Beyond Black Friday: How I’m targeting "Evergreen" Search Intent to grow a data-heavy consumer tool

Hey Indie Hackers 👋,

When you build a price-tracking tool like PriceProven, the obvious growth spikes are Black Friday and Amazon Prime Day. But relying solely on seasonal hype is a trap.

Coming from a background of building automated trading bots, I’m used to systems that run 24/7 based on raw, high-frequency data. I want PriceProven to have that same everyday utility—not just be a holiday novelty.

So, I’m shifting my focus to an "evergreen" SEO strategy, specifically targeting pre-purchase search intent.

Instead of just waiting for sale events, I’m mapping out the everyday questions shoppers ask before hitting "checkout":

• "Is this discount real?"

• "Current price vs. historical low for [Product X]"

• "Has this price been artificially inflated?"

The goal is to capture users when they have high intent but are facing weak, marketing-heavy search results.

Once they land on PriceProven, they don't get fluff. They get exactly what I'd want to see: a terminal-style, high-density data dashboard. No unnecessary empty space. Just the raw historical price curve, confidence metrics, and if we don't have enough history to verify the discount, the system explicitly throws a "Not Enough Data" flag. Absolute transparency.

My question for the community: For those of you building data-heavy platforms, have you experimented with Programmatic SEO to generate pages based on your datasets? How do you balance indexing millions of product data points without tanking your crawl budget?

Would love to hear your experiences and strategies!