by Apparel Resources News-Desk
11-February-2019 | 3 mins read
MakerSights, pioneer of the product decision platform for retail, has announced the next-generation of its popular cloud software solution, launching an AI-based decision engine that is tightly aligned to the retail calendar.
The AI and machine learning capabilities of this software allow the product team to accurately determine the styles that are in trend and letting them have a more clear picture of the winning and losing styles of the season.
This reduces the risk factor involved in all product development stages thereby bridging the gap between the company perspective and the actual market demand.
Further on the same, Matt Field, Co-founder and President, MakerSights averred “To most effectively support product-related decision-making, we designed the new iteration of our platform to be tied directly to the retail calendar as opposed to sitting outside of it.”
The brands using the technology can seamlessly aggregate the consumer feedback, historical sales data and internal hypotheses while developing a new product. These inputs can then be translated into actionable, easy to understand recommendations.
“Anyone within a product organisation can access these data-driven suggestions at any point across the product lifecycle to develop better products that will sell to their full potential,” added Matt Field.
The upgraded MakerSights’ capabilities have been extended to support wider array of retail teams and personas from designers and product developers to merchandisers, planners and salespeople, as well as executives who are looking for a structured, scaleable and trusted technology partners to build the skill set of data-driven decision-making into their organisations.
Moreover, the AI capabilities of the software have also broadened beyond collecting and analysing just consumer data. It can now incorporate a brand team’s internal perspective as well as historic selling performance to provide more robust and relevant recommendations.
MakerSights settings and controls are either pre-configured automatically (e.g., how to ask questions to consumers in the right way, how to target appropriate audiences, etc.) or are editable centrally by a MakerSights support team to ensure methodological rigour and to promote ease of use.
Products are then tested with either a brand’s CRM, an externally recruited audience or an internal employee network from the brand. Once feedback has been collected, stage-specific results are generated in real-time to help brands make the best possible product decision at each major product creation or go-to-market phase.
Brands like Levi’s, Madewell, Shinola, Allbirds, Roots, HOKA ONE ONE, Lucky Brand and many other top brands have already been using MakerSights. This has let them make better data-based decisions, de-risk investments in time, capital and creativity throughout their product development and go-to-market cycles.
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