Get Data to Table

To streamline the transfer of your marketing data from platforms like Google Ads and LinkedIn Ads into Google Sheets via Adzviser (opens in a new tab), follow these simple steps:

• Choose your workspace.
• Pick the account(s) you wish to analyze.
• Specify the date range(s) of interest.
• Select the metrics and breakdowns you need for analysis.
• (Optional) Choose the time granularity for your data.

Step 1: Choose your workspace

A workspace acts as a container for your accounts, allowing you to efficiently organize them. It enables the simultaneous querying of multiple cross-channel accounts. To choose a workspace, simply click on its name. By default, your initially created workspace is pre-selected for convenience.

Step 2: Pick the account(s) you wish to analyze

Within your workspace, you have the flexibility to analyze single or multiple accounts concurrently. This analysis generates separate worksheets for each account. To switch between accounts, select the desired account name from the dropdown menu.

Step 3: Specify the date range(s) of interest

Define one or more date ranges for the data retrieval, tailoring the information to your specific needs. Note that setting either the start or end date in the future is not permitted due to the reporting nature of the data.

Step 4: Select the metrics and breakdowns

• A metric is a quantitative measurement. It represents data that can be measured and expressed in numbers. Metrics are used to track performance or behavior. Examples include clicks, impressions, conversions, revenue, etc.
• A breakdown is a qualitative attribute or descriptor. It provides context for metrics by categorizing or segmenting them. Breakdowns are text. Examples include country, channel, campaign name, date, etc.

Both metrics and breakdowns can be easily found and selected via a search or dropdown menu.

Step 5 (optional): Choose time granularity

Time granularity allows you to choose the level of detail for time-based data segmentation. Whether you require a daily, weekly, or monthly analysis, setting the time granularity helps in tailoring the data's temporal resolution to meet your specific analytical needs. This feature ensures that you receive the most relevant and useful insights, tailored precisely to the timeframe of your analysis.