Correct revenue in Google ads that will improve your return on investment

Lukas Piątek
Data analysis
Sep 4, 2020

Over the last years, there has been a dynamic development of Google systems, both the Google Ads advertising system and the analytical Google Analytics (often providing data on the revenue from the sale of products). The popularity of the above-mentioned applications brought about the modernisation of the solutions for creating advertising campaigns. Such activities enable marketing specialists to set fewer and fewer functions in a search engine. It is worth noting that the campaigns acquiring application installations have been considerably automated, and recently this also happened to graphic campaigns in the search engine, as well as to smart campaigns in the advertising network (Smart Shopping and Smart GDN).
In view of the continuous development of the Internet marketing industry, it is worth considering what actions should be taken in a situation where the work of a specialist is largely replaced by self-learning algorithms: machine learning, deep learning and cognitive computing systems.

What should be the response of the marketing industry to the development of machine learning technology?

A solution to this issue is to provide both technologies and analytical systems with more precise data in order to be able to acquire better profiled customers, and thus to improve the databases. Furthermore, it is worth that the owners of online stores realise the importance of the need to introduce new business solutions - apart from digital - and thus implement an agile work methodology affecting a better understanding of business needs, as well as a fuller use of the opportunities and awareness of employees in terms of reading information and the selection of goals based on new enriched data. ERS (effective revenue share) indicator can be such a goal.
Practice shows that very often online stores generating higher sales revenues have their own business optimisation systems, which nevertheless are not directly integrated with marketing, and moreover, accounting and balance sheet are usually settled taking into account net values. Agile owners and managers take into account net indicators when setting business goals (e.g. net ERS, then net profit).

What are the sources of the problem of e-commerce reporting and tracking?

In 2014, Google introduced Enhanced E-commerce, i.e. an improved Google Analytics module dedicated to entities selling online. This functionality provides one of the key performance indicators (KPI) for internet sales, which is the information on gross sales.

Moreover, the second indicator often used directly in the advertising system is ROAS (return on ad spend), which determines the quotient of profit and sales revenue, thus allowing to determine the percentage return on sales. ROAS (inverse ERS indicator) can be set as an automatic strategy for building in the advertising system. However, advertising expenses are net, because no VAT is paid. This is because Google Ads is based in Ireland. Therefore, the invoices issued by this entity for the services provided determine the settlement of advertising costs. You have to be aware that they are different from national settlements and invoices.
It happens very often that the ROAS and ERS business indicators are calculated in a mathematically incorrect way, because for example, the accounting department takes into account net profit, while marketing department - gross profit, and besides there are also net advertising expenses. Therefore, the margin of error in the amount of VAT leads to overstating the expenses and reducing the profit on investment, which is advertising in Google Ads. And some online stores allocate up to several million per month for this purpose.

Specific metrics and technology come to the rescue

It is recommended that online store owners use the net ERS indicator. Then, their assumptions will be consistent with the data prepared by the accounting department, net advertising expenses, and the KPIs will be calculated in a mathematically correct way. For example, 10% ERS corresponds to 1000% ROAS.
It is also worthwhile for entities that sell online to undertake the creation of a tool called a data warehouse. Its task is to integrate the distributed data into one whole. Data warehouse enables the development of analyses and net sales reports. The last step is the integration on the data warehouse - the Google Ads advertising system plane.
The Google Ads system offers several smart strategies for establishing the rates in product campaigns, including preparing the rates for target return on ad spend (ROAS). After implementing a specific strategy, ROAS is net and the system is based on more accurate business information.
It is worth realising that more accurate data, a consistent approach of accounting and marketing departments, as well as the use of intelligent product campaigns mechanisms, are a perfect solution that improves the return on investment.

How can you build such an ecosystem in an efficient and cheap way?

The ready analytical platform provides a data warehouse (in the Google Cloud Big Query database), and the Witcloud platform module "Google Ads export" will send information about net revenues from Google Big Query to Google Ads. This solution was designed in such a way that, within two days, the data of a specific company with net revenue is transferred to the Google advertising system.

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