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.

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.

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.

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.

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.

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.

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.

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.