures, and load profiles. This allowed us to move from reactive selling to proactive, precision targeting.

• Revenue Growth:     sustained at 15–20% annually, with step-growth periods driven by      large-scale projects; 
• Deal Size:     typical deals ranged from $80k–$100k, with major projects exceeding $500k;      
• Funnel Efficiency: funnel      throughput and conversion roughly doubled after the system and knowledge      base were implemented; 
• Sales Effort:     reduced by 60–70% due to streamlined presales, shared technical knowledge,      and faster expert validation; 
• Onboarding:     partner time-to-first-sale was reduced to 1–1.5 months; 
• Scale:     supported the deployment of 5,000+ units across numerous projects and      expanded the footprint across the CIS, Europe, Southeast Asia, and North America. 

We built a repeatable scaling mechanism for a complex industrial deep-tech product. The system shifted the business away from dependence on centralized expertise and toward a managed distributed ecosystem where:

• expertise is distributed and knowledge is a shared asset; 
• market entry and lead quality are more predictable; 
• channel conflict is minimized; 
• engineering credibility is maintained at scale.