# 4.3 Combine business data in Google Analytics - Analytics Academy on Skillshop

## Метаданные

- **Канал:** Google Analytics
- **YouTube:** https://www.youtube.com/watch?v=fFOLyohQKjU
- **Источник:** https://ekstraktznaniy.ru/video/36721

## Транскрипт

### Segment 1 (00:00 - 05:00) []

(bright music) - First party data is data that you own and your customers have proactively shared with you. For example, your offline purchase data or your customer's information for loyalty programs. This data can provide valuable insights that help deliver better customer experiences and drive business results. First party data lets you create a competitive advantage as data you collect with consent is unique to your business, enhance your audience strategy as your data helps you understand your most valued customers, and tailor the messaging in your campaigns. Make informed business decisions as you can find out how users are engaging with your business and help steer product development. You can derive insights from first party data and use it to find new customers with similar in-market behaviors or develop more helpful ads for your users. The more data you have, the more accurate the insight you can generate will be, as bigger data sets can help you identify trends or outliers. These are two tools you can use to expand the first party data you have available in Google Analytics, data import and measurement protocol. First, let's take a look at data import. (bright music) Typically, each body of data you have exists in its own silo, uninformed by the other data you own. Data import lets you join all of this data in Google Analytics. Once imported, you can use your aggregate data to get a more complete picture of your customer activity and unlock new business insights. For example, if you sell products both online and offline, combining your sales data in one place can give you a more accurate view of how your products are performing. You could also import customer data for a holistic view of customers online and offline interactions with your business. You can also add metadata to data that's already been collected and processed by your analytics property. Let's look at the types of data you can import. Cost data, which would be data from non-Google ad networks, such as clicks, cost and impression data. Item data, or product metadata like size, color, style, or other product-related dimensions. User data such as loyalty rating or lifetime customer value that you can use to create segments and remarketing lists. And offline events from sources that don't have an internet connection or that otherwise don't support realtime event collection. To upload data to Google Analytics, you'll need to use CSV files. These can be created manually using spreadsheet software or exported from your CRM system. Let's show how you import a CSV file. Here's a CSV file we've prepared with example item data from the Google merchandise store. This data is specifically for clothing items like T-shirts, so we can use this to provide additional information, like color, that will enrich the already collected item data. To import this data, we'll go to admin in our analytics property. Under data collection and modification, click data import. Choose create data source, then name the source of the data. For this example, we'll put clothing details. Select the type of data, in this case item data, select manual CSV upload, then click upload CSV. Select the CSV file on your computer, then click open. Click next to proceed to the mapping stage, select the analytics fields and imported fields you want to map to one another. For example, we'll map the item IDs in the spreadsheet to the item IDs already collected by analytics off the website. Edit the field names as necessary. Since we're importing color metadata, we'll use the variant field to map “item_color” too. Once you're finished, click import. Once the data is processed, this offline data will be joined with the data analytics already collects. This more complete data enhances your reports and can be used for comparisons and audiences. Now that you know how to connect your data using data import, let's learn a bit about measurement protocol. (bright music) Measurement protocol is a way to send offline event data directly to Google Analytics. It's typically used to send data from an offline data system like a CRM or a credit card validation system and allows you to send that data asynchronously so it happens after the event you collect on your website or app.

### Segment 2 (05:00 - 06:00) [5:00]

To send events to analytics using measurement protocol, you or your developer can build these new events using the event builder tool. This tool will walk you through the steps to create a new event and then validate the event setup. For example, if you own a resale business, you may want to analyze customer behavior, both online and in your physical store to understand how customers interact with your brand across touchpoints from browsing online to visiting the store and making purchases. To accomplish this, you could use measurement protocol to send purchase data from your point of sale system in your store to Google Analytics. You can use the event builder tool to build an in-store purchase event and send parameters like product ID, quantity, price, and payment method. You can then use the tool to validate the event setup. Then once you start sending these events, you can use their real time report to verify that data is reaching your Google Analytics property. Using data import and measurement protocol to combine additional data with the data collected by Google Analytics provides a more comprehensive data set for you to use when analyzing and making decisions for your business. (upbeat music)