U.S.-based, AI-powered marketing and user-acquisition firm 23 Broadway is the new kid on the block and they’re shaking things up, writes Lauren Harrison.
Founded in 2024, the company has quickly attracted attention from all corners of the industry. And with good reason.
Offering a new approach to iGaming marketing, the company closes the loop by funding operators’ marketing efforts and reducing costs through real-time behavioural data that predicts player lifetime value, tying marketing to a revolutionary economic model of syncretic communications.
Intrigued? We certainly were, which is why iGamingFuture’s Curtis Roach invited 23 Broadway’s CEO and Co-Founder Jordan Tuch into the studio to unpack this newer, more integrated approach to marketing.
Jordan is part of the newer generation of tech entrepreneurs redefining the iGaming space.
His first company, Betty–a Canadian online casino start-up he co-founded in 2022–reached an estimated US$330 million (£260.7m) run rate in less than three-years, capturing 18 percent of Ontario’s hyper-competitive market.
We began by asking him:
As iGaming operators face increasing pressure on margins and rising acquisition costs, traditional user-acquisition models are potentially no longer fit-for-purpose. What fundamental shifts are now required?
“The traditional model–set a CPA target, buy traffic, hope the cohort performs–is broken for one simple reason: It treats every player the same at the point of acquisition.
“You’re paying the same price for a player who will generate US$2,000 (£1,580) in lifetime value as one who generates US$20 (£16).
“At scale, that’s not a margin problem; it’s a structural problem.
“The shift required is moving from backward-looking attribution to forward-looking prediction. Operators need to know the expected value of a player within hours of acquisition. Not weeks later when the cohort data comes in.
“That means investing in the data infrastructure and AI capability to generate those predictions in real-time, and then feeding them directly into bidding decisions.
“The second shift is capital. Performance marketing at scale requires consistent, significant capital deployment. And most operators are either undercapitalised or managing user-acquisition spend from working capital, which creates feast-and-famine cycles that destroy cohort quality.
“Operators need access to patient, performance-linked capital that scales with results, not with their balance sheet.”
23 Broadway sits at the intersection of capital, AI and performance marketing. How does bringing these elements together into a single model help operators overcome fragmentation and drive more efficient growth?
“Fragmentation is the core problem in many operator growth stacks. The data team builds models that the media team can’t use because it’s not built for their purpose.
“The media team buys traffic that the finance team can’t track. The finance team sets budgets based on last quarter’s results. None of these functions is talking to each other in real-time.
“23 Broadway’s model collapses that fragmentation into a single closed loop.
“Atlas generates player LTV predictions within hours of acquisition. Those predictions go directly to Google and Meta as bidding signals. So the ad platform is optimising towards predicted value, rather than clicks or registrations.
“The capital we deploy is tied to the same predictions. Every dollar we invest is underwritten by the same model that’s running the campaigns.
“The result is that capital, data and media are no longer three separate functions with three separate incentive structures. They’re one system with one objective: Acquire players whose expected value exceeds the cost of acquisition at the largest scale the data supports.”
One of the biggest challenges operators face is limited visibility of true player LTV at the point of acquisition. How does your approach–particularly through Atlas–change the way operators understand and act on customer value in real time?
“Most operators are making acquisition decisions based on signals that are weeks or months old. If, for example, a cohort from six-weeks-ago performed well, they increas the budget this week.
“That’s not data-driven marketing. That’s driving while looking in the rear-view mirror.
“Atlas changes the timeline. Within two hours of a player making their first deposit, the model generates a predicted LTV. That prediction is based on early behavioural signals–session patterns, deposit size and game selection–that are highly predictive of long-term value even when there’s almost no revenue history to work with.
“You also need infrastructure to send the results to ad platforms in the required formats, which is non-trivial to set up. We’ve built these custom data pipelines.
“The practical result is that we’re bidding more aggressively for high-value players and less aggressively for players who fit the demographic profile, but not the behavioural profile.
“That distinction–and the ability to act on it at the point of acquisition–is where the difference in return on ad spend between average and top operators is made.”
How do you see closed-loop systems between data, spend and return evolving? And what role will platforms like Atlas play in helping operators build more predictive, scalable and resilient growth strategies?
“The closed loop already exists – that’s what we’ve built.
“Atlas underwrites every acquisition decision in real-time against predicted LTV and CAC efficiency. A player is acquired; their behaviour generates data; that data produces a prediction, and the prediction determines the bid.
“The model is continuously learning from its outcomes and getting sharper. That’s not a future state. It’s how we operate today.
“What’s different about our version of the closed loop is that capital is part of it. Most operators think about data and spend as separate from their financing – the CFO manages the budget, the marketing team manages the bids and never the twain shall meet.
“We’ve collapsed that entirely. The capital we deploy is governed by the same unit economics that the model is optimising for.
“If the LTV/CAC ratio is strong, operators can scale without being constrained by their cash position. If it isn’t, we scale back. The capital follows the signal.
“That’s the part most operators are missing. Data and AI can tell you what to do. But if you’re cash-constrained you can’t act on it when the window is open. 23 Broadway removes that constraint.
“As long as the unit economics make sense, operators have access to the capital to move aggressively. The model and the money are finally speaking the same language.
“Looking further ahead, I think the operators who win will be the ones who treat acquisition capital as a dynamic, data-driven instrument rather than a fixed quarterly budget.
“That mental shift–from ‘how much can we afford to spend?’ to ‘what does the model say we should spend today?’–is where the structural performance gap between operators will emerge.”
Editor’s Note:
23 Broadway is targeting one of iGaming’s biggest challenges: Rising acquisition costs paired with limited visibility of player LTV.
In Jordan’s view, the current system is broken, with operators often overpaying for players who don’t stick around. And at scale, this is not a marginal loss; it is a structural problem.
But it’s a problem that now has a solution – one that closes the loop by combining capital, data and marketing into a single integrated model.
This is an interesting, potentially lower-risk, higher-reward approach that could prove to be a genuine game-changer. And not just for smaller brands or cash-strapped start-ups, but for operators across the wider iGaming sector.
If it lives up to its potential, this is the smart approach to acquisition spending and it could help rewrite one of the industry’s most persistent structural inefficiencies.
