Signal Analytics Now Offers Data Analysis of Over 1.8 Million Products for Apparel Businesses

For retail businesses that struggled to hit their revenue goals last year, the answer to their problems could lie in the data. As fashion companies try to identify new opportunity areas and correct the errors of 2020, Signal Analytics has expanded its marketing insights platform to serve the apparel market and try to encourage a pandemic rebound.

Signal Analytics collects data from over 13,000 external sources, ranging from social media platforms like Instagram to online marketplaces like Amazon, to department stores like Nordstrom. This information around consumer purchasing behaviors is then used to generate insights for the apparel industry, on both an industry-wide and an individual retailer level. The platform believes these insights will equip companies with the understanding to generate more relevant strategies for today’s landscape.

“Signals Analytics collects and contextualizes thousands of consumer, shopper and market insights to guide timely, business-critical decision making from concept to commerce,” said Kate DuBois, general manager of market intelligence at Kenshoo, parents company of Signals Analytics. “These insights are often used to support a number of use cases as brands go-to-market, including identifying consumer met and unmet needs; surfacing trends within and across categories; and identifying the right product mix for success.”

Specifically, the platform’s apparel market overview has amassed data from 1.8 million products, 12.9 million consumer discussions, 13 million reviews, 20,400 key opinion leader posts and 89,800 patents. This scale can help support smaller companies who don’t have that volume of data internally and who therefore may be limited in what analysis they can run.

Users of Signal Analytics can then engage with this information in one of three ways: off-the-shelf playbooks on the market as a whole or individual categories; customized solutions, which can take into account specific geographies or other needs; or as a data integration for a brand’s existing intelligence solutions. Even companies with a developed data management program may want to support this with the additional data points within the Signal Analytics system.

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Smaller brands can gain access to much larger volumes of data by utilizing a third-party solution.

“[Brands today] have likely invested in tools like Nielsen or IRI to access point-of-sale data; maybe they host research panels or use a social listening tool to understand consumer discussions,” said DuBois. “However, these data sets are often fragmented, sit in silos throughout the organization and only give users a view into one channel – not the holistic picture. Getting the complete picture can improve the accuracy of decision-making across your go-to-market.”

For many footwear businesses, their success is tied to a specific curation of product and so their data needs are very tailored within the footwear market. While Signal Analytics does offer an industry-wide view, the platform believes that its strength lies in its ability to filter through the data volume and dig deep into the granular level.

Within its pre-made playbooks, Signal Analytics divides its insights into curated taxonomies that address style features, such as heel type or toe style; performance benefits, such as wicking or odor control; material; fit; and activity. Users can filter through these playbooks to their relevant categories and gain insight into their market’s top trends, the opportunities available and the biggest competitors in the space.

“It is critical for [apparel companies] to incorporate a strong data strategy across all areas of the business – from concept to commerce,” says Guy Cohen, chief product officer of Signals Analytics. “Fashion has always been regarded as a creative rather than data-driven field, lagging behind in insight-driven decision-making. By layering in advanced analytics and predictive capabilities such as those in Signals Analytics, brands can balance the art with science, using data-driven insights to create product lines that speak to what will actually push consumers to add items to their online carts.”

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