Key Takeaways:
- It’s not enough to identify a trend–it requires AI-powered trend attribution of your product catalog to capitalize on consumer demand earlier in the trend cycle.
- As opposed to trend prediction and demand forecasting for next year or next season, trend attribution makes current trends actionable today.
- With Lily AI’s product attribution, retailers and brands can instantly curate collections and launch promotions faster to capitalize on trend cycles sooner.
At Lily AI, we know that different consumers shop differently. Whether casually browsing or ready to buy, they’re shopping with a preference or need in mind. This can often be by occasion, activity, style, fit, feature, or trend.
Of these categories, trends can be the most difficult for retailers and brands to act on quickly.
That’s not because retailers and brands aren’t in the know about the latest trends. It’s because some trends, like “fads”, surge and peak so quickly that it’s difficult operationally to keep up. Sometimes, products are attributed with relevant trends during item setup, but the trend data isn’t continually refreshed and becomes out of date. The worst case scenario is that trend attributes are ignored or missed entirely.
Let’s explore the different trend cycles, and see how AI-powered product attribution can help retailers and brands turn trends into more revenue.
Understanding Fashion, Home and Beauty Trend Cycles
When a customer purchases and wears a certain style or buys a product based on a trend, that style is then considered “accepted.” However, social media has changed the trends landscape to the point where many fashion and beauty trends DO NOT always survive and have a literal shelf-life.
Lily AI, the product attributes platform, identifies three types of trends: Fads, Mainstream, and Classic.
Fads:
- Essentially “a craze” – i.e., trends that only last for 1 month or season.
- Typically inspired by social media influencers, celebrities, and even designers.
- Trends that may not appeal to the average consumer.
- May include novelty items or unconventional, statement pieces.
Mainstream:
- “Ordinary” clothes that most consumers may wear for multiple seasons.
- Nothing too outlandish or extreme.
- Conventional, trendy, and relevant.
Classic:
- Classic trends last for several seasons – and sometimes years – to come.
- Timeless, ceases to go out of style.
- Sustainability and quality are key indicators.
How does the home cycle differ from the fashion cycle?
In general, home items are costly to produce in comparison to fashion or beauty items. Subsequently, the home trend cycle moves much slower. Decor and soft furnishings (pillows, sheets, towels, etc.) are the first items to be adopted. Unlike hard furnishings, they can be easily swapped out.
Capitalizing on Trends Faster
How do you curate a trend-based collection or campaign on the fly?
By enriching the entire product catalog with more robust attribution data that includes trends. With these trend attributes ready to go, e-commerce and merchandising teams can quickly and easily build trend-based thematic collections and landing pages. Marketers can then take these collections a step further by integrating them into campaigns and promotions.
For the hottest trends, Lily AI automatically provides trend attributes. Need something more custom? Our team of domain experts can work with our clients to define and apply a custom style or trend tag to their catalog.
By creating collections and campaigns faster, retailers and brands can capitalize on trends earlier, maximizing the revenue potential for every trend. The best part is that your customers will love being able to easily shop the latest trends, especially Gen Z and millennial shoppers that follow social-media inspired microtrends.
Learn more about the many benefits of AI-powered product attribution and how it can transform your business, elevate the customer experience, and maximize revenue.
