Selectika is an AI-driven fashion personalization platform designed for eCommerce retailers and fashion brands. It enhances online shopping experiences by delivering personalized product recommendations based on shoppers’ preferences, body measurements, and style profiles. The platform leverages artificial intelligence, computer vision, and machine learning to interpret product data and user behavior, helping retailers boost conversions, reduce returns, and improve customer satisfaction.
Rather than relying solely on traditional filters or generic recommendations, Selectika offers intelligent personalization that understands each shopper individually. This innovation allows fashion retailers to create engaging, efficient, and tailored shopping journeys that drive measurable results.
Features
Selectika’s capabilities are centered on turning raw product data and user input into actionable personalization. Key features include:
Personalized Recommendations: Delivers real-time product suggestions tailored to each shopper’s body type, preferences, and previous behavior.
AI-Generated Style Profiles: Builds shopper profiles based on user input, browsing patterns, and purchase history, combining fashion and data science.
Fit and Size Matching: Matches customers with products that are most likely to fit based on their body shape, size, and preferred styles.
Visual Search and Filtering: Uses computer vision to analyze product images and tags to ensure that style recommendations are visually accurate and relevant.
Plug-and-Play Integration: Easily integrates with eCommerce platforms such as Shopify, Magento, and custom-built stores.
Real-Time Analytics Dashboard: Provides retailers with customer insights, performance metrics, and behavior trends to optimize inventory and marketing.
How It Works
Selectika uses a combination of machine learning, NLP (natural language processing), and visual AI to enhance product discovery and match shoppers with the right items. The platform works as follows:
Product Tagging Engine: Selectika automatically enriches product catalogs using AI to generate advanced product tags from images and text descriptions. These tags include style, fit, occasion, material, and more.
Customer Profiling: Shoppers are guided through a brief onboarding or quiz where they input size, body shape, and style preferences. The system can also build profiles passively based on browsing behavior.
Personalized Discovery Layer: Based on the data collected, the platform displays only the most relevant items on the homepage, category pages, and product recommendations.
Fit Confidence Layer: Selectika cross-matches the product tags with the user profile to offer size and fit suggestions that reduce returns and increase satisfaction.
Performance Tracking: Retailers access real-time performance analytics showing click-through rates, conversion improvements, return rates, and revenue uplift due to personalization.
Use Cases
Selectika is specifically designed to serve fashion eCommerce businesses. Its applications are valuable in a variety of business contexts:
Online Fashion Retailers: Improve user experience and increase conversions by showing shoppers only the most relevant products.
DTC Brands: Direct-to-consumer brands can use Selectika to differentiate themselves with premium customer experiences.
Multi-Brand Marketplaces: Offer tailored recommendations across a wide range of categories, helping users navigate large inventories more efficiently.
Luxury Fashion Stores: Enhance personalization for high-end customers expecting premium, customized service online.
Mobile Shopping Apps: Embed Selectika’s API to offer real-time personalized recommendations within fashion apps.
Pricing
Selectika does not list public pricing on its website. Pricing is likely customized based on the size of the store, number of SKUs, and level of integration required.
However, typical pricing models for platforms like Selectika may include:
Monthly Subscription Fee: Based on the number of monthly active users or SKU volume.
Setup Fee: One-time integration and onboarding fee.
Performance-Based Pricing: In some cases, platforms charge based on the uplift in conversion or revenue.
To receive accurate pricing, interested retailers need to book a demo or contact Selectika directly through their contact page.
Strengths
Selectika delivers clear value to retailers and end-users alike through:
Highly Accurate Personalization: AI recommendations based on deep product tagging and body profile matching.
Reduced Return Rates: More accurate size and fit suggestions help reduce costly product returns.
Improved Customer Experience: Personalized journeys lead to higher satisfaction and loyalty.
Fast Integration: API and plug-ins enable quick deployment across multiple platforms.
Retailer Insights: Access to detailed analytics helps improve inventory planning and marketing strategies.
Drawbacks
Despite its strengths, there are a few limitations worth noting:
No Self-Service Pricing: Lack of transparent pricing may deter small businesses.
Initial Setup Time: Onboarding and data tagging might take time, especially for large catalogs.
Dependent on Data Accuracy: The effectiveness of recommendations depends on the quality of product data and customer input.
Enterprise-Focused: May be better suited for mid-to-large scale retailers rather than micro eCommerce shops.
Comparison with Other Tools
Compared to other personalization platforms in the fashion retail space, Selectika stands out in its AI tagging engine and fit-based personalization. Here’s a brief qualitative comparison:
True Fit: Focuses primarily on size and fit but lacks the advanced visual tagging and full personalization capabilities that Selectika offers.
Stylitics: Provides style-based outfit bundling but doesn’t offer body-type-specific recommendations.
Vue.ai: Offers similar capabilities across tagging and personalization but caters to a broader retail audience beyond fashion.
FindMine: Known for shoppable looks but lacks the personalized fit engine that Selectika provides.
Selectika uniquely combines visual AI, fit analytics, and real-time recommendation layers optimized specifically for fashion eCommerce.
Customer Reviews and Testimonials
While Selectika does not publish customer reviews directly on its site, it lists several trusted fashion brands and retailers as partners, including:
Terminal X
Golf Town
Adika
Factory 54
These businesses use Selectika to enhance their digital storefronts with AI-powered recommendations and personalized discovery tools.
Case studies and success metrics cited on the website include:
3.5x increase in conversion rate due to personalized product discovery
35% uplift in average order value
20% reduction in return rate
Retailers report smoother customer journeys, faster product discovery, and increased customer loyalty after implementing Selectika.
Conclusion
Selectika is a powerful AI-driven personalization platform built for fashion eCommerce retailers looking to enhance the digital shopping experience. By combining advanced product tagging, shopper profiling, and real-time recommendations, it creates a seamless and individualized journey for every customer.
Retailers benefit from increased conversions, lower return rates, and deeper shopper insights, while customers enjoy a faster, more accurate, and enjoyable shopping experience. With support for easy integration and measurable ROI, Selectika is an essential tool for fashion brands aiming to compete in a personalization-first eCommerce landscape.
For fashion retailers looking to modernize their customer experience and drive business growth, Selectika offers an intelligent and scalable solution worth considering.
