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3D Retail Merchandising Software Market Segmented By engagement channels such as physical stores, online stores, social media, and public spaces with technologies such as big data analytics, cloud computing, Internet of Things, augmented/virtual/mixed reality and others
In the era of digitization, many industries are adopting advanced technologies to increase their customer base. Retailers are realizing the importance of planned store layout and customer shopping experience in optimizing productivity. Enterprises are investing in 3D virtual visualization, which helps them plan their store layout and product positioning, i.e., planograms, before they start building the physical store. Moreover, these software can also be used to study customer behavior in different layouts.
3D retail merchandising software also offers implementation of strategies such as smart shelving, brand engagement, creative product advertising helping enterprises stay ahead of competition.
Retailers are introducing 3D virtual shopping that aims to replicate the experience customers have while choosing a product in a physical store combined with the convenience of online shopping. Retailers are also shifting their attention towards better shelf experience and improved store planning with the help of 3D simulation.
The need to increase brand value and strengthening relationships with customers can be met with the introduction of interactive technologies such as augmented reality. Another driver is the need for better point of sales (POS) system.
Major restraint for this market, especially since most SMEs are not eager to invest huge amounts of money in merchandising, is the high cost of deployment of such technologies. Other hindering factors include lack of skilled labor, privacy regulations in some regions, and lack of awareness about new technologies.
The segmentation for 3D retail merchandising can be done on the basis of user engagement channels, technologies, verticals, merchandising approach and region. User engagement channels can be further segmented into physical stores, online stores, social media, and public spaces.
The technologies can be segmented into big data analytics, cloud computing, Internet of Things, augmented/virtual/mixed reality and others. On the basis of verticals, consumer packaged goods sector can be segmented into food and beverage, footwear and apparel, healthcare and cosmetics, departmental stores and others.
On the basis of merchandising approach, the market can be segmented into merchandise presentation, store environment and store promotion. Regionally, the market can be segmented into North America, Latin America, Western Europe, Eastern Europe, Asia Pacific, Japan and Middle East and Africa.
Mature economies in North America like US and Canada are fast to deploy new technologies, and will be one of the leaders in the market. Asia Pacific is expected to experience a good growth rate, with enterprises investing more in this region and countries like China and South Korea that promote technology.
China alone, is expected to see a high growth rate owing to the fact that it is open to new technologies and its dominance in consumer packaged goods sector. Western Europe and Eastern Europe are expected to experience a moderate growth rate, followed by Latin America and MEA region.
The players involved in 3D Retail Merchandising Software Market are InContext Solutions, Inc., Dassualt Systems SE, Ptex Solutions., Visual Retailing BV, Perspectix AG and Klee Group. More enterprises are shifting to 3D retail merchandising software, which is expected to be the next disruptive technology for retailers.
The report is a compilation of first-hand information, qualitative and quantitative assessment by industry analysts, inputs from industry experts and industry participants across the value chain. The report provides in-depth analysis of parent market trends, macro-economic indicators and governing factors along with market attractiveness as per segments. The report also maps the qualitative impact of various market factors on market segments and geographies.