How to use data to increase e-commerce profit using Google BigQuery and Data Octopus?

The e-commerce market is developing extremely dynamically, posing new challenges for sellers. According to the IAB Polska report In 2022, the value of the online advertising market increased by over PLN 615 million, which translated into a growth rate of up to 10% and a record value of over PLN 6.8 billion. It is estimated that the number of online stores in Poland is between 60,000 and 80,000. The growth of the e-commerce market is developing in parallel with the increase in the importance of data in business. We are dealing with a drastic increase in their number and also in their dispersion. More and more sources generate data that is in different formats and often lacks a common denominator. On the one hand, we have access to an unprecedented amount of data, and on the other, there are no solutions that allow for semi-automatic or automatic analysis and activation. According to a report prepared by PWC in 2023 entitled “Cloud in business, leaders see the value” 38% of companies in Poland have implemented the cloud in all or most areas of their operations. For comparison, this coefficient for the USA is over twice as much, 78%. Moreover, as we learn from the report, 86% of companies that do not currently rely on the cloud plan to transfer all or more than half of their operations to the cloud in the next 2 years. How to design and implement e-commerce growth in such an environment? How to invest in cloud solutions, your own data and their activation? These are just selected questions that more and more e-commerce leaders will have to answer. Solutions such as Google BigQuery, i.e. cloud data warehousing based on Google Cloud, and Data Octopus, i.e. a product data management platform natively using this environment, come to the rescue. What problems can Data Octopus solve for your store?

To achieve business goals and acquire an increasing share of the market, e-commerce companies must keep up with dynamic changes. They result mainly from technological development, but also from changes in consumer thinking. As a result, entrepreneurs face challenges such as:

Growing amount of data – sellers can use an increasing number of systems that generate their own data, i.e. first party data. They are an invaluable source of information and can be used to discover consumer insights and implement necessary changes in business. However, this requires both time and competences, which are often simply lacking in e-commerce companies.
Limited resources – if you run an e-commerce business, you are probably well aware of the constant lack of time. Reports indicate that companies also lack digital and analytical competences. There are too few specialists on the market who can operate predictive models and create valuable recommendations based on them,
Opting out of third party data – next year, advertisers will experience significant restrictions on the use of third party data. To maintain the ability to effectively target campaigns, entrepreneurs will have to make even better use of the information they obtain on their own. Whoever turns this threat into an opportunity sooner will gain a significant advantage over the competition.
Decline in margins and profits – due to the digitization of society, more and more online stores appear on the market, and the requirements of the Polish consumer are constantly growing. This obviously translates into increased competition, price wars, and therefore a decline in the profitability of e-commerce companies.
Costs increase – you are probably well aware of current prices and see how, for example, the costs of logistics, human resources or B2B services are increasing. Growing expenses expose online stores to losses. As a result, even high turnover does not guarantee them high profits.
Market transformation – consolidation of the e-commerce market in Poland and the growing role of large players (such as Amazon or Zalando) may also be a challenge for sellers. Smaller companies that want to survive must learn to use their first party data to compete for customers. They should also start to use the potential of marketplaces that are gaining importance and become interested in international expansion.
Changes resulting from the entry of Google Analytics 4- did you know that without connecting Google Analytics 4 with Google BigQuery, you lose access to the data after 14 months and will not be able to generate a report or analyze it? Only this fact is a sufficient reason to make a decision to invest in cloud solutions such as Google Cloud and BigQuery. Additionally, you must remember that the data available in the GA4 panel is sampled and cardinalized, resulting in only a fragment of the image.

As you can see, running e-commerce – despite technologies that make it easier to reach customers and handle sales – is becoming more and more demanding. The solution may be a decision and action aimed at collecting and processing data about products, users, sales effectiveness or other contexts from multiple sources.

How does Data Octopus work with Google BigQuery?

Data Octopus is a Product Data Management platform based on BigQuery, which is a kind of “data warehouse”. Google’s cloud environment also guarantees full application compatibility, high efficiency and a high level of security. The main problem that Data Octopus addresses is investing advertising budgets in the sale of products that are unprofitable from a business perspective. By combining data from various sources at the product level, the system automatically identifies those that do not meet specific requirements and limits their exposure in a given advertising system or marketplace.

The generated value can be divided into 2 main buckets:

Reduction of costs and resources– the platform will help you reduce expenses on IT resources and PPC. It will do this by enabling advanced database operations without advanced knowledge of SQL or by creating product feeds directly by the digital department, not the IT department. Additionally, thanks to the use of rules and strategies, some processes are automated. The result of limiting investments in products that have, for example, low inventory and low sales effectiveness (ROAS) is a reduction in the advertising budget.

Maximizing profits – Data Octopus will also allow you to optimize your advertising budget, because you will only invest in products that help you achieve your business goals. As a result, the ROAS (return on advertising spend) of your store will increase. Even if you do not increase your revenues, overall you will still ensure higher profits, and this is what business is all about, especially in times of growing competition, falling margins and increasingly higher costs. To sum up, Data Octopus may be useful to you if:

you invest part of your advertising budget in selling unprofitable products,
you have limited digital and IT resources,
you sell through at least 3 advertising channels, such as Google, Ceneo or Empik,
Your data about products and their profitability are scattered,
you do not use strategies to select products for promotion in a given channel,
you do not have a central cloud-based data warehouse.

7 steps to increasing the profitability of database-based e-commerce – implementing Data Octopus

You may think that implementing a data-driven platform like Data Octopus is a very complicated procedure. Although its operation does require some specialist knowledge, the supplier will connect it with your e-commerce in 7 steps:

Designing an e-commerce data ecosystem – establishing the communication process of Google BigQuery and Data Octopus with your data sources, as well as selecting the markets, sales channels, advertising systems and reports that interest you. This is where designing a data ecosystem begins.
Configuring Google Cloud Platform and the Data Octopus environment – creating a Google BigQuery project and configuration and gaining access to key data sources and advertising accounts. At this stage, we determine how to connect your data source to BigQuery and Data Octous. It is important that Data Octopus can serve both as a connector for writing data to BigQuery and as an importer based on data already stored in it.
First party data migration – transfer of current and archived data on products and their sales effectiveness to Google BigQuery. This is where your investment in 1st party data begins.
Data cleansing – organizing raw input data and preparing views that will be used for reporting using Looker Studio. The most time-consuming stage, during which you have to deal with raw data that differs from each other and is often not the same as what we see in the advertising or analytical system panel.
Data import – downloading the main product file and additional information from external sources to the Data Octopus application, which will be updated on an ongoing basis. You can connect multiple feeds, multiple CSV/XML files or Google Sheets. There are also no limits to the number of tables that can be imported from Google BigQuery. This is the stage during which we “do a lot” when it comes to information about the product in terms of its attributes and sales effectiveness in multiple channels.

Data linking – selection of advertising channel, aggregation of additional product data and setting rules for each of them. During this stage, we decide where we want to advertise our offer. If we choose Ceneo, the application automatically maps input data to output data in the schema required by Ceneo. However, this is not the end, because the user can flexibly expand this schema with additional fields with product data that come from previously connected imports. The result is the combination of many data not only about the product’s features but also its sales effectiveness within one model, providing dynamic custom labels for products that change based on the input data. An example is the “Bestseller” label for products that consistently record good sales results and effectiveness.
Defining the strategy – determining the conditions that a product must meet to appear in a given advertising system, price comparison website or marketplace. It is at this stage that we determine what rules will govern which products will be displayed in a given advertising channel. An example of a strategy may be the conditions stating that it must be a product of the manufacturer Nike, with free delivery, price below PLN 200, ROAS of at least 1000%.

Using the cloud to work with data as a “New Wave”

Investing in data and its activation using cloud technologies is another “Next Wave” in digital marketing, especially for e-commerce. A business that ignores this risks reducing the effectiveness of advertising activities and the resulting profit. AI/ML solutions provided in the form of products such as BigQuery ML or Vertex AI will increasingly become part of everyday life, making it easier to create predictive models or generate content using artificial intelligence. The key will be to activate data, not just generate it in raw form. Interesting times are coming, opening new opportunities requiring new competences and technologies.