Online retailers do invest a lot of time and money in online marketing strategies in order to bring their own store to potential customers’ attention despite the lack of transparency of the Internet. As soon as that succeeded another hurdle is to be taken – the visitor has to be turned into a (buying) customer. Besides the navigation categories crucial importance is assigned to the store-intern search function, especially if there is a comprehensive assortment of goods.
Here, the conversion-rate’s dependence on user-friendly search software is very significant. The more target-aimed the product search is the higher is the probability that the customer actually purchases something. Well-polished, reliable, convincing product data provide the basis for that. On the one hand they strengthen the customers’ trust in the retailer on the other hand they include a crucial competitive advantage- products can be found faster and more efficient than in stores of competitors.
The virtual shop assistant
Visiting an online store, most of the users do still search for something in particular. Up to 80 percent of all users utilize the store-intern product search since the majority considers it to be the only navigation way to the searched product. Primarily, colloquial terms or keyword features that the required product should have are searched. Usually, they do not match the exact title. It is consequently not given that the visitor actually finds what he is searching for. If the worst case scenario occurs he leaves the shop not having purchased anything.
The majority of online retailers still underestimates the importance of the searching function – in most online stores it only works rudimentary. However, after all 40 percent of all store operators use an optimized product search what could be shown by a Survey of the project ecommerce guideline by the Regensburg University.
An intelligent search software is supposed to lead the customer to the right product like a shop assistant does. It is essential to construct the way to the desired article as efficient as possible. The display of a list of results has stopped to be enough to achieve a user-friendly product search long ago. The software is also implicitly demanded to add fitting keywords, synonyms and product pictures to the search word (Auto-Suggest-Function) and it has to offer alternative suggestions. Further, product-specific filters that vary for each offer should be contained (After-Search-Navigation) since the display has to be limited to relevant articles. The more product features can be found that way the higher is the probability that the requested article is being found.
For retailers, functions that enable one to influence the result ranking are important. By this means, marketing campaigns can by supported because currently promoted products are displayed above not promoted products. Furthermore, Analysis tools provide the possibility to exactly track what a user was searching and if he followed up on the result links he had been offered. Here, important information for marketing strategies can be gained.
Google as precursor
The trend of unifying and optimizing data feeds taken from different merchants has now also reached Google Shopping. Early in March 2014, Google announced a Reform for the Product Data Feed. Eventually, this data feed decides if and where an article is to occur in the Product Listing Ad – the display showing the relevant results. In the future, only correct, complete product data that conforms to the guidelines will be accepted. Data sets that do not meet the requirements are to be rejected and not published by Google. On the one hand, customers will be delivered better search results on the other hand retailers get a better advertisement performance because their products will be ideally found on Google Shopping. Now proceeding similarly to online market places and price comparison portals products can be compared and presented better. Google does put high requirements on retailers and their data feeds.
But: this is the crucial factor for increasing the accuracy of search results. Only consistent and complete data can make the product search in online stores and comparison portals a success factor. Even the most intelligent searching software can not work efficiently if the product data quality does not fit.
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