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Trendalytics Releases Tool to Help Predict Trend Curves a Year in Advance

The days of relying on gut instincts and last year’s sales data to predict fashion trends may be in the past for retailers.

Product intelligence data solutions company Trendalytics this week announced the launch of a new trend forecasting tool, giving retailers a technology-powered crystal ball for predicting future standout styles.

According to the company, the new platform will build upon Trendalytics’ existing cache of industry data and consumer signals to provide a “definitive forecast” for the trajectory of a given trend. In a statement, the company claimed its tool would allow users to create a detailed prognosis for a trend’s journey, up to a year in advance of it hitting its stride.

Trendalytics’ standard product intelligence engine decodes retail industry data through machine learning and image recognition, as well as analyzing online product searches, social media buzz and consumer shopping patterns.

The Trend Forecast solution has the capacity to identify and analyze the state of a current trend, while taking into account its history in the market and placing it in the context of similar trends. From there, the program calculates a predictive trend curve, indicating whether a particular fashion moment is expected to blossom, plateau or decline over the coming year.

“Our goal at Trendalytics is to empower users to make decisions based on as much valuable information as possible, and the new Trend Forecast tool delivers a new level of confidence to this information,” Kathy Leake, CEO of Trendalytics, said.

“We are moving beyond the vague assumptions of traditional trend forecasting to provide definitive information grounded in troves of past retail performance data,” she added.

The tool aims to empower retailers to make more detailed and accurate projections for their businesses, Leake noted, by augmenting their expertise with tested algorithms.

In November of last year, Trendalytics updated another retailing tool, TrendPulse, to include augmented predictive analytics capabilities. At the time, the company said the improved service would help merchants and buying teams by offering in-depth data analysis to help them decide how much product to purchase, and when.

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