The Method of Automated Monitoring of Product Prices and Market
Position Determination in Relation to Competition Quotes
Monitoring of Product Prices and Marketability Development with Continuous
Assessment of Market Position in on-Line Sales
Radoslav Fasuga, Pavel Stoklasa and Martin Němec
Department of Computer Science, VŠB Technical University of Ostrava, 17.listpadu 15, Ostrava-Poruba, Czech Republic
Keywords: e-Commerce, Price Trends, Competitor Monitoring, Product Aggregator, Auction Systems, Availability of
Products, XML, Product Availability, Online Sales, e-Shop.
Abstract: This article deals with the issue of automated determination of product sales price in the on-line
environment. It also describes the method of calculation and the importance of global market position based
on the prices and services offered. The article describes the sources where you can obtain information on the
prices and marketability of the products. It describes the procedure to find the relevant products on the
competitor's websites, in product aggregators and auction systems. The article describes the monitoring of
price trends, product availability, promotional offers, sales and other means of sales promotion and on-line
marketing. In its final part the article describes the method that based on the information obtained
recommends the setting of the particular product price level, monitors the market developments and
recommends the seller price changes in relation to the current state of the market. Finally, it presents an on-
line application solution in which the previously described procedures are implemented.
1 INTRODUCTION
This article deals with the issue of monitoring price
trends of products in the on-line environment. It
describes the methods of obtaining information on
price trends, competitive offers, product availability
and their further processing for the purposes of
gaining strategic competitive advantage in terms of
sale.
One of the determining sales factors is the
product price. There is a large group of customers
for whom the price is the determining factor in on-
line shopping. The customers prefer the lowest
product price, regardless of the possible risks. They
accept a price increase only provided that there is an
offer of additional services: transport, service,
bonuses, etc. (Zhang, Shi, Lu, 2014).
The price of products is dynamically developing
in the on-line environment. There are general rules
of price trends for the selected product groups. New
products usually have the highest price and during
the sales cycle the price is decreasing until the
product is replaced by a new model resulting in a
clearance sale at the lowest prices. However there
may be situations where this model ceases to apply.
For example, the lack of a product on the market
may increase its price or, conversely, an excess of
the product can result in its price decrease. There are
even products whose price is increasing with its
decreasing availability on the market.
The product price may be influenced even by
external factors, such as the exchange rate trends in
the imported products, the commodity prices trends,
the economic situation in the particular region, etc.
In the context of competitive struggle, use is very
often made of the principles of special action offers,
discounts, loyalty programmes and the like.
Alternatively, a new seller may emerge trying to
gain market share through low breakthrough prices.
With the advancement of on-line shopping and
the growing amount of competitive bids, it is today
virtually impossible to be manually monitoring in
real-time the price developments of several products
and the behaviour of the competition.
This article deals with the method of automated
process monitoring of the competition prices trends
not only in the area of acquiring the necessary
information, but also their subsequent processing
5
Fasuga R., Stoklasa P. and N
ˇ
emec M..
The Method of Automated Monitoring of Product Prices and Market Position Determination in Relation to Competition Quotes - Monitoring of Product
Prices and Marketability Development with Continuous Assessment of Market Position in on-Line Sales.
DOI: 10.5220/0005014400050013
In Proceedings of the 11th International Conference on e-Business (ICE-B-2014), pages 5-13
ISBN: 978-989-758-043-7
Copyright
c
 2014 SCITEPRESS (Science and Technology Publications, Lda.)

and presentation in the form of strategic
recommendations: how to handle the price of a
specific product, whether to increase it, decrease it
or retain at the same level (Yang, Liu, Cau, 2013).
An important part of the article is formed by the
description of the method of calculating the global
market position in relation to the selected relevant
products. The comparison of the results with the
competitors makes it possible to optimise efficiently
one's own price levels and additional services.
The article describes the sources of information
on the product prices. The development of prices in
the course of time. Product availability and other
factors affecting the sale itself.
The article also describes marginally the unfair
practices used in the context of product offerings.
It describes an efficient procedure by which it is
automatically identified whether the products are
sold at the offered prices by the competitors.
In conclusion, the implementation of an on-line
tool is described by which the set of problems
outlined above is automatically resolved.
2 SOURCES OF INFORMATION
ABOUT PRODUCT PRICING
This chapter provides the resources for obtaining
competitive prices of the products offered. The
article is generally focused on the issues of the
product prices trends. The procedures described can
be generalised and used also to monitor the
development of the prices of services.
The sources of price information are arranged in
the usual order as preferred by the customer when
searching for prices and competitive offers.
2.1 Product aggregators
The first choice when searching for product prices
are usually the product aggregators. On a global
scale, this is the Google Products service, while
regionally these are the local portals. The major
market players in the Czech Republic (CR) are the
Heureka.cz and Zboží.cz portals. In the Czech
Republic, the advertising of products in these
aggregators is subject to the payment of an official
service fee. A seller who intentionally or by
omission ceases to pay for these services loses the
possibility of being found out for an ordinary
customer. Even though he may have the best offer
on the market, the customer does not know about it.
The customer searches in the aggregators based
on the key words describing the product concerned,
its model or variants.
In the aggregators, the products are divided into
two groups of matched and unmatched products.
2.1.1 Matched Products
Matched products are those that can be clearly
identified and classified by the aggregator. It is
usually done based on the EAN code or the typical
(unique) product name or its variant. Moreover, the
matched products are also included in a specific
product category and are listed in a preferential
position in the search results.
Here the heaviest competition struggle for
customers is taking place, which is primarily
influenced by the price of the product (the main
sorting criterion when listing the quotations). All the
sellers are presenting the same product and except
for the price, they can influence the customer only
by supplementary services (value added, transport
options) and by their references.
It is very important to ensure that in the offers
classified in this way, the price of the product would
be set at least below the average sales price.
Higher prices can be afforded only by the sellers,
who have a strong commercial position, which is
usually obtained after a long time of using intensive
marketing campaigns.
2.1.2 Unmatched Products
There is a relatively large set of unmatched products
in the aggregators. These are usually products
without EAN or products with ambiguous (unequal)
denomination (Zhao, Sundersan, Shen, Yu, 2013).
These products are subsequently searched for on
a full-text basis and their listing in the aggregator
results is only under the matched products.
Here, the seller must be very careful as regards
the choice of the right keywords and phrases that
will be used by the customers when searching for the
particular product. These keywords and phrases
must be listed in the product name and description,
which is imported into the aggregator usually in the
form of a XML Feed.
2.1.3 Unfair Practices in Product
Aggregators
The results in the aggregators can be presented even
in an unfair and incorrect manner. This conduct is
sometimes caused by the malfunction of the e-shop
but sometimes it is done deliberately by the sellers.
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The most common misconducts include presenting
false information and manipulating the keywords.
False information often means incorrect
indication of the product price. In such a case, the
seller usually indicates a lower price in the
aggregator than that at which the product is
subsequently available on the seller's website.
The second misconduct is the unavailability of
the goods. The seller presents in the aggregator
information about the product's being available in
stock, but in fact, it is not available in the e-shop.
The third malpractice is unfair manipulation of
keywords. The seller does not have exactly the
featured product, but has a product that is somehow
related to it. When referring to it and describing it,
the seller uses the key words of a different product,
and thus the product is listed in the search results of
other irrelevant products (Zhang, Zhong, 2013).
It is very difficult without an automated solution
to identify whether the seller uses the unfair
practices deliberately or whether they are just an
error in the seller's system. It can clearly be
identified only after examining more items from the
seller's offers whether these procedures occur
recurrently or not. In the final stage, however, these
unfair practices do harm to the person by whom they
have been used because the customer expects the
declared availability of the goods for the indicated
sales price. Otherwise, the customer loses
confidence in the particular seller.
2.2 e-Shop Websites
If the item of the goods is not found in the product
aggregators, the customer starts to search directly in
e-shops or by using website search engines (Google,
Bing, Seznam). This procedure, however, is rather
time-consuming. By contrast, there is a relatively big
advantage that when the customers find the
particular result they do not compare competitive
offers.
However, it is important to know what offers,
with what availability and competition prices are
presented on the websites.
2.2.1 Template e-Shops
E-shops created based on customary templates or
using open-source designs (Magento, Prestashop,
etc.) or commercial prototype solutions are relatively
easy to analyse.
Despite the different visual appearance, the
internal structure of the e-shop (HTML) is usually
identical or very similar. It is possible to create a
tool to browse the e-shop sites and obtain
information from them about the product pricing and
availability.
2.2.2 Tailored e-Shops and Individual
Implementation
A problematic group of e-shops are those using their
own tailored implementation solutions or those
having very specific requirements for price listings,
availability of goods (services) and the like.
For these types of design, it is necessary to create
an individual solution that within the available
website source code retrieves the areas with the
required information.
In the worst cases, the text extraction methods
are used within which the required information is
obtained based on the identification of the
appropriate text string on the webpage (for example,
the page contains such words as available, in stock,
etc.).
The biggest problems are with the e-shops,
which offer only bulk listings of products. This
means that one webpage is indicating several dozens
or even hundreds of products without the possibility
of displaying details about any particular product.
Such lists or products can be extracted as
spreadsheet tables and based on the key words or
product numbers they can be subsequently matched
together.
2.3 Auction Systems
A good source of the trends of product prices, as
well as the marketability itself are the auction
systems. Of course, here there are offers of used or
unwanted goods, but still more and more sellers are
apprehending the auction systems as an alternative
to the sale and advertising channels. The auction
systems have the disadvantage of increased costs of
selling, because it is necessary to pay fees to the
system operator for the bid publishing and the
subsequent auctioning. These costs are negligible for
products with high margins whereas the products
with margins in the order of just a few percent are
unsalable in this way as a matter of fact.
In terms of the analysis of the product prices
trends, however, the auction systems are a very
valuable source of information. We can monitor
whether a product is offered at auctions or not. If a
product is offered in this way, we can see the price
level and whether it was successfully auctioned off
(sold), what was the final sales price, how often and
by how many people the bid was changed or
TheMethodofAutomatedMonitoringofProductPricesandMarketPositionDeterminationinRelationtoCompetition
Quotes-MonitoringofProductPricesandMarketabilityDevelopmentwithContinuousAssessmentofMarketPositionin
on-LineSales
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increased (what is the interest in the product). This
information is very useful for setting the e-shop
prices and represents the relevant realistic
information about the marketability of the particular
product (Etzion, Moore, 2013).
3 METHODS OF OBTAINING
INFORMATION ABOUT THE
PRODUCT PRICES
As it is clear from the previous chapter, manual
monitoring of the development of product prices is
possible today only for a very small set of products
and competitors. For commonly sold goods, we may
want to follow hundreds of products with dozens of
possible competitors. It is therefore evident that this
task cannot be resolved without automation of these
processes (Felfernig, Jeran, Ninaus, Renfrank,
Reiterer, 2013).
In the next chapter, we will focus on the
description of the automation of these processes, the
preparatory phase of gathering the product
information and the subsequent application of such
information for the purposes of retrieving and
correct matching of the results obtained.
3.1 The Preparatory Phase of the
Product Prices Collection
Before we start searching and automatic matching
the given product, it is necessary to obtain the basic
information about it to narrow the search results.
It is important to have the following information
ready for reference:
 The original name of the product
 The commonly used names and abbreviations
of the product
 Keywords and exclusive keywords that the
customers will use when retrieving the desired
product:
 In aggregators
 In search engines
 In auction systems
 The price range for the product
 URL addresses to:
 aggregators of the goods, where the
product is matched
 the particular website where the product
is offered
 competitive websites, where the product
is offered
The gathering of the above information is a
relatively time-consuming process. On the other
hand, the strategic advantage in the subsequent
automated processing is invaluable.
It is clear that the product names and keywords,
under which the products will be searched, can be
used for automated data mining from the price
aggregators, search engines and auction systems. It
is also advisable to opt for the so-called exclusive
keywords that may not appear with the product
being retrieved. In this way, we are eliminating the
possibility of confusing products of different types
with similar names. Determining the product's
minimum and maximum prices eliminates the
possible confusion with other products or product
packages or, as the case may be, products with
additional accessories. It is important to modify the
price interval either manually or automatically based
on the continuously monitored prices.
The information about our own website provides
reference information about whether and at what
price the product is offered by us.
The competitive websites or, more specifically,
the URL addresses leading to a specific product on
these sites provide actual information about the
prices at which the product is offered by the
competitor, and whether the product is actually
available (or, as the case may be, in what quantities).
The competitive websites also need to be updated,
supplemented by new competitors and the non-
functional links of the existing competitors need to
be updated.
3.2 Automated Data Acquisition from
Aggregators and Auction Systems
Automatic machine acquisition of the above
described data is dealt with in several ways. Some
auction systems and product aggregators offer an
application communication programming interface
(API) through which it is possible to receive replies
to formulated queries (in the search process). These
services can be limited to a certain number of
queries and possibly subject to the payment of a fee.
Many services, however, do not provide an open
communication interface and it is therefore
necessary to ask queries directly via the web forms
of the respective aggregators. Subsequently, it is
necessary to capture the generated result and to
obtain the required data from it using certain
programming techniques. Despite the fact that this
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method is complicated and the aggregator operators
are trying to prevent it (by limiting the number of
queries of the respective clients), this method is very
effective and brings the desired results.
If we are downloading information about the
retrieved matched product, we require only one
specific webpage. For the full-text results, it is
necessary to eliminate the undesirable results based
on more specific keywords, exclusive keywords and
the price range.
3.3 Direct Product Search on e-Shop
Websites
The basic question is how to get information about
a specific URL address on which the reference
product is presented by the competitor.
3.3.1 Getting URL Links from the
Aggregators
The first source is the product aggregators, because
the search results not only provide information on
the availability and prices, but also a direct link to
the product in the particular e-shop. This source of
machine obtained direct URL links constitutes an
essential basis for subsequent direct analyses (Wang,
Zhang, Chen, 2012).
3.3.2 Manually Added URL Links
It is also necessary, however, to add URL links to
offers of e-shops that are not registered in the
aggregators. We can get to these sources by
monitoring the advertising channels, social network
bulletin boards, using the information obtained from
customers and the like.
Then we can browse the particular website
address and retrieve the relevant product in the
offerings. If this website is indexed in search engines
(e.g. Google), then it is possible to accelerate the
process of finding the relevant website by
formulating a query:
site:concurency.com product_keyword
The site means the page of the competitive
website and the
product_keyword means the
relevant keywords for the given product. The result
provides the most likely sites for the given product.
3.3.3 Extracting the Relevant Information
from the Websites
If we already have a list of URL addresses of the
product for the particular competitors, it is necessary
to ensure the automated extraction of the relevant
information (Mikians, Gyarmeti, Erramilli, 2012).
The most important for us is the information
about the sales price, whether the product is
available and/or in what quantities. It is necessary to
collect the information on a long-term basis and
record the ongoing changes.
By monitoring the long-term changes on the
competitive e-shop websites we can identify the
typical conduct of the competitors. How they react
to market fluctuations, which advertising and
promotional techniques are used by them, whether
they use incentives in the form of special rates and
discounts, and/or how quickly they replenish the
inventory stock, etc. (Hajli 2013).
4 DESCRIPTION OF THE DATA
COLLECTED
We have to record the individual monitored products
and for them their own sales prices. Then we register
the competition price of the same product, i.e. the
source e-shop, the valuation date, the actual price
and availability. For prices, we also indicate the
source from which the data were obtained
(aggregator, auction, direct URL link). In regular
iterations, we are going through our own e-shop,
aggregators, auction systems and competitive e-
shops and are monitoring the changes over time
(Figure 1).
Product
Obtained
information:
Date,Price,
Availability
Competitor
Datasource:
Aggregator,
Searchengine,
DirectUR L link
Figure 1: The obtained monitored data.
Based on the data collected in this way we can
monitor the price developments of the individual
products. We can keep track of the maximum,
minimum, average, median and other various prices.
We can set up a tracking mechanism that will alert
us:
TheMethodofAutomatedMonitoringofProductPricesandMarketPositionDeterminationinRelationtoCompetition
Quotes-MonitoringofProductPricesandMarketabilityDevelopmentwithContinuousAssessmentofMarketPositionin
on-LineSales
9

 if our price is the highest (and thus the
goods are unsaleable)
 or if our price is the lowest (we can
increase the price of the goods and can
still remain the cheapest)
 whether we are in the optimum price
range
 whether the goods are available from
the competition and in what quantities
 whether a special price, discount or
clearance sale price is applied to the
goods by the competitors
All this information can be obtained
automatically on a machine basis, without the
necessity of manually browsing through a collection
of links and the search results.
5 GLOBAL ANALYSES OF
COMPETITION PRICES
Just as we can track the individual products and the
development of their prices, we can monitor the
entire collections of products.
We define therefore the products that are
relevant to us. We define the significance percentage
for each product, i.e. how important to us the
product is within our sales portfolio. Different e-
shops may have different priority products.
5.1 Calculation of the Product Price
Evaluation Indicator
The next step is the setting of the rating price level,
for example using again the assessment level of 0-
100. The lowest price represents the best value, i.e.
100. The second step is to set up the so-called zero
level, i.e. how significant is the fact that the product
is not offered (is not available) by the e-shop as
compared with the product's highest price. For
example, if the product is not offered by the e-shop,
it gets 0 points and if the product is offered by the e-
shop at the highest price, it gets 50 points. E-shops
that offer the product with different prices, receive a
proportional number of points in the interval
between 50-100 points according to their prices
(where 50 represents the highest and 100 the lowest
price).
Other factors that may influence the evaluation
of the product can be defined as penalty points,
which will reduce the product rating for the
particular e-shop. Typical examples for penalizing
are as follows:
 the goods are not in stock - only on
request
 the goods cannot be taken away by
person
 the goods cannot be sent on the cash-
on-delivery basis
 the goods cannot be paid by cash, by
bank transfer, by credit card
 the goods are available only based on
inconvenient modes of transport
The entire pricing process can be seen in the
following flowchart (Figure 2).
Start
Finish
Calculatebasic
valueof rating
basedonpri ce
Score:100–50
Productissold
bye‐shop?
Yes
Setratingto:0
No
Existssome
penalty?
Penaltyscorefor:
Toorderproduct,
Personal
consumption,
Cashondelivery,
Wire transfer,
Creditcard,
Transport,
Additionalservices
Minus:0–30
No
Yes
Figure 2: Product rating flowchart.
5.2 Market Position and Its Analyses
If we multiply the above result by the significance
percentage and sum up these results for all the
relevant products defined by us, we get the
assessment of our offer and the offers of the
competition, where the higher score represents a
better result. By sorting out the list of competitors in
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10

accordance with the calculated criterion, we get the
current market position (Elakehal, Padget, 2012).
Using the comparative analysis, we can compare
our position with the best competitors. In this way
we can find out in which attributes and values we
are lagging behind. Subsequently we can work on
these indicators and correct them.
We can also use the so-called differential
analysis, where we try to identify the areas in which
a few or no competitors are active. If these areas are
relevant to our customers, we can offer them new
options and services.
5.3 Frequency of the Market Position
Analysis
Just as it is important to update regularly the
development of the product prices and availability, it
is necessary to upgrade the market position rating.
It often appears that the competition is doing
nothing and that their changes at the level of partial
products are negligible, but still they can be of great
importance on a global scale.
Our monitoring has shown that small but regular
changes and sensitive price adjustments (not only
price reductions, but also price increases) of the
products are much more efficient in the long term
than dramatic actions, discounts and clearance sales.
The sellers who sell at discount prices are losing
their own profits and often have to sell much more
to achieve the same profits as those who sell without
discounts, not to mention the increased costs of
distribution, complaints and similar services.
In the on-line solution implemented by us, the
users can define the relevant products, product
groups and all the criteria described above.
This is subsequently followed by the process of
gathering the necessary data and generating detailed
reporting assemblies, both to determine the global
market position and to identify the position of the
individual products.
In addition, the system offers the possibility of
defining the control and decision-making rules,
where it is possible to define the conduct of an
expert, who based on the selected sales and
marketing strategy may recommend the appropriate
corrections to the prices and services provided.
6 THE METHOD OF
MARKETABILITY RATING
The most common user question is: Whether and at
what price the product is sold? The answer to this
question can be found in the process of monitoring
the product sales prices and their availability. The
evaluation principle is relatively simple.
If in the previous iteration, the e-shop did not
have and offer the product in stock and now it has it
in stock, it cannot be predicted whether the given
product was sold in the meantime and at what price.
If in the previous iteration the e-shop offered the
product in stock and now the product is out of stock,
it can be assumed that in the meantime the product
had been sold for the formerly ?withdrawn?
(adjusted) price. The same applies if the e-shop
indicates on its website a certain number of available
products and this number changes again (decreases)
downwards.
A problem may occur in the case when the
number of products to be sold changed (decreased),
but the price in the given period has also changed
(increased or decreased). Then we cannot say with
certainty whether the product was sold for the
original price or for the current price (Figure 3).
Start
Selectconcrete
e‐shop
Getprevious:
Productstock
count,
Product pr ic e
Previous
productstock
countis0?
Unpredictable
Sale
Yes
Getcurrent:
Productstock
count,
Product pr ic e
No
Count
previous=
current?
Yes
Count
previous>
current?
No
No
Price
previous=
current?
Yes
Productwassold
for:
Givenprice
Yes
Finish
Predictablesale,but
unpredictablepr i ce
No
Figure 3: Marketability flowchart.
TheMethodofAutomatedMonitoringofProductPricesandMarketPositionDeterminationinRelationtoCompetition
Quotes-MonitoringofProductPricesandMarketabilityDevelopmentwithContinuousAssessmentofMarketPositionin
on-LineSales
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In the chapters above, we have also indicated
how to obtain information about sales within the
auction systems.
7 DESCRIPTION OF THE
IMPLEMENTATION
The procedures and methods described above have
been experimentally implemented within the specific
research of the Mining University (VŠB), Technical
University of Ostrava.
The implementation section is divided into the
so-called crawler layer that continuously retrieves
data from product aggregators and auction systems
and accesses the e-shops as such. This layer is
implemented as a multi-threaded Java application.
MySQL was chosen as the primary database for the
storage of downloaded data as well as the calculated
intermediate results.
7.1 Extraction of Relevant Data
After the data have been downloaded, they are
extracted, both of the websites obtained from the
aggregators, where the sets of records are extracted,
as well as from the specific e-shops.
There are import templates defined for each e-
shop that describe the structural content of the
website and are able to extract effectively the
desired information. The tool allows to analyze new
websites, load new structure and in a visually
acceptable form (without knowledge of the
implementation of website presentations) to define
the places where the relevant information (prices,
availability, etc.) is located. The system is also able
to manage identification of multiple variants and
product prices within a single webpage.
7.2 Presentation Layer
The presentation layer is implemented over the PHP
technology with the Nette framework (with respect
to the choice of the open source software). The
HighCharts component is used for the presentation
of graphs. The initially intended visual
representation using the responsive CSS Framework
Metro UI (Figure 4s) was replaced with the ACE
template comprehensive solution based on Twitter
Bootstrap.
The presentation layer also includes the ability to
export the results in the CSV, XLS, XML formats
for additional processing.
Figure 4: Marketability flowchart.
7.3 Optimization, Deduplication and
Security
In the context of the analyses conducted, there are
works carried out even for relatively small projects
with large amounts of data in terms of their
transmission, processing, subsequent storage and
reasonable reporting.
Here, an important role is also played by the
continuity and smoothness of the process of
obtaining information because failures in the
downloading process cannot be replaced by
anything, because pricing is a constantly changing
dynamic process.
For the projects, it is also necessary to deal with
the query deduplication over the product
aggregators, auction systems and the sales websites.
It is very likely that the system will be also used for
analyses by competing projects, which would want
to evaluate each other. It is necessary to eliminate
duplicate requirements and especially to prevent the
possible abuse of the resulting analyses.
Each user brings into the system part of their
personal knowledge and experience with a given
market segment. They propose their own
assessments and metrics for comparing the projects.
It is therefore necessary to ensure thorough security
ICE-B2014-InternationalConferenceone-Business
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and backup of user accounts to prevent the stealing
of such critical information.
7.4 Objectives of the Implementation
and the Related Modules
At present, the application is fully localised in the
Czech language and is oriented on the Czech on-line
sales environment. The extension of the scope of
operation is being prepared for the future within the
European Union.
The entire solution should be integrated into a
comprehensive solution, which - besides solving the
pricing policy and the price developments - will also
deal with the other aspects of on-line commerce,
such as monitoring the positions in search engines,
SEO optimisations, finding similarities within the
same or competing websites, analysis of backward
references and operation on social networks. The
system is implemented on a modular basis so that
partial results of the different modules can be
mutually combined and assessed.
The system can also integrate external data
sources, such as foreign exchange lists, commodity
prices developments, demographic data and
sociological or statistical results.
8 CONCLUSIONS
The principles and procedures described herein are
reflecting the current state of the development of the
tool for the analysis of competitive quotations and
the determining of global market positions. All the
results published herein have been verified in
practice under real projects. Currently, a pilot launch
of the project is under preparation for the public.
The project is oriented with its focus on small and
medium-sized entrepreneurs who do not have
enough time and human and financial resources to
analyse such large collections of data. The
implemented system should automate and streamline
this entire process and make it available for any
common user.
We will welcome any comments, suggestions for
improvements or opportunities for cooperation and
joint research in this practice-oriented field of e-
commerce. The aim is to give the ordinary users
comprehensible facts, which will help them
streamline and further develop their business.
ACKNOWLEDGEMENT
This work was partially supported by the SGS in
VSB Technical University of Ostrava, Czech
Republic, under the grant No. SP2014/217, and
grant No. SP2014/211.
This work was partially supported by the
Development of human resources in research and
development of latest soft computing methods and
their application in practice project, reg. no.
CZ.1.07/2.3.00/20.0072 funded by Operational
Programme Education for Competitiveness, co-
financed by ESF and state budget of the Czech
Republic.
REFERENCES
ZHANG, L.Y., SHI, Y.J. and LU, Q., 2014. Consumer's
decision-making behavior in online shopping: An
integrated analysis. Applied Mechanics and Materials.
YANG, Y., LIU, H. and CAI, Y., 2013. Discovery of
online shopping patterns across websites. INFORMS
Journal on Computing, 25(1), pp. 161-176.
ZHAO, Y., SUNDARESAN, N., SHEN, Z. and YU, P.S.,
2013. Anatomy of a web-scale resale market: A data
mining approach, WWW 2013 - Proceedings of the
22nd International Conference on World Wide Web
2013, pp. 1533-1543.
ZHANG, H.-. and ZHONG, H.-., 2013. The optimal
pricing of E-commerce market with network
externalities, International Conference on
Management Science and Engineering - Annual
Conference Proceedings 2013, pp. 126-132.
FELFERNIG, A., JERAN, M., NINAUS, G.,
REINFRANK, F. and REITERER, S., 2013. Toward
the next generation of recommender systems:
Applications and research challenges. Smart
Innovation, Systems and Technologies.
HAJLI, M., 2013. A research framework for social
commerce adoption. Information Management and
Computer Security, 21(3), pp. 144-154.
ETZION, H. and MOORE, S., 2013. Managing online
sales with posted price and open-bid auctions.
Decision Support Systems, 54(3), pp. 1327-1339.
WANG, J., ZHANG, Y. and CHEN, T., 2012. Unified
recommendation and search in e-commerce. 8th Asia
Information Retrieval Societies Conference 2012.
MIKIANS, J., GYARMATI, L., ERRAMILLI, V. and
LAOUTARIS, N., 2012. Detecting price and search
discrimination on the Internet, Proceedings of the 11th
ACM Workshop on Hot Topics in Networks, HotNets-
11 2012, pp. 79-84.
ELAKEHAL, E.E. and PADGET, J., 2012. Market
intelligence and price adaptation, ACM International
Conference Proceeding Series 2012, pp. 9-16.
TheMethodofAutomatedMonitoringofProductPricesandMarketPositionDeterminationinRelationtoCompetition
Quotes-MonitoringofProductPricesandMarketabilityDevelopmentwithContinuousAssessmentofMarketPositionin
on-LineSales
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