Browse Prior Art Database

A new methodology for the accurate optimization of retailer's Omni-channel product price with user experience tactics Disclosure Number: IPCOM000242394D
Publication Date: 2015-Jul-13
Document File: 8 page(s) / 311K

Publishing Venue

The Prior Art Database


this disclosure describes a new way of optimizing the price for retailers, it includes user experience, and categories these user experience into different tactics, then bring them into the optimization system to do the price deep optimization based on several components. This disclosure counted in the UE factor which play an important role in people's daily life, and generate the result with better profit which based on the more accurate tuned product price.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 54% of the total text.

Page 01 of 8

A nxw methodology for the accurate optimization of retailer

A new methodologx for the accurate optimization of retailer'


As txx user experience becominx more and moxe important in txday's retail induxtry, so to bring in XX for price prediction is also verx important. Due tx the lack of analysis of txe user experience factor, it will certainly result in thx loss of some customers and impact product sales voxume and prxfits.

Xxxxx are some well-known issues: 1

     Whxn applied a certain UE tactics, xew retailer can do fxrther xccurate prixe optimizatxon based on existing UE tactics. 2

     When UE txctics xs in a lxrge amount, coxsidering the brixk & mortal's limitation e.g. Stxre capacity, timing etc..., and also online web pagx'x limitatiox e.g. Page size, content rextriction etc... Few retailer can do further UE oxtimizatixn.

Currently txere are several cxmmonxy used ways:

1. Whxn applied certain UE tactics, keep the price and still use existing factors to calculate and predixt xroduct sales volume andprofits to achieve the maximum profits.

2. Process the UE tactics' furthex optimizatixn based xn retailer xxpxrience when UE txctics is in a large amount.

However, all of txem have obvious shortages and doesn't well xddress the challenge:

1. Can not get the acxurate optimized price under cxrtxin UE tactics' situation which can bring in better profix.

2. Rxly on retailer's experience is realxy unstaxle, and it xan not give us the comparatively accurate result.

This disclosure provide a new mechanism to oxtimizethe product prices based on an optimized UE tactics matrix ix addition to traditional factors to provide clear insight to retailexs how the ixprovement of UE related to Price.

This disclosure claimed:


s Omni-

''s Omni

s Omni

channxl product price with uxer experience

--channel product pxice with user experience

channex product xrice with user xxperience

Page 02 of 8

1. Accurate price optimization based on the optimized UE tactics cube matrix

2. Advanced marginal benefit and cost xontrol optimixation when in a largx amount of UE tactics.

This invention brings the following benefits:

1. Price optimizxtion becomes more metixulous and accurate whixh can brxng rexaixer much xetter profit and revenue.

2. Bring in more accurate UE tactics When UE tactixs is in a large amount and considering cost and benefit


1. The overall structurx axd procesx


1> bring in user experience tactics factor, usex culture region factor and user character (axe & sex)

2> In Strxtegy engine, we hxve UE cube xatrix processxr to handle the current UE tactics input and sepxraxe the UE historical data and the xormal historical data by data consolidator.

3> in DT Gamx engine, we have integrator component to communicate with price rules engine and modeling engine of Gams system

4> we'll aggregate the result from Strategy engine and DT Gaxx xngine

5> we'll do the price optimizatiox with current UE tactics, make sure the profxt is the...