How to increase remarketing efficiency with data from your CRM
If you have a large database of purchases and customer preferences, your marketers can use it for effective targeting, giving you a competitive advantage. You can enrich Google Analytics data with information from your CRM system and create audiences based on this combined data for remarketing and email newsletters.
Table of Contents:
- Why do you need data from your CRM for remarketing?
- How to connect your data
- Step 1. Export data from Google Analytics to Google BigQuery
- Step 2. Upload data from your internal system to Google BigQuery
- Step 3. Process data in Google BigQuery
- Step 4. Import data into Google Analytics and create remarketing audiences.
- The result
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Why do you need data from your CRM for remarketing?
But why combine data at all, and why aren’t the standard Google Analytics features enough? When you create an audience in Google Analytics, you can only target users from the moment they reach that audience. That is, users first have to fulfill certain conditions. If a customer has not recently been active on your site, they won’t fall into targeted segment.
For example, say that a customer bought a stroller more than three months ago, and after that did nothing on the site. The purchase was a long time ago, so the customer doesn’t fall into the desired Google Analytics segment. However, we know this customer is interested in the Baby Products category, and this information is in the internal database. So why not benefit from it?
How to connect your data
For collection and processing, we recommend using Google BigQuery for cloud storage. There are several reasons for this:
- Inexpensive and transparent fees – You’re charged only for BigQuery resources you use.
- You don’t need to start additional servers to cope with increased data volumes.
- Thanks to ready-made libraries, BigQuery is easy to integrate with other services, visualization tools, data analysis tools, etc.
- Security certificates allow you to store even personal information about customers (name, phone number, credit card number, etc.) in BigQuery, which you cannot do in Google Analytics.
To get the most out of your accumulated data, you can:
- Export user activity data from Google Analytics to Google BigQuery.
- Upload to Google BigQuery customer and purchase information from your internal CRM / ERP systems.
- Process data in BigQuery to form segments.
- Transfer data from BigQuery to Google Analytics and create remarketing audiences.
Data will be combined according to this scheme:
Let’s take a look at each step.
Step 1. Export data from Google Analytics to Google BigQuery
There are two ways to transfer unsampled user behavior data from a site to Google BigQuery:
1. For users of the paid version of Google Analytics 360, BigQuery Export is available. Data for the current day is collected in an interim table and updated every 8 hours. The final table is formed the next day, and the intermediate table is deleted. For an additional fee, you can activate streaming export to a separate table where data will be updated every 15 minutes.
2. If you have standard Google Analytics, you can use OWOX BI to collect unsampled data. OWOX transfers information to Google BigQuery directly from your site, in parallel with Google Analytics tracking.
Because data on user actions on the site gets into your Google BigQuery project in almost real time, you can quickly send trigger messages, turn off inefficient campaigns, and redistribute your budget.
You can learn more about the differences between these methods in our article on how OWOX BI differs from Google Analytics 360.
Step 2. Upload data from your internal system to Google BigQuery
To set up remarketing, you may need the following data from your CRM:
- Personalized user data: emails, order and subscription statuses, activity information, loyalty card data, etc
- Data on orders and returns
- Data on SMS campaigns, promotions, etc. held at different times
You can import this data from your CRM to Google BigQuery on your own or with the help of developers.
Collecting all this information in a single repository will simplify the lives of your marketers. Having data in one place makes it easier to correlate disparate data and find useful insights for your business. Here are some examples of how a company can use combined data from BigQuery.
Example 1. The popularity of filters
By examining user behavior on catalog pages, you can identify the most popular filters. Then you can rank them and display a drop-down list ordered by relevance.
Example 2. Improving internal search on the site
Marketers for an online store can analyze the interactions of site visitors with internal search to make it more comfortable and effective by displaying the most relevant offers, identifying and processing requests that lead to empty prompts, etc.
Example 3. Recommendation blocks
Thanks to Google BigQuery, you can opt out of third-party services to display recommendations on your site. Instead, you can have your own tool that lets you control the display logic and improve recommendations in the Popular Products, Buy Together with This Product, “Also Interested, and other blocks.
Step 3. Process data in Google BigQuery
Having collected all the necessary data in Google BigQuery, you can use SQL queries to assign users characteristics by which segments will be formed.
Note: Before sending segment information from BigQuery to Google Analytics, review the types of data you can import.
Step 4. Import data into Google Analytics and create remarketing audiences.
With OWOX BI Pipeline, you can configure data uploading from Google BigQuery to Google Analytics. This tool automatically imports segments into the desired dataset in Google Analytics. If the volume of data to be imported exceeds the limits of BigQuery, OWOX BI automatically divides the data into several portions and deletes old files with previous data uploads.
There are two ways to create remarketing audiences:
- Transfer an aggregated variable to Google Analytics that includes identifiers of various user segments. That is, each value in this variable is responsible for a specific segment. Then, using regular expressions, select the categories that are necessary to create an audience.
- Transfer specific characteristics of users (Custom Dimensions) to custom dimensions, which then create a segment in Google Analytics.
By importing data from your CRM to BigQuery, you’ll receive additional value from the data stored in your client database. Using Google BigQuery and OWOX BI, marketers can associate each user with their history of orders – for example, in the last 10 categories with which they interacted. Marketers can also enrich user data in Google Analytics with information from personal accounts: gender, age, interests, etc.
Then, based on this combined data, marketers can form audiences and send them to Google Ads and Display & Video 360 to use for remarketing and bid adjustments. With this approach, you’ll significantly increase the size of your audience.
P.S. If you want to use data from your CRM to build audiences but you don’t have the paid version of Google Analytics, try OWOX BI. You can set up pipelines and import data from Google Analytics to Google BigQuery (and vice versa) for free. If you have any questions, leave them in the comments. We’ll be happy to help.