Behind the price tag: What you’re actually paying for with Faraday

If you’re evaluating Faraday and wondering what goes into our pricing, we want to be transparent—not just about what you’re paying for, but why it’s structured the way it is.

Because here’s the thing: Faraday isn’t traditional software. We’re not handing over a login and disappearing. You’re getting a tightly integrated system of predictive AI agents, rich data infrastructure, and top-level, human data expertise—all geared towards one common goal: making your marketing smarter and your business more efficient.

It’s not just software—it’s strategy

We don’t believe in "plug-and-play" AI. Faraday’s pricing reflects an ongoing partnership: predictive strategy, data enrichment, model refinement, and real human support. When you work with us, you're getting a team that collaborates closely to ensure your campaigns are driven by data science that actually delivers results. But we don’t stop at generating predictions—we help you apply them effectively, align them to your KPIs, and optimize them for maximum business impact. Our team isn’t just technical—they’re strategic partners focused on making your marketing and sales smarter at every step.

And it is worth noting that this caliber of expertise never comes cheap. High-quality predictive modeling takes serious time, talent, and infrastructure. If you've ever seen a data science job listing, you know the level of skill it demands—like this Gusto listing for a Staff Data Scientist at around $250,000 per year. At Faraday, our forward-deployed data scientists and engineers (FDS and FDE) bring that level of experience directly to your business. Even companies with minimal internal data teams can leverage predictive tools without needing to make a $250K hire. That’s a huge differentiator—we’re not just offering AI, we’re offering embedded expertise to power smarter, faster decisions.

If you’d like to learn more about how our team is here to help you build a strategy, not just get accurate predictions, check out this blog from our Head of Customer Analytics, Chris Waite, or this one from one I wrote about why we chose to forward deploy our DS team.

We prove our value before you ever sign

But that’s not all. Before a single contract is signed, we run predictive tests to ensure we’re a good fit. That includes techniques like pre-signup holdout validation and cross-validation, giving you a clear picture of how our models are likely to perform on your data. We’re not asking you to gamble on potential—we’re aligning your investment with real, measurable value. And the validation doesn’t stop there. Our team continues to monitor model efficacy over time, issuing regular performance reports that highlight what’s working and where we can improve. We won’t recommend a contract unless we’re confident it will generate a meaningful return—and we back that up with ongoing transparency.

Want to learn more about our pre-purchase model validation? Check out this blog which details the holdout test process, or if you’re a real smarty-pants, take a look at this technical deep dive from two of our incredible Data Scientists.

We get that big investments can feel risky

We know that investing in a new platform—especially one centered on predictive AI agents—can feel daunting. That’s why we prioritize regular ROI reporting throughout the engagement. We don’t just "set it and forget it"—we actively measure, report, and refine to make sure you’re seeing the returns you expect. From detailed model performance reports to campaign impact summaries, we make sure you have full visibility into how your investment is performing over time.

And if you clicked on that blog from Chris in the first section of this blog, you already understand that at Faraday, our ROI analysis doesn’t stop at a report card with a score to prove our value, it’s a whole additional element of building, testing, and refining our ongoing strategy. ROI is central to how we approach our strategy, and because we take it so seriously you can rest assured that you’ll never have to question just how much value you’re getting out of your investment.

At Faraday, you're paying for outcomes

At the end of the day, our pricing is shaped by what it takes to drive your success: how much data you're working with, how complex your goals are, and how much guidance you need. The more value we help you extract, the more efficient your spend becomes.

A few things that shape the cost:

• Lead volume: How many leads per month need to be scored or prioritized?
• Data complexity: Are we working with first-party data, third-party data, or both?
• Delivery destinations: Where should predictions go—CRMs, CDPs, direct mail, paid media?
• Support needs: How much ongoing guidance will make the engagement successful?

We have standard packages that fit most businesses, but we can customize engagements to make sure you're only paying for what you actually need.

We don’t believe in vague pricing or fuzzy math

If it feels like Faraday includes a lot, that's because it does. But we don’t hide it—we explain it. We'd rather have an honest conversation about value than play pricing games that sound good on paper but disappoint in reality.

You’re not just getting a tool. You’re getting a team, a strategy, and a system designed to drive real results—starting from day one. And when the right systems, models, and minds work together in sync? That’s where the magic—and the ROI—happens.