The operator's take on AI in marketing: move faster or get punished
Bill Lederer has lived through more than one tech cycle. His read on this one: it will move faster and punish hesitation.
Lederer is the chairman and CEO of MADTECH.AI, a St. Petersburg software company spun out of his services firm, iSOCRATES. He calls MADTECH.AI a marketing decision intelligence platform built to answer the questions most teams ask too late.
"In marketing analytics, there's the nice to know and there's the need to know," he said. "The need to know are things like, am I spending my money in the right areas to accomplish the goals that I'm seeking?"
Built by an operator, not a first-time founder
Lederer's track record spans 27 years in marketing, advertising and data-driven businesses. He's built and sold five companies. MADTECH.AI and iSOCRATES are numbers six and seven.
Earlier, he founded Art.com and sold it to Getty Images for a nine-figure valuation in 1999, then served in senior roles at WPP, Kantar and Getty Images. That experience shaped a core belief: waiting months to learn if something worked is not survivable.
He even crossed paths with Jeff Bezos in the late 1990s. The takeaway from that era stuck with him: he'd rather accept risk than look back with regret.
From services to software
iSOCRATES started as a professional services firm, billing by the hour to fix marketing and analytics problems. The same issues kept repeating: scattered data, late reporting, decisions made after the money was already spent.
"I thought it would be better and more useful if we made this a product instead of telling people, for hundreds of dollars an hour, I'll solve your analytic problem for you," Lederer said. MADTECH.AI is that product. It's a B2B SaaS platform that builds once and scales access.
The company was incorporated in December after Lederer came through the Tampa Bay Wave accelerator with little more than an idea. "I came here with PowerPoint and Excel," he said. Today, the team operates out of spARK Innovation Labs in St. Petersburg-its "global headquarters."
Solving the data problem first
Lederer argues the hardest part isn't insight-it's data you can actually use. "Most of the data tends to be disconnected," he said. "It's sitting in silos and very often it's heavily unusable."
MADTECH.AI built 300+ data connectors to pull from common marketing tools. The system cleans, maps and transforms that data before analysis, cutting a process that often takes 6 to 9 hours down to about three minutes.
"With AI, we are 90 days away from reducing three minutes to 30 seconds," he said. For customers, that means fewer data engineers and less dependency on specialized technical labor. The data pipeline can be purchased separately for about $2,000 per month and is included for decision intelligence subscribers.
What the platform delivers
Once data is unified, the platform runs hundreds of models and dashboards. The output is plain English, with forecasts and recommendations mapped to goals.
Users work with an AI assistant named Maddie, ask questions directly, and export results into presentations. The system works while campaigns are still running, predicting outcomes and suggesting changes across email, search, social and direct mail.
Example: shift an email send from 9 a.m. to 4 p.m. on Thursday, then retarget recipients with banner ads three times over seven days. It forecasts the lift and incremental cost before changes are made. The point isn't reporting-it's intervention.
Proven ROI at lower cost
Before MADTECH.AI was fully productized, one large marketer improved email performance by 10x within 90 days. "That system sold for $615,000," Lederer said. "Our system today sells for $60,000."
MADTECH.AI licenses its decision intelligence software at $60,000 per year. The company expects to add 45 to 60 customers this year. Advisors say the price is too low; he disagrees. "I want to democratize insights for marketers," he said. Lower pricing speeds adoption without forcing fundraising that dilutes control.
A substitute for labor
"We are a substitute for labor," Lederer said. He believes marketing is one of the first industries to automate decision-making because it's pattern-heavy and data-rich.
Most displacement comes from eliminating manual data engineering and consultant-driven analysis. Early-career roles are most exposed because much of that work is manual analysis and delayed reporting. He estimates that at least half of marketing jobs could disappear over the next decade as real-time systems replace slower workflows.
A familiar comparison
Lederer compares MADTECH.AI's role to Palantir, which provides decision intelligence to government and defense agencies. "They charge millions or tens of millions per customer," he said. "We're doing decision intelligence for marketing." One system serves national security; the other serves commercial decisions.
What comes next
He expects marketing decision intelligence to sit on top of the entire martech stack-a single brain that collects data, makes decisions and sends instructions to execution systems in real time. "Today, analytics are spread across dozens of platforms," he said. "The future is a unified brain."
He also expects consolidation. Larger platforms like Adobe or Salesforce will buy decision intelligence companies rather than let them remain independent.
The bubble, constraints and the filter that matters
Lederer calls the current moment a bubble. There's overcapitalization and valuations are too high. He also points to AI's resource intensity-energy and water-as pressure that will force a shakeout and tighter pricing across B2B software.
"There's only one thing that really matters," he said. "The business value that you deliver to your customer." For him, MADTECH.AI is about cutting waste before it becomes institutionalized. "Most marketing doesn't work most of the time. If you can learn faster and act faster, the savings can be dramatic."
What this means for marketers
- Speed is strategy. Insight after the spend is sunk cost.
- Unify data first. Model quality is capped by data quality and timeliness.
- Bias toward real-time intervention over post-mortem reporting.
- Measure lift and incremental cost before you change anything.
- Budget for platforms that replace manual data work; redeploy people to higher-value decisions and creative.
- Expect consolidation. Plan for a "single brain" to sit over your stack.
Practical next steps
- Audit your current data flow. How long from event to insight? If it's days or weeks, you're leaving money on the table.
- Start with one channel. Prove real-time optimization, then expand.
- Rewrite your reporting cadence. Replace monthly recaps with weekly (or daily) interventions.
- Upskill your team on AI-driven decisioning. If you need a fast path, see this AI certification for marketing specialists.
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