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.