, Description:FIELD OF THE INVENTION

[1] This invention is in the field of pricing, specifically the field of transaction price determination and uses an automated system which aids to identify and determine the nominal price of a resource.
OBJECTIVE OF THE INVENTION

[2] The objective of this invention is to aid users in reducing the guess work involved in determining what a unit of product or service should cost when transaction for such a resource take place. The system provides a guidance that can help users know what is the market price range for any product in consideration.
BACKGROUND OF THE INVENTION

[3] Over the last couple of years, the field of trade has grown remarkably. Trade transactions include both, goods and services and span various geographical boundaries and can involve different currencies, duties and taxes. The task of transacting for a resource (product or service) is a complex one as the greatest conundrum that the buyer and sometimes also the seller is posed with is to determine what the unit to be transacted should cost.
[4] We buy and sell things every day and such a system can make these activities simpler and more informed. In addition, it can bring fairness into the market.
[5] It is extremely important to know how much any commodity costs and what is its nominal or going market rate with respect to a plurality of factors such as the quality and/or quantity of the commodity desired, when you are looking to transact (the time of the year or the day of the week or the seasonality of the required commodity).
[6] Thus, there needs to be a uniform system by which a user understands the various market prices of the resources they need and eventually get actual rate of the same resource or commodity.
[7] The current invention provides for a systematic guidance on the price range for a particular product or service that the user should pay. It eliminates the uncertainty and guess work during the process of choosing a product or service. It brings in a better sense of fair market value for those products or
services.

BRIEF DESCIPTION OF THE DRAWINGS

[12] FIG 1. Illustrates the system for the determination of the nominal price of a unit.
[13] FIG. 2 Illustrates how the transaction densities are determined by the system based on past transaction data.
DEFINITIONS OF THE TERMS USED
[14] The term ‘user’ means and includes an individual who uses the service or operates to use the service.
[15] The term ‘traveller’ means and includes one or more of the individuals traveling in the transport vehicle. The terms ‘users and travellers’ can be used interchangeably.
[16] The term ‘computing device’ means and includes devices like laptops, computers or cellular phones which is in the transport vehicle and may be in transit in the vehicle or on the person of the ‘traveller’.
[17] The term ‘nominal price’ means and includes the going away cost of the resources.
[18] The term ‘bid density’ means and includes the quantity of demand transactions that have been conducted in the past at a specific transaction cost in the past.
[19] The term ‘constraints or attributes’ the different factors that are taken into consideration to determine the nominal price of the resource.
[20] The term ‘computing device interaction system’ means and includes the system that interacts with the computing device as described above. The computing device may interact with the computing device interaction system over a wired or wireless or other communication network in real-time or in a deferred approach if the communication network is unavailable.

DETAILED DESCRIPTION
[21] FIG. 1 discusses the system which helps the user to determine the going away price of the product or service. The system uses a plurality of factors which may either constrain or expand the supply of that unit. The system leverages a database of past records of bid offers and transaction values and transaction times.
[22] In this figure, user’s computing device (100) sends in a request to the central computing interaction system (200) requesting the price for the service or unit they require. The system 200 sends this information to the past transaction data database (201). In this database, past transaction information is available. When the user sends in a request for a unit or service, it gets sent to 201 to analyse the past transaction data for that particular unit or service. This database stores and remembers data for each transaction, bid, and offer of any product or service. This may include various attributes, including but not limited to the quantity of the product or the quality of the service, the season of the year. This data thus helps the system to find the nominal price of that particular unit or service.
[23] The qualitative & quantitative attributes of the data requested is also taken into consideration where the. For example, if the user is requesting to know the cost of a shipping container of apples the cost of apples will be affected by a plurality of factors. These factors may include but are not limited to, the size and type of the apples, the season or month of the year for which the pricing is requested, the day of the week when delivery is needed, and where the delivery is needed. The apples may cost less during the period of September- October as it is the peak season for production of apples and they may cost much more when its off-season. With the help of these factors, the data with lower relevance is given less weight as supposed to the data with higher relevance.
[24] In another example, if a user is looking to buy a car of a specific make or model the system can come back with information on the price range where most transactions have taken place and what is the reasonable price range within which the system suggests for the transaction to happen.
[25] FIG.2 discusses the system of learned market costing. In this figure, the scatter chart shows how past transaction data is plotted and the areas of the chart where the most transactions have taken place (we will call this transaction density). As shown in the figure, the data has been collected and plotted for a specific product or service that is defined by specific qualitative attributes. The data for the same is collected over a time period and stored in the system. When a user requests for the price for such product or service, this past transaction data is analysed to provide to finally determine and recommend the nominal price point for the product (as shown in FIG 3)
[26] For example, if a user wishes to buy apples and mentions the transaction attributes, like the apples should be from Himachal Pradesh or Kashmir and that the apples be of a particular quantity (10 boxes or 30 boxes.) This information is now sent to the system. The system takes into consideration the past transaction data of apples, as shown in the scatter chart in FIG 2. As seen in FIG 2, the Areas A, B and C labelled in the scatter chart are representative of the price ranges where the most transactions for the given quantity of apples have happened in the past. These price ranges are indicative of the areas with the highest transaction density for the apples and each area A, B or C may be further characterized with other attributes that further differentiate the price ranges. As an example, the price range A is for quantities in the range of ~40 to ~50 whereas price range C is for the price range of ~30 to ~40. This data helps the user to identify the best price point at which a certain quantity or quality of apples are sold for. The data plotted on the scatter chart is collected over a period of time so as to get an accurate indication of the historical price of the apples.
[27] In another example, the user wishes to buy mangoes – in the month of May. The user sends this information to the system 200, as shown in FIG. 1. This information travels to 201 where the system identifies the past transaction data of mangoes in the month of May. As given in the scatter chart, the various price points at which mangoes are sold will be plotted. The prices will vary with respect to the qualitative and quantitative attributes of the mangoes. The cluster of points in the scatter chart indicate the price points at which various quantities of mangoes are sold. This helps the user to identify the nominal price of the mangoes in the month of May. The points A, B and C are the price points at which the mangoes were sold for in the past, in the month of May. Thus, the nominal price of mangoes in the month of May will be either of the plotted points.
[28] In another example, the user wishes to buy mangoes – in the month of December. This data is plotted on the scatter chart. The points A, B and C are the price points at which mangoes were sold for a particular price in the past. This is taken into consideration while determining the nominal price of the mangoes.
[29] FIG. 3 discusses the bell curve which gives the density of different price points at which a particular unit or service is given away for.
[30] For example, a user wants to book a hotel room for a vacation. The user can request the price for a 5star hotel room in San Francisco for a specific day of the week. The system will analyse past transaction information to now come back with information on median cost of a 5start hotel room, how much such transactions the data is based on and what is the reasonable range of price that the user should expect to pay for such hotel room.

Claims:CLAIMS

I. A method and system of determination and identification of nominal prices for a unit (product or service) with the help of computing devices and a central interaction system
II. The method of Claim 1, further comprising of: determining the past transaction data of the unit
III. The method of Claim 1, further comprising of: determining the qualitative and quantitative attributes of the unit or service.
IV. The method of Claim 2 further comprises of a scatter chart to plot the past transaction data.
V. The method of Claim 3 further comprises of a bell curve to understand the nominal price with respect to various qualitative and quantitative attributes.