A lack of data
The reason search engines don’t produce the best results is that they lack data. They have less data about the business that is searching for another company. They also have a lack of data about companies that have optimised themselves to rank high on searches. Without access to sufficient data about companies, search engines spew out results that are not very useful.
Even when keywords entered in search engines are changed to make search results more relevant, the output may not be very different. For this reason, there is a need for service aggregators. Services aggregators understand every business registered with them and the requirements of companies looking for services.
Powered by Data and Machine Learning
The advantage of searching for a business on a service aggregator is that such platforms have massive amounts of information about the companies registered on their sites. Such information, and data shared by firms that want to partner with a registered business, gives rise to partnerships that work.
A service aggregator considers dozens and sometimes even hundreds of data points before displaying a result. Hence an apparel manufacturer that needs the services of a digital marketing agency will undoubtedly be paired with a firm that has experience serving players in the apparel arena.
Another advantage of using service aggregators is that after a search is made, they display only a limited number of the best-suited results. Unlike search engines which display pages of results most of which are of little use, dedicated service aggregators are more discerning. They show only those firms that are likely to be best partners of the business that entered the search query.
Using data to the fullest extent
A service aggregator uses complex algorithms to find firms their ideal business partners. Furthermore, it continuously collects data about businesses registered on its portal and about firms on the lookout for new business associations. By running data through intelligent machine learning algorithms, a service aggregator produces more relevant results with each passing month.
When a service aggregator finds that an apparel manufacturer needs the services of a digital marketing agency, its algorithm searches for digital agencies whose work has been praised the most by apparel manufacturers. The aggregator considers multiple data points such as the ratings provided by businesses that used the services of digital agencies, how many repeat orders a digital agency gets, its overall score and much more. The algorithm also considers the needs of the apparel manufacturer. A manufacturer of western apparel may have different demands than one that manufactures ethnic clothing. Using such information, the service aggregator will pair businesses with the best companies.
Data, machine learning algorithms, and a low number of precise results are what make service aggregators so good at pairing businesses. They have developed in-house intelligent algorithms that can sift through thousands of data points to produce output that best matches queries. By continuously collecting data, such aggregators provide more relevant results than they did the week before.