FutureSearch vs StoreRadar: Which is Better in 2026?
A comprehensive comparison of FutureSearch and StoreRadar covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose FutureSearch if:
- →You want a free tier to get started without commitment
- →You want more affordable paid plans (from $20/mo)
- →You need a broader feature set (6 features vs 5)
- →You need six question shapes including conditional and decision forecasts or ranked #1 of 197 bots on the metaculus futureeval live tournament
Choose StoreRadar if:
- →You need 2.6m shopify stores, 1.9m emails, 200k phones in one csv or 68 columns including apps, theme, tech stack and ad pixels
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FutureSearch vs StoreRadar: At a Glance
Pricing Comparison: FutureSearch vs StoreRadar
Understanding the pricing differences between FutureSearch and StoreRadar is crucial for making the right choice. Here's how their plans compare side by side.
FutureSearch Pricing
StoreRadar Pricing
💡 Pricing takeaway: FutureSearch has an edge with a free tier, letting you start without commitment. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from FutureSearch and StoreRadar stacks up.
What Makes Each Tool Unique
🔵 Unique to FutureSearch
Features available in FutureSearch but not in StoreRadar:
- ✓Six question shapes including conditional and decision forecasts
- ✓Ranked #1 of 197 bots on the Metaculus FutureEval live tournament
- ✓Live real-money positions on Kalshi, Polymarket and the S&P 500, published with losses
- ✓Multi-agent runs and research teams for batch forecasting
- ✓API access on every tier, including free
- ✓Credit that does not expire monthly like a plan allowance
🟣 Unique to StoreRadar
Features available in StoreRadar but not in FutureSearch:
- ✓2.6M Shopify stores, 1.9M emails, 200K phones in one CSV
- ✓68 columns including apps, theme, tech stack and ad pixels
- ✓Itemised 0–100 lead score and separate SEO score per store
- ✓Optional three-pass email verification with confidence scores
- ✓One-time purchase; the file is yours to keep
Use Case Recommendations
Best for: FutureSearch
FutureSearch is a forecasting engine that answers questions about the future with a probability and the research behind it, rather than with a paragraph of hedged prose. You pose a question in one of six shapes — probability, numeric, date, categorical, conditional, or decision — and a team of agents searches, reads and reasons its way to an estimate you can inspect. The differentiator the company leans on is a public track record rather than a benchmark table it wrote itself: it ranks first of 197 bots on the Metaculus FutureEval live tournament, scored by Metaculus on real unresolved questions, and twentieth of 335 on the Forecasting Research Institute's contamination-free ForecastBench. It also trades real money on Kalshi, Polymarket and the S&P 500 and publishes every position with its research, losers included, which is an unusually falsifiable claim for an AI product. On its own 1,907-question pastcasting benchmark it scores 0.122 against 0.130 for the best frontier model. Beyond single forecasts there is a toolkit around them — multi-agent runs and research teams for batch work, plus an agent map for cheaper row-level passes — and the whole thing is available over an API so another agent can call it. Pricing is per question rather than per seat, which fits the intermittent way forecasting actually gets used: you pay for the questions you ask and the subscription mainly buys concurrency and a usage discount.
Ideal use cases:
- •Teams or individuals who need six question shapes including conditional and decision forecasts
- •Teams or individuals who need ranked #1 of 197 bots on the metaculus futureeval live tournament
- •Teams or individuals who need live real-money positions on kalshi, polymarket and the s&p 500, published with losses
- •Teams or individuals who need multi-agent runs and research teams for batch forecasting
- •Anyone focused on forecasting workflows
- •Anyone focused on research workflows
Best for: StoreRadar
StoreRadar sells the Shopify ecosystem as a single downloadable CSV rather than as a seat in a search interface, which is the whole product decision: you buy the file once, you keep it, and there is no subscription gating access to data you already paid for. The current snapshot is 2.6 million stores with 1.9 million emails and roughly 200,000 phone numbers across 68 columns and about 480 MB. The columns go well past contact details into the fields that make targeting possible — detected Shopify apps, technologies, theme, product and collection counts, blog presence and article count, page count, password-protected status, ad pixels, languages, countries, industry, social profiles, domain creation and expiry dates, first-seen and last-detected timestamps. Two scores are computed per store: a 0–100 lead score built from migration signals, theme budget, tech stack, store liveness, social presence and maturity, each contribution itemised, and a separate SEO score. The buyer is a Shopify agency, app developer, theme seller or freelancer running outbound. The optional add-on is the honest part of the pitch: raw addresses on any list this size are a deliverability liability, so the vendor runs MX checks, SMTP mailbox-level verification and a MillionVerifier bulk pass, shipping a valid/invalid/accept-all status and a 0–100 confidence score per address. The comparison drawn is against Store Leads at $3,000 a year for one seat.
Ideal use cases:
- •Teams or individuals who need 2.6m shopify stores, 1.9m emails, 200k phones in one csv
- •Teams or individuals who need 68 columns including apps, theme, tech stack and ad pixels
- •Teams or individuals who need itemised 0–100 lead score and separate seo score per store
- •Teams or individuals who need optional three-pass email verification with confidence scores
- •Anyone focused on shopify workflows
- •Anyone focused on lead-generation workflows
📊 Other Data & Analytics Tools to Consider
FutureSearch and StoreRadar aren't the only options. Here are other popular tools in the same space:
Databricks AI
Enterprise AI and data lakehouse platform
Akkio
No-code predictive AI for business analysts
Hex
Data workspace with AI analysis and apps
MindsDB
AI layer for databases with SQL ML
Obviously AI
No-code ML platform for predictions
Julius AI
Chat with your data for instant analysis
Is one of these your tool?
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Frequently Asked Questions
Is FutureSearch better than StoreRadar?
It depends on your needs. FutureSearch offers 6 key features including Six question shapes including conditional and decision forecasts and Ranked #1 of 197 bots on the Metaculus FutureEval live tournament, while StoreRadar provides 5 features including 2.6M Shopify stores, 1.9M emails, 200K phones in one CSV and 68 columns including apps, theme, tech stack and ad pixels. FutureSearch uses a freemium model with a free tier, while StoreRadar is paid. Choose based on which features and pricing model align with your requirements.
Is FutureSearch cheaper than StoreRadar?
FutureSearch is cheaper, starting at $20/month compared to StoreRadar's $149/month. FutureSearch offers a free tier, making it easier to get started. Always check the official websites for the most current pricing.
Can I use FutureSearch and StoreRadar together?
Yes, many users combine FutureSearch and StoreRadar in their workflow. FutureSearch excels at six question shapes including conditional and decision forecasts, while StoreRadar shines with 2.6m shopify stores, 1.9m emails, 200k phones in one csv. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between FutureSearch and StoreRadar?
While both are data & analytics tools, FutureSearch emphasizes six question shapes including conditional and decision forecasts, whereas StoreRadar is known for 2.6m shopify stores, 1.9m emails, 200k phones in one csv. The best choice depends on your specific workflow and feature priorities.
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