Latest news with #zeroPartyData
Fast Company
15 hours ago
- Business
- Fast Company
Zero-party data goldmines: Post-cookie personalization tactics driving the highest ROAS
Marketers spent years chasing third-party cookies, but that well seems to have run dry. Browser blocks, data laws, and platform walled gardens have pushed cookies to near extinction. Top brands, however, aren't looking back. Rather, they're tapping into zero-party data: insights customers willingly share in exchange for value. Unlike data inferred or bought, zero-party data reflects real intent and trust. This editorial explores how leading advertisers are using it to power personalization and achieve record-breaking ROAS. The downfall of third-party cookies did more than break retargeting; it shattered a decades-long mindset that customer data was something to be harvested rather than earned. After years of being conditioned by data-breach headlines and a patchwork of privacy prompts, today's consumers are acutely aware of their digital footprint. They still crave relevance, but not at the cost of control. That tension has repositioned the brand–customer relationship around value exchange. When a sportswear retailer offers personalized training plans in return for a shopper's workout preferences, both parties win: The brand gains insight it could never infer accurately from clicks alone, and the customer receives a tangible benefit for sharing. The key shift is intentionality. Because zero-party data is offered knowingly, it carries far richer context and sentiment than behavioural breadcrumbs ever could. Marketers who respect that intent—by explaining how information will be used and delivering prompt, meaningful pay-offs—build what algorithmic shortcuts never could: durable trust. That trust, in turn, lowers acquisition costs, lifts lifetime value, and fuels the kind of ROAS metrics boards like to parade in earnings calls. Consumers don't share preferences in blank fields—they do it while engaging with quizzes, calculators, or chatbots. These tools entertain while capturing declared data that far outperforms third-party cookies. Beauty brands use shade-match quizzes; retailers use conversational chatbots to uncover style, budget, and timing. Integrated with CRM and ad platforms, these insights power highly personalized retargeting, cutting wasted impressions and driving ROAS beyond pre-cookie levels. Early versions of preference centers were forgettable footnotes in email footers, visited only by those on the brink of unsubscribing. These days, they have evolved into living dashboards where customers actively sculpt the brand relationship. Users can toggle communication channels, update sizing details, flag changing dietary needs, or signal upcoming life events—think: 'Expecting a baby in November' or 'Relocating to Toronto next month.' Each adjustment rolls downstream into campaign logic, product feeds, and service workflows. The result is a self-healing database in which data decays less because it is customer-maintained. Crucially, modern preference centers are wrapped in engaging interfaces: mobile-first layouts, gamified progress bars, and immediate gratification in the form of tailored content once changes are saved. Some brands even surface machine-learning suggestions ('People with similar goals loved our new plant-based protein range—interested?'), turning the dashboard into a two-way street of insight and offer. By empowering customers to fine-tune the data you hold about them, you simultaneously deepen accuracy and boost opt-in rates, driving higher open rates, stronger click-through and, ultimately, ROAS metrics that outperform batch-and-blast tactics by a comfortable margin. Collecting explicit data is one half of the equation; activating it at scale is the other. Modern marketing clouds combine zero-party inputs with machine-learning models to create microsegments so granular they border on one-to-one. A gardening retailer, for example, might identify 'urban balcony growers concerned about pollinators' as a distinct cohort after analyzing quiz answers, preference-center flags, and past purchase history. Creative automation systems then spin out ad variants—copy, imagery, offer laddering—matched to that microsegment's motivations. Because the seed data was permissioned and precise, the algorithm starts from a higher baseline of relevance, requiring fewer impressions to achieve lift. Beyond segmentation, AI models mine zero-party datasets for latent patterns: Customers who select 'weekend warrior' in a fitness quiz are statistically more responsive to Sunday evening push notifications, while those self-identifying as novice investors prefer plain-language copy over jargon. Feeding such insights into campaign cadences and content libraries lowers cost per acquisition and swells average order value. Brands deploying these predictive workflows report ROAS gains that would have seemed fanciful back when pixel-tracking was considered advanced. A common misconception is that zero-party data benefits only owned channels such as email and mobile apps. In truth, its impact reverberates across the entire funnel, including paid media that still competes for auction-priced real estate. Platforms like Google's new Privacy Sandbox APIs and retail media networks now accept hashed audience attributes derived from explicit user consent. Importing a preference for vegan skincare into those ecosystems allows marketers to suppress irrelevant impressions and bid more aggressively where fit is perfect, stretching budgets further. On-site visitors who completed a style-finder quiz experience dynamically reordered product grids and chat prompts tailored to declared tastes, shortening the path to purchase. In-app messaging, SMS nudges, and even connected-TV ad sequencing pull from the same unified profile, ensuring continuity that consumers interpret as respect rather than stalking. Measurement teams close the loop by attributing revenue back to the original zero-party signal, proving its causal role in conversion uplift. Across brands piloting such orchestration, efficiency metrics paint a consistent picture: fewer touchpoints to sale, slimmer frequency caps, and a ROAS curve that climbs quarter after quarter—even as ad costs inflate and cookie work-arounds fizzle out.
Entrepreneur
08-07-2025
- Business
- Entrepreneur
Rwazi Launches Sena, An AI Copilot Turning Insight into Instant Action
They're all exceptional individuals who think far beyond the box, challenge every assumption, and have turned vision into reality. Sena is their work at its finest. You're reading Entrepreneur United Kingdom, an international franchise of Entrepreneur Media. Rwazi, a global AI platform known for helping brands grow through zero-party consumer data, has announced the launch of Sena. This AI copilot was built to improve how enterprise teams interact with and act on data. It was designed as the next evolution in the company's mission to ensure clarity and accelerate action. Sena introduces a fresh way to interact with business data by allowing users to "talk" directly to it. If traditional analytics tools require predefined dashboards, SQL queries, or manual report generation, Sena responds to plain language prompts instantly. Teams can ask anything, from analyzing audience segments to comparing market trends, and get immediate insights. Besides speed and accessibility, Sena stands out for its intelligence. Layered on top of Rwazi's vast universe of real-time, zero-party consumer data, it understands context at scale. This capability means every answer isn't a surface-level metric but a tailored recommendation illustrating what's happening in the market, what matters most to the business, and where the clearest opportunities lie. In addition to interpreting the "what," Sena excels at decoding the "why." It connects patterns in consumer behavior to tangible business drivers, helping users understand what trends are emerging, why they matter, and how to respond. Sena was also built to slot seamlessly into existing workflows. Integrated with Rwazi's Consumer Insights module, it brings natural language exploration into daily operations without disruptions. Users can ask Sena to identify gaps in product lines, surface demand signals across key demographics, or simulate tactical actions to retain market share while working within the systems they already use. Sena will improve further in time and integrate with external tools such as reporting platforms and communications channels, enabling it to both recommend and execute. "We started Rwazi to fix an issue faced by enterprise teams everywhere, which is making critical decisions without hearing directly from the people who matter most: the consumers," says Rwazi co-founder and CEO Joseph Rutakangwa. "With Sena, we've built a partner that helps teams turn insight into action. It doesn't just interpret data. It acts with it, for you." Joseph Rutakangwa (CEO) and Eric Sewankamo (COO) The launch of Sena represents a significant moment in Rwazi's evolution. The company began by addressing questions for global brands, such as "What's going on?" Through AI-driven, zero-party data capture, Rwazi delivered accurate, real-time intelligence from actual consumers at scale and with global reach. This enabled early profitability and helped brands anchor decisions in real behavior instead of assumptions or third-party guesswork. However, customers' questions matured as they did, driven by the need to know what everything meant. Rwazi then built a custom infrastructure, processing billions of data points across voice, text, image, and video formats, to produce deeper meaning and context. This next phase catalyzed a wave of growth. The inevitable third question emerged from there: "What should we do about it?" That led to Lumora's development. Lumora, Rwazi's contextual AI engine, delivers high-level strategic recommendations based on market dynamics, competitor behavior, and internal business conditions. It has helped marketing, sales, and product innovation teams identify areas of opportunity and stress-test strategies before taking action. However, even with strategic guidance, execution was a challenge. Teams still needed to translate strategy into specific, timely actions. Sena was built to answer the final and most urgent question: "How do I actually do this?" "Sena guides users through every step of execution, step by step, prompt by prompt," Rutakangwa states. "Whether optimizing ad spend to attract Gen Z streamers or adjusting product positioning based on shifting price sensitivities, it can help teams act faster and more confidently." Sena's impact extends beyond a single use case. By compressing the cycle from data to decision and then to deployment, enterprises can unlock competitive advantage at scale in industries where every delay translates into a missed opportunity. With Sena, Rwazi completes a multi-year journey of product evolution that mirrors the natural arc of how modern organizations mature in their use of data. "I'm endlessly grateful to our team," says Rutakangwa. "They're all exceptional individuals who think far beyond the box, challenge every assumption, and have turned vision into reality. Sena is their work at its finest."
