How We Think About Pricing AI-First Products at Endless Blog

AI products create asymmetric value. A few GPU cycles can produce outsized outcomes—reach, leads, time, accuracy, leverage. When the spread between cost and outcome is this wide, traditional SaaS pricing breaks down. That’s why we’ve moved EndlessBlog toward a value-based model. It reflects how customers actually experience the product.

Most of the industry is running into the same wall. Analysts keep pointing to one pattern: AI pilots fail when teams can’t articulate or price the value.

Peter Bendor-Samuel put it plainly in Forbes earlier this year:

“More than 60% of AI pilots fail to reach production because providers can’t clearly link pricing to delivered business value.”
(Forbes, 2024)

That’s the problem we’re avoiding.

Why the old models don’t map to AI

Cost-plus anchors price to compute. Compute gets cheaper every year. Your impact doesn’t.

Competitor pricing assumes the market knows what it's doing. It doesn’t. Bain & Company’s 2024 analysis basically called it out directly:

“The single biggest pricing error in AI is cost-based anchoring.”
(Bain Insights, 2024)

Gartner went further:

Vendors using traditional software metrics “miss up to 80% of their obtainable revenue.”
(Gartner, 2024)

If you sell outcomes but price inputs, you build the wrong business.

What value looks like for us

Founders aren’t buying post scheduling or LLM copy. They’re buying:

• staying visible

• predictable inbound

• compounding reach

• time returned to them

Our pricing has to map to that. If someone gets 5 ready-to-approve blogs every Monday, publishes in minutes, and that visibility produces a few deals a month, the ROI is clear. Pricing based on our server bill would undermine the product.

McKinsey’s 2023 AI value report reinforced this exact point:

“AI value realization depends less on algorithmic performance and more on how providers capture and communicate measurable impact.”
(McKinsey Digital, 2023)

That’s what we’re aligning with.

The structure behind our approach

We center pricing around three things:

1. The core metric that matters.
   For our users, it’s weekly output, reach, and inbound momentum—not tokens or seats.

2. The before/after.
   How long content took. How often they posted. What consistency unlocked.
   Deloitte found that value-linked metrics alone improved renewals by 25% or more.
   (Deloitte, 2023)

3. Tiers based on outcomes, not features.
   The tier should reflect what you’re trying to achieve, not what button you can click.
   This mirrors what’s working across the industry—UiPath anchoring pricing to workflow savings, Adobe Firefly shifting from credits to deliverables, Salesforce tying enterprise pricing to revenue and forecasting gains.

The logic is simple: if the goal is an outcome, the price should mirror the outcome.

Why value alignment matters long-term

When pricing is tied to impact, you get two advantages:

• clearer expectations and cleaner relationships with customers

• better internal focus—improving the outcome, not inflating the feature list

Accenture quantified this: value-linked pricing nearly doubles the likelihood that an AI project continues beyond pilot.
(Accenture, 2024)

It also shows up in macro data. The Federal Reserve Bank of San Francisco reported that firms using value-based or AI-driven pricing grow faster in both sales and assets.
(San Francisco Fed, 2024)

Pricing isn’t a cost calculation. It’s a strategic lever.

The direction we’re moving

EndlessBlog—and the broader Endless ecosystem—will keep aligning pricing with delivered impact. EndlessBlog helps you surface as the expert AI models recommend. EndlessStartups helps you find deals without sifting through noise. EndlessBlog drives consistent visibility and inbound. All of it comes back to outcomes, not inputs.

Harvard Business Review summed it up well earlier this year:

“Value-based pricing isn’t a premium strategy—it’s a survival strategy in the age of intelligent automation.”
(HBR, 2024)

That’s the frame we’re operating from. If we deliver more value tomorrow than we do today, pricing should follow that arc. If we fail to deliver the value, no pricing model will save us.

In short: we’re pricing EndlessBlog the way AI products should be priced—anchored to the real-world results they create, not the cost of running the servers.