ValueTempo

Find the Buyer FrictionSlowing Your Growth

AVS Rubric measures buyability across 8 buyer-confidence dimensions.

Free · 3 analyses per week · ~1 minute
 

Where buyability breaks down

AI Vibe Coding Tools

79%

Avg Score

Top buyer friction: Cost Driver

Buyers struggle to predict how usage translates to cost.

Usage spikes often lead to unexpected bills, causing frustration and churn.

AI Dev Infrastructure

75%

Avg Score

Top buyer friction: Cost Drivers · Spend Controls

Cost drivers are not clearly mapped to product behavior, making spend hard to forecast.

Weak safety rails leave teams without caps or alerts, increasing risk of unexpected bills.

AI-Native CRM

63%

Avg Score

Top buyer friction: Value Units · Cost Drivers · Risk Controls

Core usage units and cost drivers are unclear, making it difficult to understand how workflows translate to cost.

Limited overage policies and missing controls reduce trust as usage grows.

GTM Platforms

60%

Avg Score

Top buyer friction: Cost Drivers · Overages · Safety Rails

Workflow-level pricing is not clearly defined, making spend unpredictable.

Overage behavior and safety controls are often unclear, increasing risk and reducing buyer confidence.

AI Agents & Automation

68%

Avg Score

Top buyer friction: Value Units · Cost Drivers

Agent behavior is hard to map to cost, making it difficult to predict how workflows scale economically.

This creates hesitation for teams deploying agents into production.

AI Media & Generation Tools

72%

Avg Score

Top buyer friction: Output Predictability · Cost Drivers

Output quality and cost per result are inconsistent, making outcomes hard to predict.

This reduces confidence for repeatable production workflows.

AI Vibe Coding Tools

79%

Avg Score

Top buyer friction: Cost Driver

Buyers struggle to predict how usage translates to cost.

Usage spikes often lead to unexpected bills, causing frustration and churn.

AI Dev Infrastructure

75%

Avg Score

Top buyer friction: Cost Drivers · Spend Controls

Cost drivers are not clearly mapped to product behavior, making spend hard to forecast.

Weak safety rails leave teams without caps or alerts, increasing risk of unexpected bills.

AI-Native CRM

63%

Avg Score

Top buyer friction: Value Units · Cost Drivers · Risk Controls

Core usage units and cost drivers are unclear, making it difficult to understand how workflows translate to cost.

Limited overage policies and missing controls reduce trust as usage grows.

GTM Platforms

60%

Avg Score

Top buyer friction: Cost Drivers · Overages · Safety Rails

Workflow-level pricing is not clearly defined, making spend unpredictable.

Overage behavior and safety controls are often unclear, increasing risk and reducing buyer confidence.

AI Agents & Automation

68%

Avg Score

Top buyer friction: Value Units · Cost Drivers

Agent behavior is hard to map to cost, making it difficult to predict how workflows scale economically.

This creates hesitation for teams deploying agents into production.

AI Media & Generation Tools

72%

Avg Score

Top buyer friction: Output Predictability · Cost Drivers

Output quality and cost per result are inconsistent, making outcomes hard to predict.

This reduces confidence for repeatable production workflows.

What the analysis evaluates

Your buyability score is what a buyer or AI agent can verify before engaging sales.

Product Clarity

Can buyers understand what your product does, who it is for, and what outcome it helps them achieve?

Cost Predictability

Can buyers see what drives usage, how cost scales, and how to avoid budget surprises?

Operational Trust

Can buyers verify the controls, limits, safety rails, and governance needed to deploy with confidence?

Decision Readiness

Can champions justify the purchase to finance, security, procurement, and leadership?

Example: Where Buyer Confidence Breaks

See how the analysis separates visible gaps from issues that may slow
evaluation, approval, or expansion.

Example: Deepgram

Overall score & band

Deepgram
Exemplary

Strong trust infrastructure — minor gaps remain in cost driver detail

13/ 16
81%
Buyability
Score

Strengths & weaknesses

Analysis Summary

↗
Top Strengths
Value unit clarity
Primary value units clearly defined: minutes for STT/voice agents, characters for TTS, with true per-second billing.
Enables: Buyers can forecast cost with precision before committing.
↘
Top Weaknesses
Cost driver mapping
Per-unit pricing is clear, but detailed driver formulas and forecasting surfaces beyond general pricing are not fully documented.
Impact: Harder to model total spend for complex multi-model deployments.

Trust breakpoints

⚠
Trust BreakpointsWhere deals stall silently
Multi-Model Cost Complexity
Combining STT, TTS, and Audio Intelligence with different billing units makes total cost forecasting harder.
Safety Rails Visibility
Budget caps and usage alerts exist but their configuration and trigger conditions are not fully documented publicly.

Dimension scores

Dimension Scores

01Product north star
High2/2
02ICP and job clarity
High2/2
03Buyer and budget alignment
High2/2
04Value unit
High2/2
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Scored across 8 buyer-confidence dimensions

The rubric maps buyer-facing friction across product clarity, pricing architecture, operational controls, and buying readiness.

Product North StarICP & Job ClarityBuyer & Budget AlignmentValue UnitCost Driver MappingPools & PackagingOverages & Risk AllocationSafety Rails & Trust Surfaces
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Frequently Asked Questions

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