SparkToro Blog

Google, Apple, and Amazon Stifle Innovation When They Favor Their Own Products

The SparkToro team got an exciting surprise on Sunday evening: a mention of our research on Last Week Tonight by John Oliver. The full episode, Big Tech Monopolies, is available on YouTube. It covers an issue I’ve railed against before, but with a heightened sense of urgency: there is actually a bipartisan bill in Congress

SparkToro’s Mission, Vision, and Values: BELUX

Those skilled in the art of BS detection can tell you that 99% of company mission, vision, and values statements are meaningless. For corporate ideals to be more than just blatant-hypocrisy-in-poster-form, leadership has to build them into the company’s operating systems: how they hire/fire/promote, how they prioritize product investments, treat customers, make decisions around funding


SparkToro & Followerwonk Joint Twitter Analysis: 19.42% of Active Accounts Are Fake or Spam

TL;DR – From May 13-15, 2022, SparkToro and Followerwonk conducted a rigorous, joint analysis of five datasets including a variety of active (i.e. tweeting) and non-active accounts. The analysis we believe to be most compelling uses 44,058 public Twitter accounts active in the last 90 days. These accounts were randomly selected, by machine, from a

SparkToro Startups Team

SparkToro’s Year 2 Retrospective: Can Chill Work, Alternative Funding, and an Indie Approach Scale?

Two years ago today, at the nerve-wracking start of a global pandemic, we launched SparkToro. Since then, we’ve learned a lot, and uncovered plenty of unanswered questions, too. As is tradition, I’ll try to share the good, the bad, and the interesting in the hopes it can help other entrepreneurs, especially those considering an alternative

Provable Marketing Attribution is a Boondoggle; Trust Your Gut Instead

You’ve heard the marketing analytics spiel before. It goes something like: Marketing journeys are long, complicated, multi-channel paths. Tracking them is always imperfect, but if you employ an extensive, expensive, difficult-to-configure combination of tools, tracking systems, and deeply talented statistics professionals, you can build a high-quality, predictive attribution modeling structure that approximates reality with relatively