What if retail data could speak directly to teams, answering questions as easily as a colleague might? In 2025, the retail industry faces mounting challenges with high return rates and sizing issues costing billions annually, and MySize Inc., a NASDAQ-listed leader in AI-powered solutions, has introduced NaizGPT, a conversational AI assistant that transforms complex analytics into simple dialogue. This groundbreaking tool, now in its pilot phase, lets e-commerce professionals interact with data through natural language, offering a glimpse into a future where insights are just a question away.
A New Era of Data Interaction in Retail
Retail analytics has often been a maze of dashboards and reports, leaving even seasoned professionals struggling to extract actionable insights. NaizGPT breaks this barrier by enabling users to ask questions like “Why are returns spiking in outerwear?” and receive detailed, conversational responses. Launched by MySize, this tool redefines how sizing and returns data are accessed, moving beyond static visuals to a dynamic, interactive experience.
The significance of this innovation cannot be overstated. With the retail sector under pressure to reduce losses—studies estimate returns alone cost U.S. retailers over $700 billion yearly—tools like NaizGPT offer a lifeline. By simplifying data interaction, it empowers teams to make faster, smarter decisions without needing advanced technical skills.
This shift aligns with a growing demand for intuitive technology in e-commerce. As companies strive to understand customer behavior in real time, NaizGPT’s pilot phase on the Naiz Fit platform is already showing promise, hinting at a broader transformation in how retail data is leveraged for success.
Why Conversational AI Matters in Retail Today
The retail landscape is evolving rapidly, with businesses grappling to turn raw data into competitive advantages. Traditional analytics tools often overwhelm users with charts and graphs, creating a gap between information and action. NaizGPT addresses this by allowing natural language queries, making data as approachable as a casual chat, and tackling critical issues like sizing mismatches that frustrate customers.
Industry trends point to a surge in AI adoption, with a 2025 report from Retail Dive indicating that 68% of retailers plan to invest in user-friendly tech to boost efficiency. NaizGPT fits squarely into this movement, offering a solution that doesn’t just present numbers but explains them. For instance, a pilot user discovered through a simple query that 30% of shoe returns stemmed from inconsistent sizing across brands—a finding that might have taken hours to uncover otherwise.
Beyond immediate insights, this conversational approach fosters a culture of curiosity within teams. Retail professionals can dig deeper into customer pain points without wading through endless reports, ensuring that strategies are informed by precise, real-time understanding. This capability marks a pivotal moment for the industry, where data becomes a partner rather than a puzzle.
How NaizGPT Redefines Retail Analytics
At its core, NaizGPT operates on a retail-specific large language model, designed to interpret nuanced questions and deliver context-rich answers. During testing on the Naiz Fit platform, users have posed queries such as “Which demographics return jeans most frequently?” and followed up with “What are the common reasons?” This iterative dialogue reveals trends and root causes that static dashboards often miss, providing clarity on complex issues.
Early results from the pilot phase are striking. Feedback shows a 75% increase in user engagement compared to traditional analytics tools, with teams appreciating the ability to explore data conversationally. A specific case highlighted a retailer identifying a 15% return rate on dresses due to length discrepancies—an insight that led to immediate product adjustments and reduced losses.
Looking ahead, MySize plans to expand NaizGPT’s scope beyond sizing and returns. Integration with Smart Catalog technology will soon enable insights into merchandising and inventory, creating a versatile tool for multiple retail functions. This evolution positions NaizGPT as a comprehensive ally, ready to adapt to the industry’s ever-changing demands.
Voices from the Frontline: Insights and Validation
MySize CEO Ronen Luzon encapsulates the tool’s potential, stating, “NaizGPT empowers teams to have real conversations with their data, uncovering the ‘why’ behind trends like high returns with unprecedented ease.” This perspective highlights a shift toward deeper analysis, where understanding drives decision-making rather than mere observation. Luzon’s vision underscores the transformative power of making analytics accessible to all.
Pilot users echo this sentiment, with one e-commerce manager noting, “Asking follow-up questions feels natural, almost like brainstorming with a teammate—it’s sparked ideas we wouldn’t have considered otherwise.” Such feedback validates NaizGPT’s design, showing how it encourages exploration and problem-solving in ways traditional tools cannot match. The enthusiasm from these early adopters suggests a strong foundation for broader adoption.
The impact is already measurable in pilot outcomes. Retail teams report faster identification of issues, such as a 20% drop in analysis time for return patterns, reinforcing NaizGPT’s credibility. This blend of executive insight and real-world experience paints a compelling picture of a tool poised to set a new standard in retail analytics.
Implementing NaizGPT: Practical Steps for Retail Teams
For retail professionals ready to embrace conversational AI, adopting NaizGPT begins with pinpointing current analytics challenges. Whether it’s unraveling high return rates or addressing sizing inconsistencies, teams should prepare targeted questions to maximize the tool’s dialogue-driven insights. This initial step ensures that interactions with NaizGPT yield focused, relevant answers from the outset.
Next, cultivating a team mindset open to interactive data exploration is crucial. Moving away from reliance on complex dashboards means embracing a simpler, question-based approach, which can reduce training time significantly. Retail managers might start by encouraging staff to think of data as a conversational resource, fostering confidence in using natural language to uncover trends.
Finally, staying attuned to MySize’s development timeline will be key. As NaizGPT rolls out commercially and integrates with broader technologies like Smart Catalog from 2025 to 2027, its applications will grow to support marketing and inventory decisions. Retail teams can position themselves for success by starting with small-scale trials and scaling efforts as the tool’s capabilities expand, ensuring a smooth transition to this innovative analytics paradigm.
Final Reflections
Reflecting on the journey of NaizGPT, it is clear that MySize has tapped into a critical need within the retail sector for more intuitive data tools. The pilot phase demonstrated remarkable potential, as teams engaged deeply with their data through conversation, uncovering insights that reshaped their strategies. This marked a turning point, where analytics became less about deciphering and more about dialogue.
Looking forward, retail professionals are encouraged to explore how conversational AI can fit into their workflows, starting with identifying key data challenges and preparing to ask the right questions. Staying updated on NaizGPT’s expanding features offers a chance to leverage its full potential across diverse functions. This proactive approach promises to keep businesses ahead in an industry where understanding customer needs swiftly is paramount.
