Technical growth strategy for prediction markets (and adjacent "pick'em" products), what's working, what's not, and what to do next

Most teams in prediction markets and adjacent pick'em products still behave as if they are selling a trading app to traders. The behaviour that matters most for growth is simpler. A large share of the audience wants a probability they can trust, without opening an account, depositing, or even thinking of it as a wager. They are using odds as a media product. That creates two funnels that look similar in the first session but diverge fast. Funnel one is odds-as-media, where the user is effectively reading and sharing the market like a live poll. Funnel two is odds-as-finance, where the user needs execution quality, confidence in price formation, and a clear understanding of costs. When you treat everyone as a trader, you build a deposit-first experience that suppresses the entire media funnel, which is the one with the widest distribution. Polymarket is the clearest proof that the media funnel exists at scale. Cumulative volume was roughly $73M by end of 2023, then about $9B in 2024, more than 100x growth, with more than $3.3B tied to a single Trump vs. Harris market. That does not happen just because a product has a good trade flow. It happens because the numbers became culturally useful, repeatably shareable, and legible to non users. If you want this to compound, the top of funnel cannot look like a brokerage landing page. Let people browse without signing in. Build pages that explain a market in one glance, then offer lightweight commitments that keep you in their week. Watchlists, alerts, and following a market are not secondary features. They are the primary conversion for the media audience. The practical decision is where you place friction. Put it at the point of real risk, not at the point of curiosity. Curiosity is your cheapest distribution channel in a category that otherwise gets expensive very quickly.

The most useful way to study Polymarket is not as a crypto app, but as an information product that got pulled into mainstream attention. The election was the catalyst, but the mechanism was credibility turning into habit. People checked markets because they believed the market was more accurate than commentary, then they shared it because a probability is a clean argument starter. There are three ingredients you can actually operationalise. First is resolved outcome storytelling. You do not need to claim you are always right, you need to show how the market processed information over time. The simplest format is a resolution recap that anchors on a timestamped probability and the final outcome. This creates trust compounding because it trains the user that prices move for reasons. Second is cultural piggybacking. A detail that matters here is Trump referencing Polymarket odds at a rally, calling it the "poly poll". That is earned distribution that teaches the product in one line, there is a number, it moves, and influential people watch it. You cannot manufacture that exact moment, but you can build the outputs that make it possible. Share cards that fit on social. Embeddable charts. Market titles that read like headlines. Third is explainability tested in the real world. Polymarket filmed an announcement video with an agency using roughly 10 to 12 actors plus crew, about 15 to 20 people total, and most did not know what Polymarket was until it was explained. Once it was framed as betting on what Trump might say, it clicked. Treat this as a creative methodology. If a random person cannot understand the product in 10 seconds, your paid social creative will bleed. If they can, you have a repeatable hook. The growth lesson is that distribution follows legibility. Election traffic was not just high intent, it was high context. Your job is to create context quickly, then give the user a reason to come back tomorrow.

In prediction markets, liquidity is not just a trading metric. It is the product quality the user feels in their first interaction, and product quality is what determines whether your paid acquisition ever becomes efficient. If the first trade has a bad fill or a wide spread, the user assumes the platform is either unfair or amateurish. That impression spreads faster than any referral program. Mechanically, these venues rely on professional market makers posting two sided quotes, functionally acting like the bookie. The detail that matters is that market makers have more influence when liquidity is thin, and less influence when participation is high. This is why concentrating attention on big moments works. When there is natural demand, spreads tighten, prices look more believable, and the act of trading feels clean. The numbers in Polymarket's recent history tell you where to concentrate. In September 2025, monthly volume sat in the $1.42B to $1.5B range depending on the snapshot, while sector wide volume in a comparable period was cited at $4.28B, implying Polymarket held roughly a third of the market. A single macro event, the September 2025 FOMC decision, cleared about $220.6M in volume. That is the kind of moment where you can acquire, activate, and retain, because the product experience will be at its best. The other structural shift is category mix. By 2025, sports markets represented more than 60% of Polymarket open interest, with more than $1B wagered on 2025 sports events. This is not just a content decision. Sports offers a calendar of recurring, predictable liquidity spikes. That makes marketing and product operations easier because you can plan around known weekends rather than random news. A common failure mode is acquiring users into illiquid long tail markets because they are easier to rank for or easier to create. That is backwards. Your launch calendar should mirror your liquidity calendar. If you cannot guarantee a good first trade experience, you are paying to create negative word of mouth.

This category is unusually sensitive to economic clarity because users constantly do mental maths. Even casual users intuitively understand that a small edge can vanish if the platform takes too much. One example is that a roughly 3% commission can turn a slightly better price into a worse bet. You do not need to over index on that specific number, you do need to accept the underlying truth. If fees feel hidden, users stop trusting the odds. There are two distinct problems to solve. The first is the absolute cost of trading. Traditional sportsbooks typically embed a 4 to 5% house edge in odds. Polymarket has positioned a future regulated exchange model at around 0.01% trading fees. Whether you can deliver that across jurisdictions is a strategic question, but from a growth point of view it defines your story. An exchange can win on fairness and price discovery, but only if users can actually feel that advantage. The second problem is comprehension. If fees are explained in financial jargon, people assume you are trying to hide something. The best practice is to quantify the impact right at the moment of decision. Show a simple example in the confirm screen, and make it obvious what the user receives if the outcome resolves in their favour. Do not bury it in a help centre. Polymarket's historical positioning as near frictionless trading, with monetisation likely captured indirectly via spread and liquidity provision, is a useful lesson for product marketers. If you earn through spread, you still need to educate users about spreads, because sophisticated users will compare execution. If you introduce explicit fees later, you must manage the narrative carefully so the platform does not feel like it changed the deal. In growth terms, fee transparency is not compliance work. It is conversion copy. It reduces buyer remorse, lowers support load, and makes it easier for people to recommend the product without caveats.

New users in prediction markets routinely make an avoidable mistake. They try to make markets by posting their own quotes, then get punished by adverse selection when new information arrives and smarter participants trade against their stale price. This is trading advice on the surface, but it is a growth problem underneath. If your early cohort loses money fast because you guided them into the wrong first behaviour, you will see churn, complaints, and reputational damage that paid acquisition cannot outrun. On chain analysis looked at roughly 1.7M unique addresses and found only about 30% were net profitable, while 70% were unprofitable. Realised profits totalled about $3.7B, and the distribution was extreme. Fewer than 0.04% of addresses captured more than 70% of profits. Most profitable addresses, about 63.5%, earned between $0 and $1,000 and collectively earned less than 1% of all profits. This tells you what your mainstream user experience will be. Most users are not going to become elite traders, and many will have a negative PnL over time. That does not mean the product cannot grow. It means your onboarding must reduce unnecessary losses. The safest first action for a beginner is to be a taker with clear pricing, small stake sizes, and guardrails. Your acquisition messaging should match that. Emphasise one tap buy Yes or No, getting the current price instantly, setting odds alerts, and following markets. Avoid campaigns that imply anyone can be a market maker or that posting lines is a fun mainstream feature. You can also design your first trade experience around moments where the market is thick. When liquidity is deep, fills are better and users feel less like they got fleeced. Combine this with transparent economics and you increase the chance that a user makes a second trade within a week, which is when habit starts. If you want long term retention, you have to accept that most users are not playing to win money. They are playing to be right, to hedge a view, or to participate in a conversation. Onboarding should respect that reality.

If you accept that odds-as-media is a real audience, you need a funnel that converts curiosity into a relationship before asking for a deposit. The simplest model is browse, follow, trade, then repeat at peak moments. The key is to measure each step like a media business as much as a financial product. Start with public market pages that load fast, rank, and are built for sharing. People should be able to view prices without signing in because a meaningful slice of future traders will arrive as anonymous browsers first. Treat share rate per visitor as a core KPI, and do not panic if many return visits never trade. Returning non traders are still distribution because they are the people screenshotting and arguing. Next, offer lightweight commitments that are easier than a deposit. Watchlists, odds alerts via email or push, and a simple follow feed that keeps a user anchored to a small set of markets. The aim is to turn a one off visit into an addressable audience. Measure browse to follow conversion, and measure the number of followed markets per user, because too many followed markets becomes noise and too few reduces return frequency. Only then should you push the first trade, and you should time it. Trigger it when markets move and liquidity is naturally higher. This is also where fee transparency belongs, directly on the trade confirmation screen, because it reduces drop off from second guessing. If you do this well, your retention will be driven by moments, elections, rate decisions, playoff games, not by generic weekly nurture. Polymarket's scale shows the upside of getting this right. DeFiLlama shows lifetime DEX volume around $15.728B and 30 day volume snapshots around $1.049B, with 24 hour volume around $31.95M at one point in time. You do not reach that kind of activity by treating every visitor as a conversion opportunity on day one. You reach it by building habit loops around markets that people already care about. The most important mindset shift is that your top of funnel is a newsroom with a price feed, and your mid funnel is a subscription product built from alerts and follows.

Regulation is not just a legal constraint in this category, it is a marketing constraint that determines what can go viral and how you are allowed to frame it. For CFTC regulated event contracts, the perimeter excludes terrorism, assassination, war, gaming, or anything unlawful under state or federal law. That immediately shapes your market taxonomy. Some of the most meme friendly topics are simply off limits. This pushes you towards a different kind of brand advantage. Legitimacy becomes a product feature. If you cannot rely on shock value markets, you win by being the venue people trust for information discovery and risk transfer. It also changes your channel strategy. Partnerships that embed your odds as data can outscale many consumer channels because they sidestep the need to sell the act of trading directly. Polymarket's partnership with Intercontinental Exchange is the most important example. ICE invested $2B in October 2025, valuing Polymarket at $9B post money, and is distributing Polymarket data as a commercial product. That turns odds into a feed that can appear inside institutional terminals and broadcaster graphics. From a growth point of view, that is syndication as acquisition. It is the same playbook that made financial indices and polling aggregates powerful, but with live market pricing. On the regulated side, Kalshi's sports pivot shows how taxonomy choices change the business overnight. It surpassed $1B in monthly volume in mid September 2025, with 98% of that flow being sports related. Sports is not just popular, it is defensible within a regulatory framework and it provides a constant drumbeat of events. The NHL licensing deal in October 2025, granting official data access and in broadcast advertising rights tied to prediction markets, is another sign of where distribution is heading. If you can be present in broadcast moments, you acquire users when context is highest. Creatively, you must be careful with gambling framing where it is disallowed or risky. Emphasise probabilities, hedging, and information discovery. You cannot out meme your regulatory perimeter. You have to build virality inside it.

The category is moving from novelty to infrastructure, and that changes what winning growth looks like. Early growth was driven by headline events and social sharing. The next phase is about becoming the default probability layer for sports, politics, and macro, distributed through feeds as much as through apps. Polymarket's metrics hint at this transition. By late August 2025, YTD volume was already over $7.7B, suggesting the post election drop off did not end the habit. Open interest hit records around November 2024, dipped, then rebounded into Q3 2025 towards those highs. Sports becoming more than 60% of open interest tells you where daily usage will come from, while moments like the $220.6M FOMC market show that macro can still produce spikes that pull in new cohorts. However, there is an uncomfortable truth most teams avoid. The profit distribution shows that a tiny elite extracts most of the gains, while the majority lose or win small. If the industry keeps marketing like a get rich product, it will attract the wrong users, trigger regulatory scrutiny, and churn faster than it can acquire. The only sustainable mass market positioning is that these are probability products that sometimes pay out, not payment products that sometimes predict. Adjacent pick'em and DFS products will keep competing on promos, creator partnerships, and sports calendars. Prediction markets will win where they can offer better economics and better information. The claimed delta between a 4 to 5% sportsbook edge and a 0.01% exchange fee is the strategic wedge, but only if the execution quality feels better and the fee story is clean. My controversial view is that the next big moat will not be a better referral program or a clever meme. It will be distribution rights for the odds themselves. If your prices are embedded in broadcasts, terminals, and major platforms through data deals, your app becomes the place people go after they already trust the number. In that world, paid social becomes a rounding error, and the companies that focused early on odds-as-media will look obvious in hindsight.