Analytics For Fashion Retail

Is it possible for technology to take over the creative finesse of the humans? May be not. But technology can at least complement human creativity with workable inputs that go a long way towards producing finer results. That is exactly what’s happening in the fashion retailing domain right now. Clever hunches, novel imaginations, and the “Big Data” are blended in a magic caldron called analytics for fashion; the resultant diet is equally delectable to fashionistas, fashion-challenged folks and, of course, apparel retailers.

The “Big Data” Revolution

From real-time data analysis to forecasting color and style combinations for the upcoming season to fix viable pricing strategies, analytics for fashion offers an omnibus of services to fashion retailers. The rationale for these sophisticated analytical tools is to extract the most popular attributes and highlight the not-so popular ones from a humongous data set. Assortments can also be fine-tuned for region-specific or geographical preferences; thus, clearing the decks for a precision-based design decisions. Authenticity of predictions by a market intelligence mechanism is subject to the merit and accessibility of raw data. In this regard, some of the issues that the industry confronts are:

• Collation of attribute-based data is not real-time and warrants herculean effort.
• Notwithstanding the application of analytics for fashion, designers have to count on their experience and acumen while okaying the right inspiration.
• Fashion is like a weather vane, it can change directions freely. There is no guarantee that a quirky trendsetter from the current season will rule the roost in the next season. It’s not easy to anticipate trends accurately.
• Non-availability of market data is a hindrance to gauge the success of new inspirations.
• Fashion retailers may be skeptical about season performance in terms of stock turnover, net margins, and price reductions.

Predictive and Real-Time Analytics To Understand Changing Customer Preferences

Fashion trends are fleeting affairs, always vulnerable to change. It’s an arduous task for retailers to keep pace with the caprices of the consumers who remain unmistakably well-informed about hippest styles and silhouettes through online and offline channels. Here, fashion retailers have to take two routes:

Utilize predictive insights provided by Big Data for next-season planning
Insights from Big Data are worth their weight in gold to streamline the supply chains, and can support the power of human intuition to predict next season trends. Millions of people through social media outlets like Facebook, Twitter, Pinterest, or Instagram are registering their resounding approval or thumping disapproval for a line of apparel. To tap these sentiments, haute couturiers are putting their best foot forward. They are launching new lines on Instagram, revealing behind-the-scenes images via Twitter, or starting microsites dedicated to fashion weeks. Tapping into this huge segment is herculean task, but comes with its own benefits.

Making the most of in-season data to optimize marketing and inventory decisions
In this volatile scenario, analytics and business intelligence are the most sought-after deadly duo to moderate operational inefficiencies, increase cost savings, quicken inventory turnover cycles, and enchant shoppers. Real-time in-season data collected through BI tools can provide deep insights into how your customers are behaving today and that will help you in quickly identifying the best plan of action for marketing, merchandising, and stock placements.

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