Iris X

A Powerhouse of Data and Analytics

Recognized as a ‘Cool Vendor’ in Gartner’s 2020 Report, “Cool Vendors in Retail: Meeting Customer’s Basic Expectations Is More Important Than Ever”, Iris X provides automated data integrations and dedicated merchandising expert support in analysis and decision making. Its unique web-based, SaaS+ model for B2B and B2C retailers, performs billions of computations to give marvelous insights.

Impact

Deep insights help break complex retail challenges into simple targeted solutions that drive brand value and promote sales.

13% increase in in-season full-price sell-through for one of the largest celebrity brands

25% increase in revenue and a 4% improvement in margins for one of the largest lingerie brands.

24% L2L growth in full price revenue with discount reduction of 3% for one of the largest women’s wear brands

13% reduction in brokenness for a leading formal wear brand

28% improvement in ROS through inter store transfers for a leading men’s wear brand

Reduced inventory holding from >120 days to <80 days for a pioneering lingerie brand

Modules

Use this intelligent merchandising tool, consisting of patent-pending algorithms developed over 3 years of R&D to revamp your retail game.

Smart Assortment Plan

Enable merchandisers and planners to optimize inventory mix with computational power to go up to a granularity of design level attributes of styles.

  • Identify NOOS- top sellers/ best sellers and core styles with persistent sales for a longer period of time
  • Perform computations up to 17 levels of product attributes for ideal decision making
  • Better forecast across stores basis true rate of sales at the store-attribute group level by analyzing past sales, revenue, discounts, size-cuts, stock-outs, and exposure.
  • Identify and discard highly discounted sales that distort true demand
  • Achieve higher revenue and margins by identifying true style level store demand and maintain continuity of pivotal sizes in each store. 
  • Lower inventory cost by correcting long-tail styles at the store-attribute group level.

Open To Buy

Maintain freshness throughout the season by creating an appropriate mix of inventory in the right levels with high availability as per the local demand.

  • Automate store-style level buy across drops
  • Determine actual procurement order based on Demand Planning, Depletion, Returns, and other considerations like lead time and MoQ, to find the opening inventory at the start of the OTB period
  • Predict daily ROS at an attribute group level

Dynamic Markdown

Basis a style’s on-going performance and stock-status, the smart algorithm recommends if it is an outperformer and should be re-ordered, or if the current discount should be increased or decreased, basis:

  • Price elasticity and brand-category level guardrails for discounting and reordering
  • True ROS ™ of healthy size-set, when compared to others
  • Current discounting
  • Ageing of style
  • The present health of the style

Optimal Store Allocation

Take advantage of this highly advanced and automated solution that generates a dynamic store-style ranking to optimize inventory distribution through:

  • Fresh/ New season allocation
  • Size-wise and collection/story-wise displays
  • Event-based allocation
  • Automated replenishment and replacement system. 
  • Identifying non-moving dead styles in stores and suggesting pullback to warehouse

Inter-store transfers

Prevent extra buying and utilize inventory redistribution between stores to:

  • Improve stock health
  • Reduce stockouts at SKU level
  • Improve omnichannel exposure by leveraging excess stock. 
  • Optimize stock cover across stores

Business Intelligence

Offers a wide range of dashboards to review business performance and take focused action.

  • Business overview for executives
  • Category performance reports for merchandisers (Sell-through-rate, sales  Velocity, DoH, Top/Dead sellers, Planogram Adherence, Style Performance, Stock v/s style, Discount v/s ROS).
  • Target v/s Achievement of revenue, week-on-week store performance, and Sales per SqFt. reports for operations
  • Design dashboards for buyers
  • Analytics ranging from a store manager to the CEO

Designed for Fashion

  • Attributes-based prediction
  • Seasonality, Festivity, and Recency
  • Full price v/s End of Season Sale
  • Freshness index

Built for accurate and fast results

  • True ROS ™ (rate of sale) + Liquidation noise cleanup
  • No clustering of stores – “segment of 1”
  • 17 levels of fashion attributes instead of the usual 5
  • Allocation based on store style ranking

Created by merchandisers

  • Pre-season - Smart assortment plan & Automated buy plan
  • In- season - Optimal store allocation, Inter-store transfers, New store allocation, Dynamic discounting

Based on Intelligent algorithms

  • Patents pending (US & India) self-learning algorithms
  • Consumes only raw data, creates intelligent inputs
  • 100+ customizable algorithms, to map brands business requirements

Have questions? Get in touch with us and we'll walk you through it. increff@increff.com

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Smart store-style algorithms

Using smart store-style ranking algorithms, one of India’s leading men’s casual wear brands, distributed inventory across ~120 EBOs based on the Smart Assortment Plan suggested ...

Auto-Replenishment System

One of India’s leading formal wear brands used IrisX to manage inventory across multiple sales channels. By predicting the size-wise demand at store category level ...

Smart Assortment Plan

Optimized inventory through the smart assortment planning for different sales channels. one of India’s biggest celebrity-endorsed fashion brands reduced overstocking by defining display norms as ...

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