Invisible Hand Technologies

Invisible Hand Technologies is a web platform for consumer brands and CPG manufacturers that need store-level guidance on pricing, promotions, availability, and competition. It suits teams managing decisions across multiple retailers and local markets, while smaller businesses looking for a self-serve repricing tool will find the sales-led buying process less convenient. The central advantage is a connected view of causes and likely outcomes rather than isolated price reports.

Overview

The platform combines store-by-store price, promotion, and availability data collected up to daily with internal, market, and third-party data. Its machine-learning engine models volume, price, and elasticity for each local market, then simulates possible outcomes before a user acts. That local modeling can make recommendations more relevant than a single national assumption, particularly when retailer conditions differ materially.

Invisible Hand links changes in sales, margin, or share to price, promotion, distribution, availability, and competition, with analysis down to individual stores. Recommendations are delivered in dashboards and real-time alerts, while an AI data assistant answers what is happening, why it is happening, and what to do next. Users can inspect the data behind an answer and challenge the recommendation, keeping commercial judgment with the team.

Key features

Price and promotion optimization

Price optimization works at SKU, retailer, and market level and uses elasticity analysis to suggest price moves intended to create value for both brand and retailer. Promotion analysis separates incremental sales from subsidized volume, making it useful for deciding whether a discount creates demand or simply gives away margin. This is a better fit for CPG organizations balancing retailer relationships than for merchants wanting a basic automated repricer.

Root-cause and competitive analysis

When performance changes, the root-cause analysis traces the effect to factors such as distribution, availability, competition, price, or promotion. Store-level diagnosis can turn a broad share decline into a more actionable investigation. Competitive intelligence supplies real-time views of rivals’ pricing and promotion trends across a category, supporting continuous rather than occasional monitoring.

Availability and AI guidance

Out-of-stock visibility spans retailers carrying a customer’s products, helping teams distinguish lost demand from weak pricing or promotion. The AI assistant puts the same customer data and optimization models into plain-language questions, while inspectable reasoning provides a check against accepting an unexplained recommendation.

Pricing

Invisible Hand uses paid, custom pricing. The company’s homepage and product page direct prospective customers to schedule a demo, and no subscription prices, plan tiers, free plan, or trial terms are published. Buyers therefore need a sales conversation to establish cost, scope, and commercial fit. That approach may suit enterprise CPG teams needing a tailored deployment, but it offers no low-cost way for a small team to evaluate the product independently.

Platforms

Invisible Hand is delivered through the web. The web format suits distributed brand and revenue-management teams, although the supplied platform coverage does not include a native mobile or desktop application.

Who it's for

This is aimed at consumer brands and CPG manufacturers making pricing, promotion, distribution, and availability decisions across retailers. It is particularly well matched to organizations with enough store-level data to benefit from local elasticity modeling, simulations, competitor monitoring, and continuous alerts. A business that only needs a handful of product prices checked or a simple rule-based repricing workflow should look for a more transparent, self-serve alternative.

Pros and cons

• Pros: SKU-, retailer-, and market-level price recommendations; promotion analysis that distinguishes incremental sales from subsidized volume; root-cause analysis down to individual stores; real-time competitor pricing and promotion insight; retailer-wide out-of-stock visibility; inspectable and challengeable AI recommendations.
• Cons: Custom pricing means there is no published cost for budgeting or comparison; no free plan or trial terms are stated; the sales-demo process may be excessive for smaller teams; web is the only stated platform.

Alternatives

DynamicPricing.ai is the better starting point when a team wants a freemium web product with a free tier covering one price test, one pricing rule, and up to 50 products per rule, plus unlimited monthly orders; its Starter plan is $75 a month for up to 500 orders.

Pricefy fits teams seeking a free or trial-based API and web tool for up to 50 SKUs, five competitors, daily price updates, AI Automatch, competitor discovery, and one feed channel.

Retailgrid is preferable when a freemium API and web workflow with manual imports and seven-day retention is sufficient; its Freemium plan allows up to 500 grid rows, while Starter costs €349 a month.

NIQ is a paid alternative available on Android, iOS, Windows, web, and API.

Peak is a paid API and web option with an Essentials tier that includes five data feeds, two small workspaces, ten workflows, 500 API calls per day per API, one deployed API, one Peak application, one power user, and ten commercial users.

RELEX Demand Planning is a paid web alternative focused on demand planning.

7Learnings is a paid API and web alternative priced through a demo request.

Oracle Retail Assortment Planning Cloud Service is a paid web alternative.

Verdict

Choose Invisible Hand if you are a consumer brand or CPG manufacturer that needs continuous, local-market pricing and promotion recommendations tied to store-level causes, competitor movement, and out-of-stocks. Its strongest differentiator is the combination of simulation, diagnostics, and inspectable AI guidance. Look elsewhere if transparent pricing, a free evaluation, or a lightweight self-serve repricing workflow is more important than enterprise-oriented analysis.