Selling Signals - the Data Monetisation Podcast

James Worthington and Eric Evans

Selling Signals is the podcast for anyone building, selling, or buying data, with a focus on commercialising data in the investor ecosystem.

Each episode brings together industry insiders to share real, first-hand experience from the front lines of data sales. We unpack what actually works when turning raw data into revenue, whilst exploring other data buying silos to break down the walls between them.

Selling Signals delivers practical lessons to help data teams sell better and build stronger, more commercial data businesses.

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21 episodes
fortnightly
Avg 48 min
English

Episodes 21

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S1 · E21
Friday · 46 min
Vinesh Jha: Turning Data Into Alpha
In this episode of Selling Signals, we're joined by Vinesh Jha, CEO of ExtractAlpha and former quant researcher at Morgan Stanley's PDT, to explore how quantitative data products are developed, validated and commercialised. Drawing on ExtractAlpha's new AI Earnings Transcript Model, Vinesh explains how his team identifies predictive opportunities, builds investment signals and differentiates its research from what hedge funds can develop internally. We also get into the commercial realities of selling to funds: how they evaluate external signals, why research transparency matters, how ExtractAlpha structures trials and what vendors routinely get wrong when bringing datasets to market. We finish by discussing how AI is changing the economics of quantitative research and allowing vendors to evaluate more potential sources of alpha.
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S1 · E20
October 2 · 49 min
Arsham Ghahramani: Voice AI for Expert Networks
In this episode of Selling Signals, we’re joined by Arsham Ghahramani, CEO of Ribbon AI. Arsham explains how a product built to interview job candidates found a new market in expert systems and investment research. He describes a hedge fund that went from consulting a handful of experts to interviewing a hundred on the same question. We discuss what this changes about research and how Ribbon handles the confidentiality of a fund’s questions. We also explore the value of expertise that has never been written down. Arsham shares his view on why demand for human knowledge could grow as AI improves, including the possibility of models calling experts when they get stuck.
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S1 · E19
September 18 · 54 min
Matthew Bernath: Building a Business Around Your Data
In this episode of Selling Signals, we’re joined by Matthew Bernath, co-founder of Alternata. Matthew works with companies exploring whether their existing data could support a new business. We discuss how to assess the commercial opportunity before committing resources. Matthew explains how prototypes built with synthetic data can help test a proposed product with buyers. He also shares his approach to pricing around the value a customer expects to receive. The conversation turns to consumption pricing and Matthew’s preference for long-term relationships in which buyers help improve the product. He explains why one-off AI training deals can still make sense when the revenue justifies the work involved. Throughout the discussion, Matthew returns to one constraint. A data business should not damage the core operation that produces its data. We explore how that affects the opportunities a company should pursue.
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S1 · E18
September 3 · 48 min
Freeman Lewin: Agentic Data Sourcing
What happens when the person sourcing your data is no longer a person? In this episode of Selling Signals, we’re joined by Freeman Lewin, co-founder of Brickroad. Freeman began his career in private equity and later worked as an attorney negotiating data and AI contracts. Brickroad uses agents to discover new data suppliers and automate what Freeman calls the “messy middle” of procurement. Its agents search thousands of sources and infer key details about a dataset. They then surface the suppliers most worth investigating. We also discuss how vendors should think about monetising their data with both frontier AI labs and smaller specialist AI teams.
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S1 · E17
August 20 · 43 min
Tjeerd van Cappelle: Literally Selling Signals
In this episode of Selling Signals, we’re joined by Tjeerd van Cappelle, founder of aiLiftOff. Tjeerd spent more than 16 years on the buy side as a quantitative investor before building a company that forecasts revenues and earnings for stocks globally. We discuss what quants look for in data vendors and why a backtest is only the start of the conversation. We also cover the challenge of selling model output, where trust can matter as much as accuracy. The episode ends with a fascinating discussion on artificial stock markets and what they could mean for AI-driven investment research.
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S1 · E16
August 6 · 53 min
Matt Ober: What the Buy Side Really Wants
Matt Ober was looking for unconventional datasets before alternative data became an established industry. He has led data strategy at WorldQuant, served as Chief Data Scientist at Third Point and now works with data providers through Social Leverage and Initial Data Offering. In this episode, he explains how the market operates from the fund's side. The buying process differs sharply between quant and fundamental investors. A quant team may begin by examining coverage, history, frequency, delivery and point-in-time integrity. A fundamental analyst usually begins with a company and a specific investment question. We discuss what vendors should provide during a trial, why external research cannot replace a fund's own testing and how poor documentation can waste a limited evaluation window. Matt also gives his views on pricing, renewals, distribution and the importance of maintaining good relationships with buyers.
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S1 · E15
July 23 · 54 min
Kai Searle: Hiring Elite Data Sellers
In this episode of Selling Signals, we’re joined by Kai Searle, Senior Consultant at Engage PSG. Kai helps data, research and AI businesses build go-to-market teams across the US, UK and EMEA. We discuss why hiring for data companies differs from hiring for SaaS. Kai explains what separates elite data sellers from average ones, and how candidates can assess whether an opportunity is as strong as the hiring team says it is. This episode is for founders building commercial teams and for candidates navigating the data sales market.
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S1 · E14
July 9 · 47 min
Nick Derewlany: From Data Asset to Data Business
In this episode of Selling Signals, we’re joined by Nick Derewlany, a data monetisation leader who has worked across GlobalData and Trustpilot building new data products inside larger organisations. Nick brings a practical view on how corporates should think about commercialising existing data assets. We talk about why “we have lots of data” is not the same as “we have a data business”, and what companies should prove before hiring a team or putting large revenue targets in front of the board. The conversation also covers the path from 0 to 1, the importance of repeatable demand, and why $1m ARR across several customers is a very different signal from one large bespoke deal. This episode is for anyone building, buying or selling data products, particularly inside companies where data monetisation sits alongside a much larger core business.
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S1 · E13
June 25 · 45 min
Brad Preston: Alternative Data in Emerging Markets
In this episode, we’re joined by Brad Preston, founder of Beagleworks. Brad spent two decades on the buyside in South Africa before moving into data and research, giving him a rare perspective on how alternative data gets used outside the US and Europe. We discuss what makes emerging markets different for data providers, why pricing needs to reflect liquidity and stock coverage, and how Brad thinks about the line between raw data and research. A highlight of the conversation is Brad walking through how he would evaluate a hypothetical South African consumer receipt dataset, from the economics of the market to the questions it could help investors answer. This episode is essential listening for anyone selling alternative data into smaller or less mature markets, or trying to understand what buyside users really need before a dataset becomes useful.
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S1 · E12
June 12 · 56 min
Jordan Hauer: Taking Stock of the Alternative Data Industry
In this episode of Selling Signals, we’re joined by Jordan Hauer, Founder and CEO of Amass Insights. Through Amass, Jordan helps investment firms discover, evaluate, and source datasets while also helping data providers better understand and monetise their assets. Having spent more than a decade at the centre of the market, Jordan has a unique perspective on how alternative data has evolved, from the industry’s early days of scarce and highly differentiated datasets to today’s world of abundant data and rapidly advancing AI tools. We discuss which datasets are seeing the strongest demand in 2026, how funds evaluate new data sources, and why sales cycles remain stubbornly long despite significant improvements in the market. Jordan also shares his views on trials, pricing, backtesting, and the common mistakes data providers make when trying to sell to investment firms. Whether you’re a data provider, investor, or anyone building in the data economy, this episode offers a valuable look at where the industry is heading next.
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S1 · E11
May 28 · 42 min
Jonathan Chin: Building a Tier 1 Dataset
In this episode of Selling Signals, we’re joined by Jonathan Chin, co-founder of Facteus and author of Data-Minded. Jonathan brings a founder’s view on what it takes to build a transaction data provider trusted by institutional investors. We talk about why data businesses do not behave like SaaS companies. Data often sells optionality rather than a fixed outcome, which changes the way buyers evaluate products. Jonathan explains where SaaS playbooks break down, what still carries across and why data quality issues are different from software bugs. We also discuss aggregation, alpha decay and the role of AI in the future of alternative data. A big part of the conversation focuses on whether alternative datasets could become part of future model training rather than simply being queried through tools or MCP servers.
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S1 · E10
May 14 · 48 min
Sheraz Bhatti: Land and Expand
In this episode of Selling Signals, we’re joined by Sheraz Bhatti, who led Customer Success at Similarweb and now does the same at Quartr. We discuss what Customer Success means in a data business and why it differs from the standard SaaS playbook. Sheraz explains what good adoption looks like, why usage metrics can be misleading, and how data vendors can tell whether their product is making it into real investment decisions. We also cover churn risk, internal champions and what “land and expand” looks like when the product being sold is data.
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S1 · E9
May 1 · 37 min
Julia Meigh: Macro, Mayhem & (Prediction) Markets
In this episode of Selling Signals, we’re joined by Julia Meigh, who has spent years helping investors decide what data to buy, with a particular focus on macro and ESG. Few people have had a closer view of how macro investors think about new datasets or how providers break into the market generally. We discuss what macro funds actually need from data and where vendors still have room to win. Julia also shares her view on geopolitical uncertainty and on prediction markets, both of which are playing a bigger role in macro investing. This episode is essential listening for anyone building data products for macro investors or trying to understand where that market is heading.
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S1 · E8
April 16 · 40 min
Florence Broderick: The Cutting Edge of Data Sales
In this episode of Selling Signals, we’re joined by Florence Broderick, CRO at General Index, where she is helping scale a commodities data business. Florence has worked across both software and data companies, which gives her a rare perspective on how different those worlds are when it comes to selling, hiring and supporting customers. We discuss why SaaS is still ahead of DaaS in go-to-market maturity and how AI is changing sales teams in practice. Florence shares what is actually working in prospecting today, how data vendors should think about AI use in customer contracts, and why in-person events may become even more important as more of the sales process becomes automated. This episode is essential listening for anyone building a data business, modernising a GTM team, or trying to understand what data companies still need to learn from SaaS.
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S1 · E7
April 2 · 55 min
Aidan North: Alt Data in an Agentic World
In this episode of Selling Signals, we’re joined by Aidan North, Commercial Lead at Orbit. Orbit sits at the intersection of unstructured data, AI and institutional investing, helping transform unstructured information into formats that can be consumed within investment workflows. We discuss how hedge funds are adopting AI, Orbit’s position at the forefront of agentic use of alternative data, and what has changed since the early days of pre-LLM systems. Aidan also explains Model Context Protocol (MCP) and why it is becoming an important part of the data ecosystem, enabling smaller funds to access and integrate datasets that were previously out of reach. This episode is essential listening for anyone building or selling data products into the investment industry, or trying to understand where AI is having real commercial impact.
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S1 · E6
March 19 · 53 min
Valsys: Ticker Mapping Explained
In this episode of Selling Signals, we are joined by James's Valsys co-founders, Jack Fuller and Simon Bessey, for a practical discussion on ticker mapping. It is one of the least visible parts of the alternative data workflow, but it has a big impact on whether a dataset can actually be used by the buy side. We discuss what ticker mapping is and why funds care about it. Jack and Simon explain why the problem is harder than it looks. They show how point-in-time accuracy changes the picture and what good validation looks like. We also get into why ownership changes and M&A make mapping much harder to get right. This episode is essential listening for any data provider that wants to make its product usable in capital markets.
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S1 · E5
March 5 · 44 min
Lauren Ambrose: Monetising Exhaust Data
In this episode of Selling Signals, we’re joined by Lauren Ambrose, Business Development Director at Snoop. Before joining Snoop, Lauren spent nearly a decade at PitchBook and later worked at Ascential, giving her a rare view of how data is commercialised across very different organisational settings. We discuss how PitchBook became embedded in private market workflows and how different the challenge becomes when you’re building a new revenue line from exhaust data inside a consumer-facing business. Lauren also shares how Snoop’s UK consumer spending data can be positioned not only to investors, but also to adjacent markets such as advertising. This episode is essential listening for anyone breaking into new data markets, prioritising early buyers or trying to sell one dataset across multiple use cases.
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S1 · E4
February 19 · 1 hr 1 min
Stuart Reid: Quant to Entrepreneur
In this episode of Selling Signals, we’re joined by Stuart Reid, CEO of Nosible. A computer scientist and former quant, Stuart has priced complex derivatives, experimented with deep learning for market prediction, and now leads a team building infrastructure for financial institutions to search and monitor the web in real time. At Nosible, Stuart and his team index tens of millions of webpages every day, structuring and verifying web content so it can be used by investment funds, asset managers, banks and insurers. Their focus on point-in-time integrity and traceability makes them akin to the “point-in-time police” of the internet. We discuss what data vendors often misunderstand when selling to systematic investors, why Nosible is building a web-scale search engine for funds, and how AI is changing the structure of the web itself. As more content is created, copied and remixed at scale, verification may matter more than volume. This episode is essential listening for anyone building web-derived alternative data, selling to quants or thinking seriously about the future of information in financial markets.
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S1 · E3
February 5 · 49 min
Marko Matejcic: Media Buyers and Alternative Data
In this episode of Selling Signals, we’re joined by Marko Matejcic, who has spent more than a decade building and commercialising data products across the advertising and marketing ecosystem. Marko has worked across identity, privacy, measurement, modelling and activation, giving him a practical view of how alternative data is actually used in media. We discuss how media buyers evaluate alternative data, how planning, activation, and measurement differ from investment workflows, and why attribution is such a difficult problem to solve. Marko explains where alternative data vendors often struggle when moving from hedge funds into media and what needs to change for data to be adopted and licensed by agencies and brands. This episode is essential listening for anyone selling or building alternative data who wants to understand how a very different data buying world operates.
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S1 · E2
January 22 · 48 min
Ed Lavery: Selling Alternative Data Across Funds and Corporates
In this episode of Selling Signals, we’re joined by Ed Lavery, who previously built and scaled investor data sales businesses at Similarweb and Placer.ai. Ed draws on his experience commercialising complex behavioural datasets to hedge funds, asset managers, and corporate buyers, offering a rare perspective on how data products succeed across different markets. We discuss how alternative data vendors can identify genuine “white spaces” in the investment ecosystem, why selling data to corporates often requires a fundamentally different strategy than selling to funds, and how investment approaches have evolved beyond simply “calling the quarter.” Ed brings a thoughtful, highly practical view on what it takes to turn complex datasets into repeatable revenue. This episode is essential listening for anyone navigating data monetisation across financial services and corporate markets.
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