Powering Fashion Retail Consumer Insights with Advanced Retail Predictive Analytics
Increasingly, fashion retail organizations are challenged to stay trend focused, relevant, competitive, and most significantly, profitable in this very dynamic socioeconomic climate. Traditionally, before the latest technological advancements, the typical 12-18-month fashion apparel merchandising strategy season planning worked rather successfully. More predictable trend shifts such as color, silhouettes, fabric and weather shifts were typically accounted for in most merchandising planning and assortment systems. Essentially, the fashion houses and retail companies had the absolute advantage in setting trends and driving where the market was going. However, with the continuous evolution of the retail industry, along with the increase of socially empowered and mobile-connected customers, there are significantly more factors that the retail merchant must take into consideration to build, develop, drive and maintain brand loyalty & satisfaction.
The Age of Predictive Analytics – Knowing Your Customer
We have effectively entered into an age of advanced predictive analytics, where the retail executive is challenged to have a continuous and real-time 360-degree perspective of their consumers, across all possible physical and digital shopping channels, along with social influences. Additionally, the onset of the “Fast Fashion” revolution, has caused a significant disruption for more traditional fashion retail companies. They have redoubled their efforts to stay ahead of the changing fashion trends, driven primarily from social media outlets, crowdsourcing, as well as the need to increase the overall speed to market. More traditional fashion retailers such as Ralph Lauren, Macys and others are turning to advanced predictive business analytics to compete and thrive in the fast fashion environment, driven by Zara, H&M, Uniqlo and others. By effectively centralizing all of your consumer insights data, and translating these into visual and predictive tools that can drive merchandising solutions, you will have the ammunition at hand, to be far more proactive, vs. reactive to the changing industry trends.
Emerging Predictive Analytics Trends – 2016 and beyond
The following advanced predictive analytics trends have recently emerged, and will continue to evolve in 2016 and beyond as the demands for increased consumer insights grow for fashion retailers, to drive optimal assortments and tightened inventory management processes:
- What the age of Data Democratization really means?
- With knowledge comes great power: Retail organizations are discovering there is an increasing number business users who need to explore advanced predictive retail analytics
- With great power also comes great responsibility: Democratization of data requires a multi-tiered approach, to balance both data accessible and governance
- Moving to the Cloud = Empowering Advanced Retail Predictive Analytics
- Expandable Cloud Means Increased Scalability: Leveraging the cloud provides scalability, and once these data points are there, cloud analytics enables fashion apparel retail companies to be extremely agile
- Significant economic savings: With the costs of leveraging the cloud continuing to drop, this has stimulated the data cloud boom, as well as stimulated cloud-based data storage innovations for fashion apparel retail companies
- Everything is Mobile
- Mobile First Experience: Business intelligence products with a fluid, agile and scalable mobile-first experience have emerged is no longer simply an interface to legacy business intelligence solutions
- Single Version of the Truth: Since everyone is leveraging the same consolidated data, this will drive more efficient, accurate and timely decisions
- Our Brains Are Wired for Sight – Visual Analytics are on the Rise
- Data & Technology are an integral Part of the Conversation: Fashion retail executives are leveraging their data to explore questions, solve complex problems via insights, and requiring critical thought long-term strategies supported by data
- Visual analytics Will be the Unifying Language: Which empowers retail executives to reach consumer insights rapidly, enable meaningful cross-functional collaboration, and build a culture of “data” within the retail organization
Bringing it all together… The Rise of Self-Service Predictive Analytics
With the rapid pace and seemingly daily trend shifts in retail, It is evident that the continuous improvements, innovations, the rise predictive analytics, and most importantly, a self-service mobile first business intelligence strategies are not just emerging, rather, they are elevating fashion retailer executive’s decision-making capabilities to the next level. There are fascinating predictive analytics innovations, which enable far more confident decision making, to not an only forecast but to monitor analyze the near real-time data. By focusing more organizationally, advanced predictive solutions filter the data into personalized self-service dashboards, and visuals, resulting in faster decision making. As your fashion retail business grows into other categories, shopping channels, geographical regions, and potentially through acquisition, your cloud-based predictive analytics suite has to be, extensible, scalable, and flexible to meet these needs.
The ability to track and meet the ever changing needs of your evolving consumer is truly the holy grail for fashion retail companies. To stay on top of this innovation curve, and not only ride but control the fashion trend waves always has been a challenge for fashion retail executives. Fear not, there are enterprise business solutions out there which will meet and exceed your needs, and enable you to carry it with you wherever you go. In conclusion, there are no segregations between technology, data, and your fashion retail business. They are now synonymous, and those analytically cultured retail organizations will thrive in this ever complex, and evolving fashion marketplace.
Visionet Systems, Inc.