Digital Marketing has become one of the most popular techniques that businesses rely on to market their products. This is because these techniques allow businesses to reach a wider audience and efficiently measure the performance of their marketing efforts in a way that can be easily visualized and communicated to decision-makers. This allows them to plan future Marketing strategies and campaigns accordingly.
All these efforts to promote the products & services and plan strategies will be rendered useless if businesses are not able to understand the behavioral patterns of their customers and refine their products & strategies accordingly. One of the most popular tools used by businesses to track Customer Engagement is AppsFlyer. This article will help you understand how you can seamlessly migrate data from AppsFlyer to Snowflake to perform a comprehensive analysis of your attribution data.
Introduction to AppsFlyer
Appsflyer is one of the most popular Attribution and Marketing Analytics platform. The platform typically processes billions of actions every day, giving marketers and developers the ability to maximize return on their Marketing investments. AppsFlyer also houses numerous Marketing Analytics tools that enable Marketers, User Acquisition (UA) Managers, and Product Managers to quickly determine Customer Engagement and measure Return on investment (ROI). AppsFlyer users get seamless access to Retention and Cohort reports, Raw Data reports, Business Intelligence (BI) support, APIs, mobile access, and live alerts allowing them to get comprehensive insights and achieve marketing success.
Understanding the Key Features of AppsFlyer
The key features of AppsFlyer are as follows:
- Marketing Analytics: AppsFlyer offers users access to Cohort and Retention reports allowing them to get insights into Marketing performance and user retention, Engagement Activity allowing them to discover trends in user behavior, and Cost Reporting and Revenue Attribution enabling them to build an effective acquisition strategy by accurately calculating the Lifetime Value (LTV) and Return on Investment (ROI) of customers.
- Fraud Detection: AppsFlyer houses functionality to prevent its users from the threat of Mobile Ad fraud. It can detect and block fraud in real-time using its robust Machine Learning classifiers.
- Easy Integration: AppsFlyer allows users to make attribution data the foundation of their Marketing Tech stack through seamless integration with more than 6000 partners such as Facebook, Snapchat, Pinterest, Google Ads, Slack, etc.
Introduction to Snowflake
Snowflake is one of the most popular enterprise-grade Cloud-based Data Warehouses that brings simplicity to its users without reducing the features being offered in any way. It is capable of automatically scaling resources up and down based on data requirements to ensure that users get the right balance of performance and cost.
Snowflake is now widely used by a large number of businesses primarily because it separates Compute Nodes from Storage Nodes. This is considered to be one of the most significant advantages of using Snowflake since all other databases, or Data Warehouses offer Compute and Storage Nodes together as a single bundle. Earlier, businesses had to acquire resources based on the largest workload and incur its cost. But with Snowflake, they can choose to pay only for the resources they use.
Understanding the Key Features of Snowflake
The key features of Snowflake are as follows:
- Advanced Scalability: Snowflake houses functionalities that allow users to practically create an unlimited number of Virtual Warehouses with each one running its workload against the data in its database.
- Robust Security: Snowflake ensures that all data stored in its Data Warehouses is secure by implementing a wide variety of industry-leading and powerful security features, such as Multi-factor Authentication, Automatic 256-bit AES Encryption, etc. Snowflake is also compliant with numerous enterprise-grade data security standards such as PCI DSS, HIPAA, SOC 1, and SOC 2.
- Automated Performance Tuning: Snowflake offers its users an Automatic Query Performance Optimization mechanism backed by a robust Dynamic Query Optimization Engine in their Cloud Services Layer.
Methods to Set up AppsFlyer to Snowflake Migration
Users can set up AppsFlyer to Snowflake Migration by implementing one of the following methods:
Method 1: Manual AppsFlyer to Snowflake Migration
AppsFlyer offers a wide range of RESTful APIs that you can leverage to extract the required data in a row-level or aggregated format. Row-level / Raw Data Points include impressions, installs, clicks, etc., and Aggregated Data Points include aggregated impressions, filtering by a media source, etc.
It is important to understand that the data you are trying to extract from AppsFlyer may be limited by the current plan you are on. Hence, it is advised to understand the limits and level of access permitted by your AppsFlyer plan.
In the manual AppsFlyer to Snowflake Migration methods, you are going to extract data using PULL APIs. PULL APIs help the AppsFlyers users get a copy of their data in CSV format.
The steps involved in executing a data migration process from AppsFlyer to Snowflake database are:
Step 1: Extracting Data from AppsFlyer
To extract data from AppsFlyer, you can make an API call describing the data points you want to be returned. You also need to specify the Authorization Key and data range for which the data needs to be extracted. The format for the API call to request data from AppsFlyer is as follows:
https://hq.appsflyer.com/export/master_report/v4?api_token=[api_token]
&app_id=[app_id]&from=[from_date]&to=[to_date]&groupings=[list]&kpis=[list]
It is, however, essential to specify your unique API Token and App ID along with the date range and list of the parameters required in the above request to get a successful response. Each successful API request will return a CSV file that can be downloaded into the local system. Also read how to Integrate AppsFlyer to BigQuery in to time.
Step 2: Loading Extracted CSV Data into Snowflake
You can load CSV data into Snowflake by creating a Snowflake Stage and loading data from that stage into the Snowflake table. You can easily complete this process by implementing the following steps:
- Create a Snowflake stage by executing the following query:
create or replace stage appsflyer_stage;
- Create a file format using the FILE FORMAT command to describe the format of the file to be imported by executing the following query:
create or replace file format appsflyer_format type = 'csv' field_delimiter = ',';
- Upload the CSV containing the AppsFlyer data using the PUT command by executing the following query:
-- For Windows
put file://C:test/appsflyer.csv @appsflyer_stage;
-- Linux/Mac
put file:///tmp/data/appsflyer.csv @appsflyer_stage;
- Create a table in Snowflake in which all AppsFlyer data will be stored using the CREATE command. The tables should columns based on the data exported from AppsFlyer. The format for the CREATE command is as follows:
create or replace table appsflyer (
id varchar(100),
.......
)
- Load data from the Snowflake Stage into the table using the COPY INTO command by executing the following query:
copy into test.appsflyer from @appsflyer_stage;
Limitations of Manual AppsFlyer to Snowflake Migration
- Accessing AppsFlyer Data in Real-time: The manual approach will work fine if you are looking at a one-time data load. However, that is often not the case. If you wish to access the AppsFlyer data in Snowflake in real-time, you would then need to set up additional cron jobs to move data. This is a resource-intensive process and can slow down the project.
- Infrastructure Maintenance: When transferring data from AppsFlyer to Snowflake, many things could go wrong. For example, Snowflake may be unavailable or AppsFlyer may sometimes update the APIs. These issues will stop data flow leading to severe data loss. Therefore, a team would be needed to always monitor and maintain the infrastructure
- No Ability to Transform the Data: In case you need to clean, transform and enrich the data to make it analysis-friendly before loading it into Snowflake, you will need to write additional scripts to perform those actions. Again, this would need you to deploy additional resources that can set up and maintain the infrastructure.
Method 2: AppsFlyer to Snowflake Migration Using Hevo Data
Hevo helps you directly transfer data from AppsFlyer and various other sources to Snowflake, Business Intelligence tools, Data Warehouses, or a destination of your choice in a completely hassle-free & automated manner. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.
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Hevo takes care of all your data preprocessing needs required to set up AppsFlyer to Snowflake Migration and lets you focus on key business activities and draw a much powerful insight on how to generate more leads, retain customers, and take your business to new heights of profitability. It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination.
The following steps can be implemented to set up AppsFlyer to Snowflake Migration using Hevo:
- Configure Source: Connect Hevo Data with AppsFlyer by providing a unique name for your Pipeline, along with details about your AppsFlyer account such as the App ID, API Token, etc.
- Integrate Data: Complete AppsFlyer to Snowflake migration by providing information about your Snowflake database and its credentials such as database name, username, and password, along with information about Schema associated with your Snowflake database.
Conclusion
This article provided you with a step-by-step guide on how you can set up AppsFlyer to Snowflake Migration manually or using Hevo. However, there are certain limitations associated with the manual method. If those limitations are not a concern to your operations, then using it is the best option but if it is, then you should consider using automated Data Integration platforms like Hevo.
Eva is passionate about data science and has a keen interest in writing on topics related to data, software architecture, and more. She takes pride in creating impactful content tailored for data teams and aims to solve complex business problems through her work.