The best retailers are constantly searching for more efficient ways to advertise. Because although it is necessary to attract new customers, you want to ensure that every pound you spend delivers your content to the right audience. When you yourself are looking for a new product, your search almost always begins with Google. It is therefore not surprising that nearly all our clients advertise via Google.
After developing your campaigns, you will need to monitor how they perform closely, because you ultimately pay for every click or impression. Google has developed a clear dashboard for this, which you are probably already using to monitor your adverts. To subsequently perform your own analyses on all this data, you need to manually export this data each time via CSV files. You could then combine this data in ever-growing CSVs, to then load them into an analysis tool like Power BI. This often takes considerable time. You will also need to clean up files and make backups from time to time.
Centralising Google Ads data in my data warehouse
Google also offers an alternative: you can automatically unlock your own performance data with a self-built pipeline via the API. This automatic extraction then retrieves a number of important metrics monthly for each component.
This data is automatically retrieved and stored in a central location - your data warehouse. Here you can easily combine Google Ads data with other sources, for example from other channels such as Bing, Pinterest or Meta. This way you can easily see which adverts on which channels generate the most exposure or conversions. So you can ensure that every pound is optimally spent.
Further processing
Additionally, when analysing you can also make use of other automatic extractions. Think, for example, of weather data, which may explain why your advert performed very well in one particular week (when everyone was indoors because of the rain) and less so the week after (when everyone was at the beach). It may also be that your adverts generally attract the most audience in the evening. But since that was the only dry moment of the day, your results unexpectedly disappoint.
You will find that once your data stream is in good order, you are no longer limited by processes, but by what forms of analysis you can dream up!
For retailers, Google Ads data becomes especially valuable when it sits alongside sales, margin, stock and customer behaviour. Also view Datalab Retail Studio for a complete data foundation for retail, e-commerce, wholesale and D2C.