How Is VAIS Calculated? Inside the Logic Behind the Score

Traditional lead scoring has always had a blind spot.

It evaluates accounts the way a recruiter skims a resume, quickly filtering by industry, company size, or revenue bracket. On paper, it looks like a system. But when the sales call happens and the conversion doesn’t, the system reveals its real flaw: it was never measuring the right things.

Just like a good resume doesn’t guarantee performance, a firmographic match doesn’t guarantee sales.

That’s the gap Valasys AI Score or VAIS was built to close.

Instead of relying on static attributes, VAIS evaluates accounts the way you would assess a candidate through a live simulation with the one where you’re observing real-world signals, market conditions, and contextual fit before making a call. It is, at its core, an alignment score. It answers one question with data that most scoring models never even think to ask: How well does your product fit this account, given everything happening in the market right now?

The workflow on which VAIS is built explains this perfectly. At the center sits a single unified score. Surrounding it are nine independent parameters, each one a different lens through which the market is evaluated. They don’t operate in sequence. They don’t cancel each other out. Together, they build a picture that no single data point could ever paint alone.

Here is what each of those nine signals actually measures and why it matters.

Demand of the Product: Does the Market Even Want This?

Every evaluation begins here, because without demand, alignment is meaningless.

Before asking whether an account is a good fit for a product, VAIS first asks whether the market is actively engaging with that product category at all. This signal is constructed from product reviews on platforms like G2, sentiment analysis across those reviews, and broader adoption trends observed through market surveys and historical data.

If buyers are actively evaluating, reviewing, and adopting a product, that’s traction. If the sentiment around it is positive and growing, that’s validation. When both are present, the scoring model knows it’s working with a product that has real pull and accounts within its reach are more likely to be receptive.

Low demand, on the other hand, doesn’t necessarily mean a bad product. But it does mean longer cycles, harder conversations, and lower probability of conversion, all of which VAIS accounts for before a single sales rep picks up the phone.

Product Market Share, Investments & Funding: Is There Momentum Behind It?

Demand tells you where the market is today. Market share and funding tell you where the product is heading.

VAIS evaluates the product’s current position in its category, how much of the addressable market it holds, whether it is gaining or losing ground, and what the investment activity around it signals about growth confidence. A product that is attracting funding, expanding market share, and sitting within a category that institutional analysts and investors are backing carries a fundamentally different weight than one that is plateauing.

This momentum matters because it shapes the account’s decision-making environment. Accounts aligned with a growing product are more likely to see long-term value in adopting it and more likely to act with urgency. The scoring model treats momentum not as a vanity metric, but as a genuine predictor of opportunity strength.

Best Fit Company Size & Revenue: Does the Account Actually Match the Profile?

A product designed for mid-market operations does not belong in front of a ten-person startup. A platform built for enterprise-scale complexity may be overkill and overpriced for a regional SMB. VAIS encodes this reality directly.

Using historical data from the Valasys database, past customer interaction records, and structured questionnaire data, this parameter evaluates whether an account’s size and revenue bracket match the profile of companies where the product has historically resonated, onboarded successfully, and delivered measurable ROI.

When firmographic alignment is strong, the structural conditions for adoption already exist. The product fits the organization’s scale, budget range, and operational complexity. When it’s weak, even genuine interest from a prospect may not survive the internal evaluation process. VAIS weighs this accordingly.

Competition of the Product: How Hard Is the Battlefield?

Fit is only half the conversation. The other half is context specifically, how crowded the space is and how difficult it will be to win an account that has alternatives.

This parameter draws from market research, competitive analysis, and survey data from product owners and industry influencers to evaluate the saturation level of the product’s category. A highly competitive market isn’t necessarily a dealbreaker, it often signals strong demand. But it does mean that conversion requires sharper differentiation and more strategic outreach.

VAIS factors in competitive intensity so that accounts in oversaturated categories are scored with appropriate realism, while accounts in categories where the product has a meaningful competitive edge are surfaced with higher priority. It evaluates the battlefield, not just the account.

Product Brand Value: Is There Trust in the Room?

In B2B, trust is a currency. And brand value is how much of it a product has already earned.

VAIS measures brand strength through a combination of social proof signals, product website presence, third-party review platform analysis, and market perception indicators. The logic is straightforward: a product with strong brand recognition faces fewer objections at the awareness stage, moves through committee-driven purchase decisions with less friction, and benefits from the compounding effect of peer recommendation.

A weak or largely unknown brand doesn’t disqualify a product but it does add resistance. VAIS treats brand value as a real variable in the probability of conversion, because in practice, it is.

Industry Specific Rules: Can the Product Even Operate Here?

Not every product can enter every industry. Some sectors are heavily regulated. Others have operational constraints, compliance requirements, or structural limitations that determine whether a product is viable before a single conversation even begins.

VAIS captures these realities through the industry-specific rules parameter, which draws on product usage data, retention patterns, and documented industry compliance considerations. Rather than scoring an account highly and leaving discovery of a fundamental mismatch to the sales team, VAIS filters for viability early.

In some cases, this parameter doesn’t lower a score, it eliminates the account from consideration entirely. That’s not a limitation of the model. That’s the model doing its job.

Product & Industry Relevance: Does This Actually Make Sense?

This is the most foundational signal in the entire model.

Relevance asks whether the product genuinely solves a real problem for the industry of the account being evaluated. Not whether it could theoretically be applied. Not whether a creative sales pitch could make the connection. But whether, at a fundamental level, this product belongs in this industry’s conversation.

The scoring relies on industry trend data, use-case alignment research, and the accumulated intelligence from Valasys Media’s decade of product and market research, spanning over 50,000 reviewed products across 293 sub-categories. High relevance means the product fits naturally into the account’s existing workflow and challenges. Low relevance means the alignment is forced, and no amount of intent or outreach will compensate for a solution looking for a problem it wasn’t built to solve.

Revenue Potential: Is This Opportunity Worth Pursuing?

Not all aligned accounts deliver equal value. VAIS doesn’t just optimize for probability of conversion, it optimizes for the quality of what’s being converted.

Revenue potential is evaluated through feedback forms, historical deal data, and internal benchmarks that estimate the likely deal size and long-term account value given the product-account pairing. An account that is easy to convert but represents minimal revenue should not occupy the same priority position as one that is slightly harder to win but represents significant pipeline value.

This parameter brings strategic prioritization into the model, ensuring that the VAIS score reflects not just who can be closed, but who is worth closing.

Success Stories: Has This Worked Before?

Past patterns are the closest thing to certainty that any scoring model can offer. VAIS leans into this through its success stories parameter, which evaluates whether the product has already delivered documented results in accounts that resemble the one being evaluated.

This is predicted on the basis of case studies, third-party research reports from institutions like Gartner and McKinsey, and Valasys’s own historical data on product performance across verticals. When a clear pattern of success exists in accounts that match the current target’s profile, the scoring model gains confidence. When no comparable success story exists, the uncertainty is reflected in the score.

It answers the question no one wants to leave unanswered going into a sales conversation: has this worked before?

How These Nine Signals Become One Score

Each of these nine parameters is researched and validated using a combination of web scraping, structured surveys, questionnaire-based interviews with industry influencers and product owners, external market research, and over a decade of accumulated historical data from the Valasys database.

They are not evaluated in a sequence. They are evaluated in parallel, each contributing its own dimension of intelligence to the final calculation. The predictive analytics model at the core of VAIS synthesizes these signals, weighs them against each other based on the product category and market context, and outputs a single, unified alignment score.

The result is not a guess. It is a calculated representation of how well your product fits a specific account, grounded in real market conditions, not assumptions, not gut feel, and not yesterday’s CRM data.

The Layer That Changes Everything: VAIS Meets Intent

A strong VAIS score tells you who should buy. But it doesn’t tell you who is ready to buy right now.

That distinction is everything in B2B.

VAIS measures fit. Intent measures timing. And even the best candidate won’t join if they aren’t actively looking.

This is why Valasys AI Score  layers a second intelligence system in association with Bombora on top of the score, an Intent Sentiment Analyzer powered by Natural Language Processing that monitors over 5,000 B2B websites, tracks 16,000+ intent topics, and processes 16.2 billion events monthly to generate surge scores for 4 million domains every week.

When these two layers are combined, a matrix of action emerges that transforms scoring into decision-making.

• High VAIS paired with high intent means you call now, the account is aligned and actively researching. 
• High VAIS with medium intent means targeted outreach,  the fit is there, the trigger hasn’t happened yet. 
• High intent without VAIS alignment means qualifying further before committing resources. Low on both means monitor, not pursue.

This dual-layered system is what separates VAIS from every other scoring model in the market. It doesn’t just tell you who to target. It tells you who to target, when to move, and how urgently.

What This Means for B2B Teams

When scoring becomes this precise, prioritization becomes fundamentally different.

Sales teams stop chasing accounts that look good on a spreadsheet but have no structural reason to convert. Marketing teams build campaigns around accounts where the product genuinely belongs, not accounts that happen to fall within a demographic filter. ABM strategies become sharper, because they are built on alignment backed by data, not on intuition backed by hope.

Since its launch, VAIS has helped enterprise teams achieve a 40% increase in first-touch conversions and 3x ABM campaign engagement, with enterprises reporting a 50% lift in click-throughs and a 35% improvement in lead-to-opportunity conversions with VAIS enabled targeting.

Those numbers don’t come from better salespeople. They come from a smarter system telling the right people to go after the right accounts at the right moment.

The Bottom Line (And It’s a Good One)

The best salespeople in the world still can’t know what they don’t know. They can’t see which accounts are actively researching your category at 11pm on a Tuesday. They can’t weigh a decade of market signals in their heads before picking up the phone.

But VAIS can.

It’s not replacing your sales team’s instincts, it’s giving those instincts something real to work with. A foundation of data, precision, and clarity that turns “who should we call?” from a debate into a decision.

The score is in. Now it’s your move. Click here: B2B Sales Intelligence Tool | Valasys AI Score (VAIS)

Mansi Hake