Becausal is a causal AI-powered audience intelligence and measurement company redefining how brands understand consumer behavior and measure marketing impact. Built on privacy-first principles, transparent data practices, and auditable measurement, Becausal helps brands, retailers, agencies, and CPG companies move beyond black-box predictive models to better understand the drivers of consumer purchase behavior and real-world sales lift. Using deterministic purchase-signal data, causal inference modeling, and transparent data provenance, Becausal delivers actionable, accountable insights designed to help organizations measure and understand what influences consumer decisions, setting a new standard for ethical, explainable, and high-performance audience intelligence. Pulse 2.0 interviewed Becausal CEO Avi Chai Outmezguine to learn more.
Avi Chai Outmezguine’s Background
Could you tell me more about your background? Outmezguine’s background
“I’ve spent most of my career building companies at the intersection of data, technology, and consumer behavior. Before Becausal, I led Scanbuy, where we helped global brands like PepsiCo, Mondelez, and Conagra use QR codes and digital packaging to connect with consumers. That experience taught me two big lessons: data is incredibly powerful, and it must be handled with transparency and purpose.”
“Becausal grew out of that belief: quality data should explain why things work, not just who clicked.”
Formation Of The Company
How did the idea for the company come together? Outmezguine shared:
“Advertising became driven by opaque black-box systems. Brands were spending more but understanding less. We saw a gap: there was no easy way to connect real purchase behavior with causal, explainable insights that marketers could trust. So, we built Becausal to do exactly that, combining multi-source CPG purchase data with causal AI and strong data provenance.”
“Our mission is simple: Make data trustworthy, auditable, and measurably useful.”
Favorite Memory
What has been your favorite memory working for the company so far? Outmezguine reflected:
“The moment we could mathematically prove why customer behavior occurred, not just what happened. That’s when we knew causal AI could make marketing smarter, more efficient, and more honest. That was the moment our vision turned into reality.”
Core Products
What are the company’s core products and features? Outmezguine explained:
“Our platform focuses on three pillars:
– Multi-source CPG purchase data — receipts, loyalty, and app-based signals with national coverage.
– Causal AI & transparency tools — showing not just who is targeted, but why and what changed.
– The Becausal Data Store — a self-service environment where agencies, brands, and platforms explore audiences, understand provenance, and activate campaigns.
Everything we do ties back to trust, performance, and explainability.”
Challenges Faced
Have you faced any challenges recently? How did you overcome them? Outmezguine acknowledged:
“The biggest challenge is cultural: the industry has gotten used to “black box” convenience.”
“We’ve overcome that by proving that transparency doesn’t slow performance; it improves it. Once brands see fewer wasted impressions and cleaner compliance conversations, they don’t go back.”
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Outmezguine noted:
“We started with raw data curation. Today we’ve layered on:
– Advanced taxonomy covering 800K+ SKUs and 600+ categories
– Causal modeling frameworks
– Retailer attribution and enrichment
– A scalable Data Store experience for partners
In short, we evolved from “data supplier” to “decision intelligence partner.”
Significant Milestones
What have been some of the company’s most significant milestones? Outmezguine cited:
– Launching the Becausal brand and platform
– Securing partnerships with global platforms and CPG brands
– Completing rigorous due diligence reviews with leading industry partners
– Deploying our Data Store MVP across pilot users
“Each milestone validated a different piece of the strategy.
“Next up, we’re focused on three milestones that matter just as much:
– Full Data Store commercialization
– Expanding multi-year strategic partnerships
– Publishing measurable causal-lift results with brands”
“Those are the inflection points that turn Becausal from ‘promising’ into ‘essential.'”
Customer Success Stories
Can you share any customer success stories? Outmezguine highlighted:
“A great example is our work with Kellanova, the global CPG company behind brands like Pringles, Pop-Tarts, and Eggo. Kellanova was evaluating purchase-based data partners to help them understand how real shoppers behave, not just who bought something in the past.”
“With Becausal’s multi-source purchase data, their analytics team was able to build more nuanced audience segments — for example, identifying shoppers who commonly switch between brands or have purchase patterns indicating real consideration rather than random exposure. This lets them avoid spending media dollars on consumers unlikely to convert and instead focus on those segments with higher potential impact.”
“That shift, from broad, historical buckets to behaviorally grounded, purchase-informed audiences, helped Kellanova operate more efficiently and get closer to causal understanding of what drives customer behavior. It’s the kind of insight that turns data from a reporting exercise into a strategic advantage.”
Funding/Revenue
Are you able to discuss funding and/or revenue metrics? Outmezguine revealed:
“We operate on a disciplined growth model. We focus on recurring revenue, strong unit economics, and sustainability. While we don’t disclose exact figures publicly, we’re expanding across agencies, platforms, and strategic brand partnerships, and we’re building toward profitable scale.”
Total Addressable Market (TAM)
What total addressable market (TAM) is the company pursuing? Outmezguine assessed:
“We operate at the intersection of retail media, data licensing, and AI-driven audience intelligence, categories that collectively represent trillions of dollars in global marketing and commerce influence.”
“But the more important truth is this: the market is still early in its shift toward causality, transparency, and privacy-safe data. Most tools still explain what happened. Very few explain why or can prove it in an auditable way.”
“That is the part of the market we are building for. As regulation, accountability, and performance pressure grow, the demand for causal, transparent data will only accelerate. We’re simply designing for that future today.”
Differentiation From The Competition
What differentiates the company from its competition? Outmezguine affirmed:
“Three things:
– Transparency by design — provenance, explainability, and auditability.
– Causal AI — we model why outcomes change, not just correlation.
– Multi-source data depth — breadth, retailer mapping, and rigorous taxonomy.
We believe the future belongs to companies that make data understandable and accountable.”
Future Company Goals
What are some of the company’s future goals? Outmezguine emphasized:
“Our goal is to become the trusted backbone for causal, transparent consumer intelligence, powering agencies, retail media networks, and brands. We’re expanding the Data Store, deepening key partnerships, and continuing to invest in responsible AI.”
Additional Thoughts
Any other topics you’d like to discuss? Outmezguine concluded:
“Advertising funds the internet. It shapes culture. It should also be ethical.”
“Becausal exists because we believe innovation and integrity shouldn’t be mutually exclusive. As we prove that transparent, causal data performs better, not just theoretically, but in-market, then the industry will shift on its own.”
“That’s the mission: make data both more effective and more honest. And that’s the future we’re building toward every day.”
