Innovate. Optimise. Transform.
Modern consumers, driven by inspiration from the physical world and social media, seek effortless product discovery experiences.
Visual search powered by AI object recognition models is the answer for retailers to engage, excite, and direct their customers to their product pages instead of using traditional organic or website search methods.
This technology leverages smartphone camera video feed or rendered page intelligence (what’s on the screen) to identify products and perform real-time matching with your product catalog to surface similar items.
Being visual and engaging is the way to win consumers. Three-quarters of Americans use a smartphone to buy things online, and these devices with powerful cameras and processing power offer retailers a significant opportunity.
AR rendering of the product catalog and virtual try-on removes friction so that consumers can see and understand products in front of their eyes while sitting on their couches.
AR rendering leverages advanced technologies such as AI computer vision, 3D modeling, and LIDAR to deliver unparalleled and modern experiences for consumers.
Know me better and show me what I like and when I want to see it, but don’t intrude on my privacy. That’s what consumers expect from retailers. Understanding customer preferences, demographics, purchase history, search queries, and relevant attributes can allow retailers to surface helpful and credible product recommendations.
Leveraging select branches of AI, such as NLP and data science, retailers can build intelligent product recommendation engines that balance customer conversions and lifetime values while considering consumer privacy concerns.
A positive brand reputation is essential in the digital age. One way to accomplish this is through AI monitoring social channels for negative feedback and tracking keywords, hashtags, and brand mentions.
The AI solution captures and analyses rich real-time data on customer sentiment, preferences, and problems, which can be used to make timely decisions.
Failure to balance inventory demand and supply can significantly impact your top and bottom lines. Inventory planning and forecasting, powered by advanced AI predictions, consider historical patterns and trends and combine them with current and forecasted economic and market signals to drive optimal outcomes.
AI data science models can go one step further by understanding where inventory should be placed and how it is moved proactively based on multiple inputs and parameters, such as weather, events, zip code-based buying patterns, and other related signals.
Blogs
