Product search engine
A product search engine is a special type of search engine that searches through structured article data that has been stored on a computer or network - for example on the Internet. A product search engine is often equated with a price comparison portal and acts as an intermediary between retailer and consumer by displaying article data aggregated on a platform. The search engines mostly work across retailers and thus provide consumers with a transparent overview of products and prices. In addition to simply providing item details and price information, some product searches also provide real-time information and availability that indicate whether a particular offer is still in stock.
Types of product search engines
Online product search engines
An online product search engine, sometimes referred to as a price comparison website, price analysis tool, or shopbot, is a vertical search engine that allows buyers to filter and compare products based on price, features, ratings, and other criteria. Most online product search engines aggregate product listings from many different retailers, but they don't sell products directly themselves, instead making money from affiliate marketing agreements. Product search engines for online articles have been around since 2001. The competition in this segment is fierce, which has led some providers to specialize in specific product categories, for example electronics or technology.
An example of a large online product search is idealo.de . Test results, user opinions, price history and data sheets are made available for products.
Another is Google Shopping . Google has recognized that the demand for local offers on the Internet is also increasing. That is why Google introduced the “local shopping” feature in 2010. The group worked with selected retailers in development and is now also offering the availability of local offers.
The European Commission penalized Google with a record competition fine of 2.42 billion euros in 2017. The reason for this was the preferential treatment of the Google price comparison when listing search results. Google then converted its own product search into a price comparison platform with external providers in order to escape a ban on Google Shopping in the EU. Since then, all shopping ads that are displayed on Google have been part of a Comparison Shopping Service (CSS). Google Shopping itself is also one of the CSS ("From Google") and has to compete for the advertisement with the other price comparison platforms in a bidding auction for every search query.
Local offer searches
Local offers searches have been developing in the market since around 2008, with the idea of making local offers available online and thus offering retailers an online reach channel in addition to the print brochure. Such platforms give retailers the opportunity to reach households who do not want to receive print advertising in their mailboxes. Nevertheless, according to a study by the EHI Retail Institute, around half of all marketing expenditure in retail is still in the print sector, including the printing and distribution of advertising slips and catalogs.
The relevance of local search engines is increasing. According to a study by the Kelsey Group, 97% of consumers first look for products online before shopping locally. The following channels serve as a source of information:
- 90% search engines
- 48% search through online business directories
- 42% price comparison portals and product search engines
- 24% vertical niche portals
Mobile offer searches
The growth of the smartphone segment and the mobile Internet is also causing retailers to be mobile-findable. Users can find out about online and local offers using various apps . Barcode and QR code scanners are also partially preinstalled on the phones.
history
The first product search engine was BargainFinder, which was developed by Andersen Consulting (now Accenture). The team, led by researcher Bruce Krulwich, created BargainFinder in 1995 as an experiment and published the project without informing the listed e-commerce websites. The first commercial product search engine, called Jango, was produced by Netbot, a Seattle-based startup founded by Professors Oren Etzioni and Daniel S. Weld of the University of Washington. Netbot was taken over by the Excite portal at the end of 1997. Junglee, a Bay Area startup, was also a pioneer in online price comparison and was soon acquired by Amazon.com. Other early product search engine providers were pricewatch.com and killerapp.com.
In 1998 and 1999, various companies developed technology to search retailers' websites for prices and store them in a central database. Users could then search for a product and see a list of retailers and prices for that product. Advertisers didn't pay to be listed, they paid for each click on a store link. Streetprices, founded in 1997, was a very early company in the field. It invented price graphics and email notifications in 1998.
technology
Product search engines can collect data directly from retailers. Retailers who want to offer their products on a product search engine can also provide their own product and price lists as CSV or XML files, which are then compared with the original database. This data is then imported from the comparison website. It does this through a mixture of information extraction , fuzzy logic and human work. An important matching criterion of different shops for individual products is the European Article Number of the product (if available).
Some third party companies offer data feed consolidation so that product search engines don't have to import data from many different retailers. Affiliate networks aggregate data feeds from many merchants and make them available to product search engines as one file. Many of the popular product search engines offer a direct link to the shop that wants to become an affiliate partner. They provide the affiliate partner with their own API. This allows product search engines to monetize the products contained in the feeds by earning commissions on the click-through traffic (click on the shop link).
In recent years, many commercially available software solutions have been developed that enable website operators to use the inventory data from price comparison websites as a white label solution. This means that blogs can also place shop prices on their blog. A provider for this is z. B. Connexity (formerly Become). In return, the blog operators receive a small share of the revenue generated by the product search engines. This is often referred to as the revenue share model.
Another approach is to scour the web for prices. This means that the comparison service searches the retailers' websites to get the prices rather than relying on the retailers to deliver the prices using CSV or XML. This method is sometimes referred to as "scraping". Some, mostly smaller, independent websites only use this method to get prices directly from the shops they use for comparison.
Another approach is data collection through crowdsourcing. This allows the price comparison engine to collect data from almost any source without having to program a complex crawler or data feed processing system. Product search engines that use this method rely on visitors to contribute price data. Unlike discussion forums, which also collect input from visitors, product search engines using this method combine data with related input and add it to the main database through collaborative filtering, artificial intelligence, or human labor.
Most often, however, a combination of all three approaches is used.
Demarcation
In addition to product search engines, there are other specialized search services such as business directories, people search engines or job portals.
Individual evidence
- ↑ http://www.inc.com. Google Opens Local Shopping Feature to Small Businesses. Retrieved November 29, 2011.
- ↑ http://europa.eu. Antitrust law: Commission imposes a fine of EUR 2.42 billion on Google for abusing its dominant position as a search engine by improperly preferential treatment of its own price comparison service
- ↑ https://www.blog.google. Supporting choice and competition in Europe
- ↑ Future scenarios for communication in retail 2025. EHI, archived from the original on December 16, 2014 ; Retrieved February 4, 2016 .
- ↑ Kelsey Group ( Memento of the original from November 21, 2011 in the Internet Archive ) Info: The archive link was inserted automatically and has not yet been checked. Please check the original and archive link according to the instructions and then remove this notice. Consumer study - search online, but shop offline & locally. Retrieved November 29, 2011.
- ^ Shopping Price Comparison Scripts . Retrieved May 7th, 2010.
- ↑ 50/50 Revenue Share . Retrieved September 3rd, 2010.
