Infoshina is an online store that specializes in selling car tires and rims for vehicles, offering both self-pickup from their own stores and nationwide delivery. They are a direct importer of tire brands such as Continental, Gislaved, Michelin, Goodyear, Bridgestone, Kelly, Debica, and others.
The specificity of the Infoshina niche involves a significant number of additional product characteristics that customers specify during their search and consider for further selection. The website addresses this need through filters. However, apart from the existing loyal customers of the brand, it is crucial to attract new customers who are searching for a specific product with certain characteristics on search engines.
Before the implementation of the new system, user queries that matched the website filters (e.g., tire size "195 65 r15") were used in search campaigns. However, these queries were manually updated by specialists, leading to a number of issues:
If certain characteristics were still being used in the ads, specific products like "Michelin Alpin 6 205/55 R16 91H" might not have had dedicated search campaigns created for them.
There are two ways to increase the relevance of advertisements and increase the number of transactional queries from advertising:
Among the disadvantages of the first approach are the inefficient use of technical specialists' time and a high probability of errors during configuration. As a result, the project's cost may increase without profitability, and there may be a decrease in focus on other tasks, such as strategic planning and conducting experiments.
The optimal solution for a retailer with such a large assortment, like Infoshina, has been to configure the automation of the process of creating and managing search campaigns. This has opened up the possibility of automatically creating relevant ad groups for specific products and specifying more characteristics that align with the website's filters.
Configuring automatic creation and management of search campaigns became possible thanks to the tool G-MOS, the internal development of Promodo.
G-MOS is an internal product of Promodo, a tool that helps work with model search queries (for example, Bamix Classic EO140) and display advertisements with up-to-date pricing.
G-MOS incorporates algorithms for processing information from feeds, whether they are .xml or .csv files. These feeds can include Merchant Center feeds used in regular shopping campaigns, as well as feeds specifically created for use within the service. G-MOS can work with any feed and its attributes, as long as it follows a consistent structure.
Through its integration with the Google Ads API, G-MOS enables the creation of ready-to-use search campaigns that automatically update based on changes in the feed data.
Google Ads API allows developers to create applications that interact directly with the Google Ads server. With these applications, advertisers and third-party developers can effectively manage large or complex Google Ads accounts and campaigns.
The automatic updating is made possible by uploading the feed into the service, where you can make your own configurations for campaign generation. As a result, the generated campaigns always have up-to-date prices in the ads and accurate status for ad groups.
The advantage of G-MOS, compared to other automation services, is its ability to work not only with feeds containing products but also with feeds that can include any pages of a website: articles, job vacancies, search results, filters, events such as concerts or exhibitions.
Workflow of the Service
The data feed is transformed into the desired representation of groups and individual listings, as well as key attributes in the G-MOS database. Afterward, the database is synchronized with the Google Ads account.
During the configuration of a profile in G-MOS, attributes are set that the service will retrieve from the feed. For example, these attributes could include the product ID, model, brand, category, price, and so on.
According to the defined schedule, G-MOS accesses the data feed, generates new groups within the corresponding campaigns for new products, and updates information in the groups for products that already have existing ad groups. Following this, the database is synchronized with the Google Ads account.
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To ensure that the automation service has data for generating ads, the client has created separate feeds for each characteristic from the filters (e.g., tire size "195 65 r15", model "Michelin Alpin 6") and for specific product offers (e.g., "Michelin Alpin 6 205/55 R16 91H").
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The mechanics of the service were also relevant for tire models, since the site uses the Content API to transfer product data to the Merchant Center and does not have a separate product feed.
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After we uploaded all new feeds to G-MOS, the service automatically created search campaigns. Currently, they bring in up to +50% of traffic from search.
The introduction of G-MOS helped to comprehensively solve the client's problems: increase the relevance of ads and, as a result, increase the volume of transaction requests from advertising campaigns.
Our automation service has helped Infoshina capture the previously untapped segment of traffic, processing it in its entirety. Currently, G-MOS enables the brand to swiftly handle large volumes of data, even up to 3,000,000 products simultaneously. The advertisements themselves are generated only from available products with up-to-date prices.
Implementing these solutions has significantly reduced the likelihood of errors that could occur during manual campaign management.
The synchronization of work with the client has facilitated efficient campaign configuration, aligning profitability, brand presence, product availability, and establishing priorities in search advertising operations.
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