Market Minds Advisory
Alternative Data Market

Alternative Data Market: Alternative Data: Signal Decay, Provenance Risk and the Buyer Base That Is Smaller Than It Looks

Every dataset that works stops working once enough people have bought it, which means providers are selling something they actively destroy by distributing, and this industry has never resolved that.

Lead Analyst

Published

September 2026

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2025 MARKET VALUE$9.4BMarket Size 2025
2036 FORECAST VALUE$47.2BBase Case , 2026 to 2036
CAGR 2026 TO 203615.8 %Bull 17.0% / Bear 14.6%
INCREMENTAL OPPORTUNITY$36.3BNet 10- year value creation
EXPANSION MULTIPLE4.34x2036 value over 2026 base
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Executive Snapshot and Market Trajectory.

A dataset that predicts a quarterly result stops predicting it once enough funds trade on it, typically inside 14 months. Providers are therefore selling something they destroy by distributing widely, and nobody in this industry has resolved that. Subscriptions reduce what the product is worth. Nobody has resolved that.
The response has been to move where decay is slower. Geospatial and earth observation grows at 23.7%, half again the market rate of 15.8%, because physical activity signals persist longer than transaction panels do. Trade and commodity flow data follows closely behind at 21.2%. North America takes 48% of value because the institutional buyer base sits there, and only around 780 firms globally hold the budget and capability to use this properly.
Concentration is very low at roughly 23% across the top five on measured subscription revenue, spread across hundreds of providers each holding a narrow specialism and very little else. Compliance is the constraint most of them consistently underestimate: around 27% of datasets are declined on provenance or privacy grounds alone. Data quality does not compensate for weak documentation, however predictive the dataset in question happens to be.
Market Definition
This market covers non-traditional datasets and derived analytics sold for investment and corporate decision-making, spanning transaction and consumer spending panels, geolocation and foot traffic, web scraped pricing and product data, geospatial and earth observation, trade, shipping and commodity flows, and employment, sentiment and digital engagement data. Revenue is measured as data subscription and attributable analytics value at provider level. Traditional market data feeds, exchange pricing, company fundamentals, credit ratings, general business intelligence software and consumer marketing data sold for advertising are excluded.
Base Year Value
$9.4B in 2025 (MMA Primary Research Dataset, September 2026)
Forecast Period
2026 to 2036, eleven discrete annual values
CAGR
15.8% base case. Bull 17.0%. Bear 14.6%.
Fastest Growth Segment
Geospatial and Earth Observation: 23.7% CAGR
Fastest Growth Country
Singapore: 20.4% CAGR
Fastest Growth Region
South Asia and Pacific: 18.2% CAGR
Largest Region
North America: 48% of 2025 global value
Market Leaders
YipitData, Similarweb, Kpler, Planet Labs and Placer.ai lead on measured alternative data subscription and analytics revenue. Source: MMA Primary Research Dataset, July 2026.
Primary Survey
n=3,800 procurement and R&D decision-makers, Q4 2025, six countries
Methodology
Demand-side build-up, cross-validated against public data, 47 expert interviews

Alternative Data Market Forecast Scenarios

alternative-data-market-size-forecast-scenario-1788423690204
Growth ran at 14.6% from 2020 to 2025, well below the expectations that attracted capital into the sector. Pandemic conditions produced a genuine surge as traditional indicators stopped describing anything and funds paid for real-time visibility into activity nobody could otherwise observe. That demand normalised afterwards, and providers discovered that their most valuable datasets had been sold widely enough that the differentiated returns supporting the price had largely disappeared.
The base case at 15.8% rests on three mechanisms. Physical activity data decays more slowly than transaction panels, because observing ships, facilities and land use produces signals that many buyers can hold without eliminating the advantage. Corporate buyers now represent 31% of spending and want answers rather than feeds, which is a different and more durable product. Third, compliance requirements are consolidating spending toward providers with documented provenance, which advantages scale over specialism.
The bull case at 17.0% assumes corporate adoption continues broadening beyond competitive intelligence into operational decisions, where budgets are far larger than investment research allocations. The bear case at 14.6% is that signal decay accelerates as more capital chases the same datasets, forcing providers into exclusivity arrangements that cap their addressable revenue at a handful of clients each.

Selling Something That Distribution Destroys

The commercial problem in this industry is elegant and unsolved. A dataset earns its price by revealing something unpriced, and once enough funds hold it the information is in the price and the dataset describes history. Decay runs around 14 months on transaction panels. A provider maximising subscriptions is therefore destroying the value of the product it sells, and one restricting distribution is capping its own revenue.
TOP FIVE CONCENTRATION23%Highly fragmented across hundreds of specialist data providers
SIGNAL DECAY PERIOD14 monthsTime before a dataset stops generating differentiated investment returns
INSTITUTIONAL BUYER COUNT780 fundsFirms with the budget and capability to use these datasets
CORPORATE SHARE OF SPEND31%Purchases made outside investment management for operating decisions
COMPLIANCE REJECTION RATE27%Datasets declined on provenance or privacy grounds alone
AVERAGE DATASET PRICEUSD 185,000Annual subscription for a single institutional grade dataset
The buyer base is also considerably smaller than the sector's marketing suggests. Roughly 780 firms worldwide combine the budget, data science capability and compliance tolerance to use these datasets properly, and many buy the same panels. Below that tier, funds lack the people to extract anything from a raw feed. The corporate market that was supposed to broaden demand mostly wants analysis rather than data, which is a different business.
Compliance has become the constraint providers most consistently underestimate. Around 27% of datasets are declined on provenance grounds: unclear consent chains, scraping of doubtful legality, or no way to demonstrate the information is not material and non-public. Data quality does not compensate for weak documentation, and a fund's compliance function has no reason to take the risk.
"Everybody in this sector talks about signal and almost nobody talks about the arithmetic that follows from selling it. If a dataset works, you can sell it to five funds at a high price or five hundred at a low one, and the second option means it stops working. Most providers pick the second and are surprised by the outcome."
Director, Data and Investment Technology Practice · MMA Technology Practice · September 2026

Market Trends

Physical Activity Data Decays More Slowly Than Transactions

Transaction and card panels predict quarterly results directly, which is exactly why the advantage disappears once enough funds hold them, typically within 14 months. Observations of physical activity behave differently: vessel movements, facility utilisation, construction progress and land use inform a broader set of questions and support many holders without eliminating the edge for any of them. Geospatial and earth observation grows at 23.7% for that reason, and trade flow data at 21.2%. Providers are shifting toward data whose value survives distribution rather than data that predicts one number. Portfolio decisions here are made years ahead of the decay.
Market Impact: Corporates fund 31% of spending

Corporate Buyers Want Answers Rather Than Feeds

The corporate market now represents 31% of spending and behaves nothing like the investment one. A commercial team wants to know how a competitor is performing or where demand is shifting, and has neither the data scientists nor the appetite to derive that from a raw panel. Providers delivering analysis, benchmarks and answers reach that budget, while those delivering feeds reach only the small number of corporates with genuine analytical capability. It is a service business attached to a data asset rather than a data business, and the margins reflect that.
Market Impact: Fastest segment at 23.7% growth

Market Opportunities and Growth Drivers

Corporate Operating Budgets Exceed Investment Research Allocations

An asset manager funds alternative data from a research budget measured in single-digit millions, while a large corporate can fund competitive and demand intelligence from operating budgets an order of magnitude larger, because the decision it informs is pricing, capacity or market entry rather than a position. Corporate purchasing now represents 31% of spending and is growing faster than the investment side. The product required is different, since the buyer wants an answer rather than a dataset, and providers built for quantitative funds frequently cannot deliver that. Quantitative providers rarely built that capability.
Market Impact: Decay hits within 14 months

Satellite Capacity Makes Physical Observation Continuous

Earth observation constellations now revisit most locations daily or better at resolutions that support counting vehicles, measuring inventory and monitoring construction, which turns periodic imagery into a continuous activity signal. That capability barely existed commercially a decade ago and now underpins the fastest growing segment at 23.7%. The signals decay more slowly than transaction data because they inform many questions rather than predicting one number. Cost per observation has fallen far enough that continuous monitoring of many sites is affordable to buyers who could previously afford occasional snapshots. Continuous monitoring is now affordable at many sites.
Market Impact: Rejects 27% on provenance

Market Restraints and Challenges

Distribution Destroys the Product Being Distributed

A dataset generating differentiated returns stops doing so once enough funds trade on it, with decay running around 14 months on transaction panels, which means growth in subscriptions actively reduces the value of what is being sold. The root cause is that investment edge is a relative position rather than an absolute property of the data. Commercially this forces providers to choose between few clients at high prices and many at low ones. Mitigation runs through exclusivity tiers, delayed general release and moving toward data whose value survives being widely held.
Market Impact: Decay runs about 14 months

Provenance Failures Disqualify Data Regardless of Quality

Around 27% of datasets are declined by investment firms on compliance grounds rather than on quality, because consent chains on transaction and location data are unclear, scraping arrangements are legally doubtful, or the provider cannot demonstrate the information is not material and non-public. The root cause is that many providers assembled data before documenting how, and retrofitting provenance is often impossible. Commercially this eliminates suppliers before evaluation. Mitigation requires documented consent and collection methodology built in from the start rather than assembled afterwards. Retrofitting documentation is usually impossible once data exists. Providers discover that during their first institutional review.
Market Impact: Corporates now 31% of spending
3 additional market trends, 4 additional growth drivers, and 2 additional restraints and challenges are covered in the full report. Contact sales@marketmindsadvisory.com to access the complete intelligence.

Segment CAGR and Growth Architecture

Segmentation follows the data type, because each carries a different decay profile, a different compliance exposure and a different buyer. Data predicting a single reported number behaves completely differently from data describing physical activity, and that difference governs both pricing strategy and how many customers a provider can sensibly serve. Customer counts follow from that.
alternative-data-market-market-share-analysis-1788423690745

Geospatial and Earth Observation

Earth observation is the fastest part of this market at 23.7%, half again the market rate of 15.8%, and it grows partly because its signals survive distribution. Counting vehicles, measuring stockpiles, monitoring construction and tracking land use inform many different questions rather than predicting one reported figure, so many buyers can hold the same imagery without eliminating each other's advantage. Constellation capacity now supports daily or better revisit at useful resolution, which converts periodic snapshots into continuous monitoring. Compliance exposure is also lower than transaction or location panels, since observing physical activity from orbit raises far fewer consent questions. Constellation economics have improved considerably, and cost per observation now supports monitoring many sites continuously rather than occasionally.
CAGR 23.7%

Trade, Shipping and Commodity Flows

Trade and commodity flow data grows at 21.2% on demand that is operational rather than analytical, which makes it unusually durable. Shippers, traders, refiners and manufacturers need to know where cargo actually is to make routing, inventory and pricing decisions weekly, and that requirement does not decay when competitors hold the same information. Disruption to routing and tariff arrangements has raised the value considerably. Singapore is the fastest-growing country market at 20.4% largely on this demand, given the concentration of commodity trading there, and buyers include corporates who would never purchase an investment dataset. Renewal here is far stronger than any investment subscription achieves, because the requirement returns every week.
CAGR 21.2%
Full segment breakdown across 6 segments available in the complete report.

Regional Architecture and Country Demand Map

Spending concentrates where the institutional buyer base sits rather than where the data originates. A relatively small number of funds and corporates account for the overwhelming majority of subscriptions, and they are not distributed anything like evenly. The buyer base is small and geographically lopsided.

North America

North America holds 48%, far above the regional band, because the institutional buyer base is overwhelmingly American: hedge funds, quantitative managers and asset managers with dedicated data science teams and research budgets that support USD 185,000 subscriptions routinely. Most providers were founded here and sell here first. Corporate adoption is also furthest advanced, with consumer goods, retail and industrial companies buying competitive intelligence from the same providers. Compliance scrutiny is correspondingly intense, since securities regulation makes material non-public information a genuine exposure rather than a theoretical one. Regional growth at 15.0% is near the market rate, since the institutional buyer base here is mature and its numbers are not expanding.
Share: 48% | CAGR: 15.0% (2026 to 2036)

Western Europe

European demand is smaller and considerably more constrained by data protection requirements that make consent chains on transaction and location data far harder to document defensibly. London hosts most of the region's institutional buying, with quantitative and macro funds purchasing at specifications comparable to American ones. Continental corporate buyers show more interest than continental funds, particularly in supply chain and commodity flow data. Providers serving the region carry compliance overhead that American-only competitors avoid entirely, which shows up in both cost structure and the datasets they are able to offer. Regional growth at 14.2% is the slowest of the major markets, constrained by data protection requirements rather than by any lack of analytical capability.
Share: 22% | CAGR: 14.2% (2026 to 2036)
Regional intelligence for 5 additional markets available in the complete report: East Asia, South Asia and Pacific, Latin America, Middle East and Africa, Eastern Europe. Contact sales@marketmindsadvisory.com.
alternative-data-market-country-cagr-analysis-1788423691268

Where Data Providers Actually Earn

Selling an investment edge widely destroys it, and the institutional buyer base is roughly 780 firms rather than the market the sector describes. What holds value is data whose signal survives distribution, corporate buyers who want answers, and provenance documentation that survives a compliance review. Everything else depreciates as it sells. Scarcity is the asset here.

Sell Data That Survives Being Widely Held

Transaction panels predicting a quarterly figure decay within about 14 months as more funds trade on them, which means every additional subscription reduces what the product is worth. Physical activity data informs many questions rather than one and supports many holders simultaneously without eliminating anybody's advantage. Providers weighted toward observational data sustain around 3 times the customer count at comparable pricing. It is a portfolio decision made years before the decay becomes visible, which is why so many providers face it too late. Most providers face it far too late.
Market Impact: Supports 3 times the paying customer count overall

Reach Corporate Budgets With Answers Not Feeds

Corporate buyers now represent 31% of spending and fund purchases from operating budgets an order of magnitude larger than investment research allocations, because the decision concerns pricing, capacity or market entry. They want analysis rather than a panel, and lack the data scientists to derive one from the other. Providers delivering answers achieve roughly 2 times the contract value of feed subscriptions and renew considerably better. It requires building analytical services that quantitative-focused providers have often deliberately avoided constructing. Service capability is the barrier, not the data. Feeds and answers are different products.
Market Impact: Achieves 2 times the feed contract value overall

Document Data Provenance Before Anyone Asks

Around 27% of datasets are rejected on compliance grounds rather than on quality, covering consent chains, collection legality and material non-public information exposure, and retrofitting that documentation is frequently impossible once data has been assembled. Providers with documented consent, collection methodology and legal review pass evaluation where better datasets fail entirely. It is unglamorous work that has to happen before collection rather than after. Compliance teams have no incentive whatsoever to accept an undocumented dataset, however predictive somebody claims it is. Documentation precedes collection or it never exists. Reviews happen before evaluation, not after.
Market Impact: Passes the review where 27% get rejected outright

Price Exclusivity Explicitly Rather Than Accidentally

Providers who quietly limit distribution get neither the price premium exclusivity deserves nor the volume that broad sale would generate, which is the worst of both positions. Explicit exclusivity tiers, with early access, restricted client counts and delayed general release priced accordingly, let a provider monetise scarcity deliberately. Funds pay multiples for genuine exclusivity and pay very little for a dataset they suspect is widely held. Making the distribution policy visible converts an unmanaged problem into a pricing structure that both sides can evaluate. Funds pay multiples for exclusivity they can verify. Decay begins within 14 months of general release.
Market Impact: Decay begins within 14 months of general release

Who Controls the Margin Pool

Concentration is very low at roughly 23% across the top five on measured subscription and analytics revenue, and the field runs to hundreds of providers each holding a narrow dataset with a specific application. The gap between leaders and the long tail is provenance documentation, reach into roughly 780 institutions, and analytical capability rather than data quality. Many small providers hold genuinely useful data and cannot pass a compliance review or reach a buyer.
Competition runs on three dimensions. Compliance defensibility is first and eliminates candidates before evaluation, since 27% of datasets are declined on provenance alone. Second is signal durability, because a fund buying data that decays in a year is purchasing a depreciating asset and increasingly prices it that way. Third is analytical delivery for corporate buyers, who represent the growth and want conclusions rather than feeds.

Two pressures are reshaping the field. Consolidation is accelerating as buyers reduce vendor counts to manage compliance overhead, which advantages providers holding several datasets over specialists holding one. Meanwhile corporate demand is pulling the market toward analysis, which favours providers with service capability over those built purely around collection. Rankings will move toward participants with documented provenance and analytical delivery capability.
alternative-data-market-company-positioning-matrix-1788423691809

Competitive Moat and Risk Dimensions

YIPITDATA

Moat: Analytical delivery and coverage breadth

YipitData built analytical products across many companies and sectors rather than selling raw panels, which reaches buyers without data science capability and serves corporate customers as readily as funds. Breadth across datasets means a client reduces vendor count by consolidating, which matters increasingly as compliance overhead grows. Documented methodology and provenance pass institutional review where smaller providers fail.
YIPITDATA

Risk: Transaction data decay exposure

A substantial share of coverage rests on transaction and web-derived data whose investment signal decays within roughly 14 months as client counts rise, which creates pressure to keep adding coverage rather than deepening it. Corporate buyers value the analysis more durably than funds value the signal. Competing datasets covering the same companies erode differentiation further.
KPLER

Moat: Operational commodity flow position

Kpler serves an operational requirement rather than an analytical one, since traders, refiners and shippers need cargo visibility to make weekly routing and inventory decisions regardless of who else holds the same information. That demand does not decay with distribution, which is rare in this industry. Data assembly across vessel tracking, port activity and trade documentation is hard to replicate.
KPLER

Risk: Commodity cycle demand exposure

Demand concentrates among commodity traders, refiners and shipping operators whose spending follows commodity market conditions and trade volumes rather than any independent path. A period of stable routing and low volatility reduces the urgency that currently drives adoption. Expanding into investment buyers means entering a market where signal decay applies.

Players Tracked

Prominent Players

YipitData
Similarweb
Kpler
Planet Labs
Placer.ai

Other Key Players

M Science
Consumer Edge
Earnest Analytics
Facteus
SafeGraph
Advan Research
Sensor Tower
Thinknum
Orbital Insight
Spire Global
ICEYE
Vortexa
Bright Data
Dun and Bradstreet
Nasdaq Data Link

Recent Developments

APRIL 2025

Institutional buyers consolidate providers to manage compliance overhead

Investment firms reduced the number of alternative data vendors under contract, citing the review burden of documenting provenance and consent for each dataset separately. Consolidation favoured providers offering multiple datasets under a single documented methodology rather than narrow specialists. Narrow specialists were dropped in several cases.
Signal: Compliance overhead rather than data quality is now driving the vendor selection decisions at institutional buyers.
SEPTEMBER 2025

Corporate purchasing extends from competitive intelligence into operating decisions

Consumer goods and industrial companies began funding alternative data from pricing, supply chain and capacity planning budgets rather than from market intelligence allocations. The purchases required analysis and benchmarks rather than raw data feeds, which several providers were not equipped to deliver. Budgets were considerably larger than research allocations.
Signal: Operating budgets are far larger than research allocations, and they buy a completely different kind of product.
JANUARY 2025

Providers restructure distribution with explicit exclusivity tiers

Several data providers introduced formal tiering with early access, restricted client counts and delayed general release priced separately, replacing informal limits on distribution. The change followed client pressure to know how widely a dataset was being sold before agreeing terms. Client counts were disclosed under the new arrangements.
Signal: Making scarcity explicit lets providers monetise it, where informal limits captured neither the price nor the volume.

What These Datasets Cost to Produce

Cost structure varies enormously by data type. Panel and transaction data is dominated by acquisition payments to the parties supplying the underlying records, running between 34% and 52% of cost depending on exclusivity and consent arrangements. Earth observation carries satellite capacity and downlink cost instead. Data engineering and normalisation adds roughly 21%, compliance review 11%, and analytical delivery the balance.
Data acquisition terms have been the sharpest pressure. Parties holding transaction, location and application usage records have recognised the value of what they supply and renegotiated accordingly, while consent and privacy requirements narrowed what can legitimately be collected at all. Planet Labs and Similarweb both referenced data acquisition and operating cost conditions in recent annual reporting. Providers with multi-year client pricing absorbed the increases rather than reopening terms.

Exposure varies by data source rather than by scale. Providers dependent on third-party record holders carry acquisition cost and continuation risk they do not control, and a supplier withdrawing can end a product line entirely. Those operating their own collection carry capital cost and control supply. Analytical providers carry labour scaling with clients. Small specialists carry acquisition dependence without a client base to absorb repricing.
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Contract data acquisition on multi-year terms

Parties supplying underlying transaction, location or usage records have discovered what their data is worth and reprice accordingly, which can remove a product line at renewal. Multi-year acquisition agreements secure both supply and cost against that. They require committing volume before demand justifies it. Losing the dataset entirely is worse. Losing a dataset a product was built around is worse.

Build compliance documentation into collection design

Around 27% of datasets fail institutional review on provenance, and documentation cannot usually be reconstructed once data has been assembled through arrangements nobody recorded properly. Designing consent capture, collection logging and legal review into the process costs modest effort and removes the failure mode. Providers retrofitting it found large parts of their historical data could not be documented.

Price analytical delivery separately from data access

Corporate buyers want answers and consume analyst time accordingly, while fund clients want raw access and consume very little. Bundling both into one subscription means feed clients subsidise analytical ones or analytical delivery quietly erodes margin. Separating them lets each be priced against actual cost and clarifies the corporate proposition considerably. That segment approaches a third of spending.

Portfolio Architecture for Margin Defence

Margin architecture separates on whether the provider owns its collection. Data acquired from third-party record holders carries payments that can be repriced at renewal and a product line that can disappear with a supplier decision. Data collected through owned infrastructure, including satellite constellations, carries capital cost and controls supply completely. Analytical delivery earns well and carries labour that scales with clients rather than with data volume.
The volume tension is between fund clients and corporate ones. Funds pay well per subscription, understand raw data, consume almost no service and represent a buyer base of roughly 780 firms that is not growing. Corporates pay more in total, need analysis, consume analyst time and represent a base measured in thousands. Providers built for the first serve a fixed market; those built for the second run a consulting business with a data asset.

High-value revenue concentrates in observational data whose signal survives distribution and in analytical delivery to corporate buyers. Both involve value that does not erode as customers are added, which is the exception here. Transaction and panel data occupies the volume position, generates the visibility that builds a provider's reputation, and depreciates with every subscription sold.

Volume / Commodity-Adjacent

Transaction, panel and web-derived datasets sold as feeds to institutional buyers. The wide range separates providers with owned collection from those paying third-party record holders. Signal decay means the product depreciates as the customer count rises.
Gross Margin: 44-58%

Premium / Certified

Datasets with documented provenance and compliance review that pass institutional evaluation reliably. Margin holds because 27% of competing datasets are eliminated before assessment. Documentation cost is real and it is what makes the revenue accessible at all.
Gross Margin: 52-67%

Sustainability / Regulatory / Next-Generation

Observational and operational data whose value survives distribution, and analytical delivery to corporate buyers. The widest range in the portfolio, spanning satellite capacity cost and analyst-delivered services. Highest margin and the only revenue that does not depreciate with scale.
Gross Margin: 58-79%
alternative-data-market-portfolio-architecture-1788423692497

High-value Sub-segments and Strategic Watch-out

Observational and Flow Data

High value and high growth together, because many buyers can hold the same physical activity signals without eliminating each other's advantage. The margin range reflects collection infrastructure ownership. It also carries lower compliance exposure than transaction or location panels, which removes a substantial cause of rejection.
Gross Margin: 62-79%

Corporate Analytical Delivery

High value with strong growth, funded from operating budgets far larger than investment research allocations and buying conclusions rather than data. The range reflects analyst labour intensity per client. Renewal is considerably better than fund subscriptions, since the answer does not stop working when competitors buy it.
Gross Margin: 56-70%

Transaction and Panel Feeds

The volume core of institutional subscriptions and the part that depreciates as it sells, with signal decay near 14 months on the most heavily distributed datasets. It builds provider reputation and reaches the fund base. Every additional subscription reduces what the product is actually worth.
Gross Margin: 42-56%

Third Party Record Holder Repricing

The strategic watch-out, carried at zero because it represents cost moving to the parties supplying underlying records rather than revenue. Those parties have learned what their data is worth and reprice at renewal. Providers without multi-year acquisition terms can lose an entire product line at a supplier's decision.
Gross Margin: 0-0%

How This Revenue Repeats

Renewal depends on whether the data still works, and for investment buyers that question has an expiry date. Transaction panels renew while they generate returns and are dropped once decay sets in, usually within 14 months. Observational and operational data renews indefinitely because its value does not rest on being scarce. Corporate analytical subscriptions renew best, since a benchmark does not stop working when somebody else buys one.
Adoption depth varies sharply by buyer type. Quantitative funds ingest raw data continuously and build their own models, consuming almost no provider service. Fundamental funds use curated analysis around particular positions. Commodity traders use flow data operationally every day. Corporate strategy teams use benchmarks episodically around planning cycles. Corporate pricing and supply chain functions use it continuously once integrated, the most durable customers available.

The buyer has broadened rather than shifted. Investment research remains the largest single budget and is not growing much, constrained by a base of roughly 780 capable firms. Corporate operating functions are the growth, buying different products from different budgets. Compliance functions now hold an effective veto regardless of who wants the data. Providers organised around fund research address the one buyer whose numbers are fixed.
alternative-data-market-end-use-penetration-index-1788423692982

What Holds Value Here

These are among the four positions where our research anticipates prominent divergence between winners and laggards over the coming forecast period. Each is grounded in the demand model, the regulatory perimeter, and the announced capacity pipeline.
01 / SIGNAL DURABILITY SELECTION

Own data that survives being sold to everybody

Transaction panels predicting a reported figure decay within roughly 14 months as more funds trade on them, which means every subscription added reduces what the product is worth to everybody already holding it. Physical activity and flow data informs many questions rather than one and supports many holders at once without destroying anybody's position. Providers weighted toward observational data sustain around 3 times the customer count at comparable pricing, and the portfolio decision has to be made years before decay becomes visible.
02 / CORPORATE BUDGET ACCESS

Sell answers to operators, not feeds to analysts

Corporate buyers already represent 31% of spending and fund purchases from pricing, capacity and supply chain budgets that are an order of magnitude larger than investment research allocations. They want conclusions rather than panels and have no data scientists to convert one into the other. Providers delivering analysis achieve roughly 2 times the contract value of feed subscriptions and renew far better, though it requires building the service capability that quantitatively-minded providers have often deliberately declined to construct at all.
03 / PROVENANCE DOCUMENTATION DISCIPLINE

Build the compliance file before collecting anything

Roughly 27% of datasets are declined by institutional buyers on provenance grounds rather than on quality, covering consent chains, collection legality and material non-public information exposure. Documentation cannot usually be reconstructed once data has been assembled through arrangements nobody recorded, so providers who retrofitted it frequently discovered that large parts of their historical data could not be documented at all. A compliance function has no incentive whatever to accept an undocumented dataset, however predictive somebody claims that particular dataset happens to be.
04 / EXPLICIT SCARCITY PRICING

Charge for exclusivity instead of limiting it quietly

Providers who informally restrict distribution capture neither the premium that genuine exclusivity commands nor the volume that broad sale would produce, which is the worst available position in a market where decay begins within 14 months. Formal tiering with early access, restricted client counts and delayed general release lets that scarcity be monetised deliberately instead. Funds pay multiples for exclusivity they can verify and they pay very little indeed for data they suspect is already widely held by their competitors.

Engagement Snapshot From the Field

A live engagement with an industry participant carrying material or product regulatory and market exposure ahead of a defining policy shift, showing how our research translates into a defensible multi-year portfolio strategy.
MARKET MINDS ADVISORY · CLIENT ENGAGEMENT SUMMARY
Alternative Data Producer Strategic Portfolio Review and Transition Roadmap 2026·Investment Scenario on Alternative Data Exposure Evaluation 2025-26
CLIENT PROFILE
A quantitative asset manager with roughly USD 34 billion under management across systematic equity and macro strategies (client-reported, unverified by MMA). The firm subscribed to 61 alternative datasets at a combined annual cost near USD 19 million, and acquisition decisions had been made by individual portfolio teams rather than through any central process at all.
STRATEGIC CHALLENGE
Research had shown that measured contribution to returns had fallen across the portfolio while spending rose 40% over three years (client-reported, unverified by MMA). Compliance had separately flagged provenance concerns on several datasets, and nobody could say which subscriptions were genuinely contributing because no consistent attribution framework existed anywhere in the firm.
MMA APPROACH
MMA attributed measured return contribution to each dataset individually rather than to strategies, which the firm had never separated, and tested each against how widely the provider distributed it. We interviewed 17 portfolio and research staff, the compliance function and nine providers. Datasets were assessed on decay evidence and provenance documentation rather than on descriptive quality or vendor reputation.
KEY FINDINGS
  1. Nineteen datasets showed no measurable return contribution over the preceding eighteen months, and fourteen of those were transaction panels the providers confirmed were widely distributed.
  2. Seven datasets could not be documented to compliance standards on consent or collection legality, and three of those were among the most heavily used across strategies.
  3. Total spending on the eight datasets with genuine sustained contribution was roughly USD 4 million, against USD 15 million on everything else combined.
  4. Two providers offered exclusivity arrangements that had never been requested, at prices below the combined cost of datasets subsequently found to contribute nothing.
CLIENT PROFILE
A quantitative asset manager with roughly USD 34 billion under management across systematic equity and macro strategies (client-reported, unverified by MMA). The firm subscribed to 61 alternative datasets at a combined annual cost near USD 19 million, and acquisition decisions had been made by individual portfolio teams rather than through any central process at all.
STRATEGIC CHALLENGE
Research had shown that measured contribution to returns had fallen across the portfolio while spending rose 40% over three years (client-reported, unverified by MMA). Compliance had separately flagged provenance concerns on several datasets, and nobody could say which subscriptions were genuinely contributing because no consistent attribution framework existed anywhere in the firm.
MMA APPROACH
MMA attributed measured return contribution to each dataset individually rather than to strategies, which the firm had never separated, and tested each against how widely the provider distributed it. We interviewed 17 portfolio and research staff, the compliance function and nine providers. Datasets were assessed on decay evidence and provenance documentation rather than on descriptive quality or vendor reputation.
KEY FINDINGS
  1. Nineteen datasets showed no measurable return contribution over the preceding eighteen months, and fourteen of those were transaction panels the providers confirmed were widely distributed.
  2. Seven datasets could not be documented to compliance standards on consent or collection legality, and three of those were among the most heavily used across strategies.
  3. Total spending on the eight datasets with genuine sustained contribution was roughly USD 4 million, against USD 15 million on everything else combined.
  4. Two providers offered exclusivity arrangements that had never been requested, at prices below the combined cost of datasets subsequently found to contribute nothing.
RECOMMENDED STRATEGY
Phase 1: Cancel the nineteen datasets showing no measured contribution and the seven that cannot be documented, releasing roughly USD 11 million annually. Phase 2: Negotiate exclusivity or restricted distribution on the datasets showing sustained contribution, since their value depends directly on how widely they are held. Phase 3: Establish central attribution and compliance review before any new subscription, replacing entirely the team-level purchasing that produced the current portfolio.
OUTCOME
Annual spending fell to roughly USD 9 million while measured return contribution rose, since the released budget funded exclusivity on the datasets that worked (client-reported, unverified by MMA). Compliance exposure was closed out, and every new subscription now passes both attribution and provenance review before any purchase.

Frequently Asked Questions

Foundational context covering the market sizes, CAGR, scope, country, region and competition that inform every finding below. This section is provided to cover basics and most often pre-purchase conversations, answered from the MMA Primary Research Dataset.

What is the current size of the Alternative Data Market?

The market was worth USD 9.4 billion in 2025 and reaches USD 10.89 billion in 2026. Corporate buyers now account for roughly 31% of that spending.

How large will the Alternative Data Market be by 2036?

MMA forecasts USD 47.22 billion by 2036, an expansion of 4.34 times over the forecast period. That represents USD 36.33 billion of incremental annual revenue against 2026.

What is the CAGR for the Alternative Data Market 2026 to 2036?

The base case is 15.8% compound annual growth, with a bull case at 17.0% and a bear case at 14.6%. How far corporate adoption broadens separates the three scenarios.

Which segment is growing fastest?

Geospatial and earth observation grows at 23.7%, half again the market rate of 15.8%. Physical activity signals survive distribution in a way transaction panels do not.

Who are the major companies in the Alternative Data Market?

YipitData, Similarweb, Kpler, Planet Labs and Placer.ai lead on measured subscription and analytics revenue. Together they hold roughly 23% across a field of hundreds of providers.

Which country is growing fastest?

Singapore grows fastest at 20.4%, on commodity trading concentration, where cargo and commodity flow data is a daily operating requirement rather than an analytical subscription bought for research.

Report Segmentation Architecture

The full report scope spans multiple orthogonal segmentation dimensions, with cross-tabulated demand data provided for each dimension pair. Coverage extends further to regional breakdowns, trend trajectories, and the competitive detail needed to support segment-level decision-making.

By Primary Market Dimension

  • Transaction and Consumer Spending Panels
  • Geolocation and Foot Traffic
  • Web Scraped Pricing and Product Data
  • Geospatial and Earth Observation
  • Trade, Shipping and Commodity Flows
  • Employment, Sentiment and Digital Engagement

By End-Use Industry

  • Hedge Funds and Quantitative Managers
  • Traditional Asset Management
  • Commodity Trading and Shipping
  • Consumer Goods and Retail
  • Industrial and Manufacturing
  • Private Equity and Credit

By Commercial Dimension

  • Institutional Subscription Access
  • Corporate Analytical Services
  • Exclusive and Restricted Licensing
  • Data Marketplace Distribution
  • Managed Delivery and Integration
  • Consulting and Bespoke Analysis

By Region

  • North America
  • Western Europe
  • East Asia
  • South Asia and Pacific
  • Latin America
  • Middle East and Africa
  • Eastern Europe

Scope, Methodology, and Coverage

Every figure in this report is reproducible from documented input assumptions. The scope below maps the historical period, the forecast horizon, the segmentation dimensions, and the countries covered, alongside the underlying primary and qualitative methodology.
Historical Period
2020 to 2025
Forecast Period
2026 to 2036
Base Year
2025 (USD billions; MMA Primary Research Dataset, September 2026)
Market Definition
This market covers non-traditional datasets and derived analytics sold for investment and corporate decision-making, spanning transaction and consumer spending panels, geolocation and foot traffic, web scraped pricing and product data, geospatial and earth observation, trade, shipping and commodity flows, and employment, sentiment and digital engagement data. Revenue is measured as data subscription, licensing and directly attributable analytical service value at provider level. Traditional market data feeds and exchange pricing, company fundamentals and filings, credit ratings and scores, general business intelligence software, and consumer data sold for advertising targeting are excluded.
Quantitative Units
USD billions, subscription, licensing and attributable analytics revenue
Segmentation Dimensions
Data type, buyer industry, commercial model, region
Regions Covered
North America, Western Europe, East Asia, South Asia and Pacific, Latin America, Middle East and Africa, Eastern Europe
Countries Covered
United States, Canada, Mexico, Brazil, Argentina, Chile, United Kingdom, Germany, France, Netherlands, Switzerland, Sweden, Ireland, Spain, Poland, Czechia, Japan, South Korea, China, Hong Kong, Taiwan, Singapore, India, Australia, United Arab Emirates, Saudi Arabia, Israel, South Africa
Key Companies Profiled
YipitData, Similarweb, Kpler, Planet Labs, Placer.ai, M Science, Consumer Edge, Earnest Analytics, Facteus, SafeGraph, Advan Research, Sensor Tower, Thinknum, Orbital Insight, Spire Global, ICEYE, Vortexa, Bright Data, Dun and Bradstreet, Nasdaq Data Link
Quantitative Methodology
Primary survey, n=3,800 respondents, Q4 2025, six countries; demand-side model with trade association cross-validation
Qualitative Methodology
47 expert interviews, Q4 2025; applied to validate demand model assumptions, identify emerging dynamics, and assess competitive positioning
Report Format
PDF and XLSX data workbook (Word format preview document)
Publisher
Market Minds Advisory
Report Code
MMA-2026-TEC-941
Published
September 2026
Contact
sales@marketmindsadvisory.com | www.marketmindsadvisory.com

Purchase the full Alternative Data Market Report (2026 to 2036).

The full MMA report examines the tension at the centre of this industry, where selling a dataset widely destroys the value being sold, and identifies the data types and buyers that escape it. It sizes the market to 2036 across six data types, seven regions and 28 countries, with segment growth rates and regional demand mechanisms set out in full. Competitive analysis covers 20 providers assessed on measured subscription and analytics revenue, including moat and risk assessment for the two leaders. The report quantifies acquisition cost structure, signal decay economics and margin architecture across three portfolio tiers. It closes with four strategic verdicts and an anonymised asset manager engagement.
Six data types sized to 2036
Seven regions with demand mechanism analysis
Twenty providers on consistent revenue basis
Signal decay and compliance rejection benchmarks
Margin architecture across three portfolio tiers
Anonymised asset manager data portfolio engagement

Built For The People Who Decide

From boardroom strategy to bench-side execution, this report is read cover-to-cover by leaders shaping the next decade of their industry, turning demand scenarios, market dynamics and valuation benchmarks into decisions.
CXOs/ Presidents/ VPs/ Managers
M&A and Corporate Development
Strategy Teams and R&D Heads
Procurement and Product Directors
Regulatory and Compliance Leaders
Investor Relations and Equity Analysts