Google Ads to Snowflake – Made Easy

Step by step guide to move PostgreSQL to BigQuery into a data warehouse of your choice! ETL/ ELT your eCommerce data easily with Daton

Google-Ads-to-Snowflake-Made-Easy | Saras Analytics
Google-Ads-to-Snowflake-Made-Easy | Saras Analytics

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If you’ve come here, you are probably looking for a way to transfer data from Google Ads to Snowflake quickly. In this article, we talk about why Google Ads is essential and how you can get access to this data without having to write any code.

The choice for eCommerce businesses when it comes to marketing and selling their merchandise is growing every day. eCommerce vendors have to decide on what channels they want to sell on, which channels they want to spend their advertising dollars on, and whether the channels include:

  • Branded websites
    • In some cases branded eCommerce sites per country
  • Marketplaces
    • In many instances, marketplaces per country
  • Retail stores
    • to create an omnichannel presence and to engage buyers where the shop

Complexity increases with the addition of every sales channel. For instance, if we consider marketing channels available to support online business, you will find a choice of:

  • Social Media ads – Some platforms include Facebook Ads, Instagram, LinkedIn, Twitter, and others
  • Digital ads and remarketing – Criteo, Taboola, Outbrain, and others
  • PPC – Google ads, Bing ads, and others
  • Email – Mailchimp, Klaviyo, Hubspot, and others
  • Podcasts
  • Affiliate – Refersion, CJ Affiliates
  • Influencer marketing
  • Offline marketing and more

Choice, while being a great virtue, leads to complexity, and this complexity when not managed properly, can, in turn, impact the efficiency of running an eCommerce business. Most eCommerce businesses grapple with this complexity; some well and many not so well.

In the competitive digital landscape that we live in, it has become imperative that eCommerce businesses of all sizes that aspire to grow and stay profitable have to look into their data deeply and leverage this for growth.

With the increase in competition, eCommerce Companies should strive to be more data-driven for various reasons. Some of these reasons include.

  • understanding the balance between demand and supply
  • understanding customer lifetime value (LTV)
  • Segmenting customer base for effective marketing
  • finding opportunities to reduce wasteful spend
  • optimizing digital assets to maximize revenue for the same marketing spend,
  • improving ROIs on Ad campaigns and
  • offering an engaging and seamless experience for customers in every channel that the customer engages with the brand.

Businesses these days need to be efficient in terms of their data analysis. They are struggling to make sense of the data generated from various applications and tools used to manage different processes efficiently.

Due to the reasons highlighted above, any eCommerce business typically operates at least 10-15 different software/platforms to deliver on their customer expectations. As a result, data silos are created, which makes it more difficult to consolidate data and use the data for reporting, operations, analysis, and taking informed forward-looking decisions.

Marketing platforms like Google Ads generate a substantial amount of data like impressions, user behavior, clicks, product details, and more. Additionally, eCommerce companies that sell globally often end up having separate ad accounts for each country which in turn creates data silos for each country. Imagine a brand selling on three marketplaces or three countries – They may have three accounts per channel in which they are generating data—consolidation of data from these accounts for effective reporting.

These silos make an analysis of the entire business data comprehensively, challenging. Data Savvy eCommerce businesses try to reduce the effort of reporting and analysis by integrating data from all these channels into a cloud data warehouse like Snowflake. By taking this step, the process of reporting and analysis becomes easy, inexpensive, and consequently done more frequently.

In this post, we will be looking at methods to replicate data from Google Ads to Snowflake.

Before we start exploring the process involved in data transfer, let us spend some time looking at these individual platforms.

 

Google Ads Overview

Google Ads (formerly AdWords) is Google’s online advertising tool. Google Advertising is an efficient way to bring potential traffic or suitable buyers for your company who are browsing for goods and services that you sell. Google Ads reaches about 90% of internet users worldwide. Google Ads helps you display your ads to people who are already searching for something similar to what you offer. Instead of broadcasting your message to anyone, you can choose to display the ads to the users who are already in the market for your products or services. There is no minimum commitment to spending, and the system can be stopped or paused anytime. You can use retargeting strategies to boost return traffic and increase sales. This way, when your advertisement makes sense, you reach your target audience effectively.

  • You can target anyone as the reach of Google is virtually limitless.
  • You can ensure that your ads are always relevant to the user.
  • Your ads are always going to the right people.
  • You have to pay only when someone clicks on your ad.
  • You can remarket to people who have already been to your site.
  • Google gives you a ton of relevant data you can use to improve performance.

 

Snowflake Overview

Snowflake is a cloud-based data warehouse created by three data warehousing experts at Oracle Corporation in 2012. Snowflake Computing, the vendor behind the Snowflake Cloud Data Warehouse product, raised over $400 million over the past eight years and acquired thousands of customers. One might wonder if another data warehouse vendor is needed in an already crowded field of traditional data warehousing technologies like Oracle, Teradata, SQL Server, and cloud data warehouses like Amazon Redshift and Google BigQuery. Well, the answer is the disruption caused by cloud technologies and cloud opportunities for new technology companies. Public clouds enabled startups to shed past baggage, learn from the past, challenge the status quo, and take a fresh look at cloud opportunities to create a new data warehouse product. You can read this article to understand the core technology components that make up this modern, cloud-built data warehouse for consumers of cloud technologies.

You can register for a $400 free trial of Snowflake within minutes. This credit is sufficient to store a terabyte of data and run a small data warehouse environment for a few days.

 

For more information, visit Google Ads Connector.

 

Why Do Businesses Need to Replicate Google Ads to Snowflake?

Let’s take a simple example to illustrate why data consolidation from Google Ads to Snowflake can be helpful for an eCommerce business.

An e-commerce company selling in multiple countries is running campaigns on Google Ads. They have different selling platforms, payment gateways, inventories, logistic channels, and target audiences in each country. An ad might be running off a product that might no longer be in stock, or might not be deliverable in the location in which it is running, rendering these ads as redundant and thus causing a substantial loss for the company. Now when the decision-makers want to rectify this and optimize the Google Ad campaigns to maximize ROIs, they are faced with the following problems.

  1. There are separate data silos for inventory data, and logistics data, which need to be separately downloaded and compared, and updated regularly to optimize the Google Ads campaign.
  2. Again if you want to do remarketing effectively, then people who have not completed payments, or have encountered a failed transaction need to be targeted in addition to people who have added products to their cart, wishlists or favorites. People who have responded to other marketing campaigns like email, SMS, social media marketing also need to be targeted. So again separate data silos from various selling platforms, payment gateways, and marketing tools need to be downloaded, analyzed, and compared.
  3. Audience profiling data from e-commerce platforms, CRMs, customer support systems need to be analyzed to optimize audience targeting.
  4. While calculating profits/losses of the overall business, it becomes a nearly impossible task to pull all of these data from multiple platforms for each country separately, and then analyze all of this data together with the expense data and calculate profits. It involves a lot of working hours which costs money, and there is usually a time lag involved, which reduces the accuracy of the analysis and its effectiveness as the data is not analyzed in real-time.
  5. The compilation and processing of data from multiple sources for thorough research is a considerable challenge if carried out manually.

For these reasons, top companies consolidate all of their data from Google Ads and other apps and tools into a data warehouse like Snowflake to analyze the data and generate reports at a rapid pace.

The more data you can gather and use from different sources in your Google ad campaign, the more your ad delivery is optimized. All these data can not be natively transmitted to Google. Such data must be collected and analyzed correctly in a data warehouse before you use the relevant information to run ad campaigns on Google.

 

Replicate data from Google Ads to Snowflake

There are two board ways to pull data from any source to any destination. The decision is always a build vs buy decision. Let us look at both these options to see which option provides the business with a scalable, reliable, and cost-effective solution for reporting and analysis of Google Ads data. You can also retrieve the data from Snowflake any time you want. To know more, click here.

 

Use a cloud data pipeline

Building support for APIs is not only tedious but it is also extremely time-consuming, difficult, and expensive. Engaging analysts or developers in writing support for these APIs takes away their time from more revenue-generating endeavours. Leveraging an eCommerce data pipeline like Daton significantly simplifies and accelerates the time it takes to build automated reporting. Daton supports automated extraction and loading of Google Ads data into cloud data warehouses like Google BigQuery, Snowflake, Amazon Redshift, and Oracle Autonomous DB.

Configuring data replication on Daton on only takes a minute and a few clicks. Analysts do not have to write any code or manage any infrastructure but yet can still get access to their Google Ads data in a few hours. Any new data is generated is automatically replicated to the data warehouse without any manual intervention.

Daton supports replication from Google Ads to a cloud data warehouse of your choice, including Snowflake. Daton’s simple and easy to use interface allows analysts and developers to use UI elements to configure data replication from Google Ads data into Snowflake. Daton takes care of

  • authentication
  • rate limits,
  • Sampling,
  • historical data load,
  • incremental data load,
  • table creation,
  • table deletion,
  • table reloads,
  • refreshing access tokens,
  • Notifications

and many more important functions that are required to enable analysts to focus on analysis rather than worry about the data that is delivered for analysis.

 

Daton – The Data Replication Superhero

Daton is a fully-managed, cloud data pipeline that seamlessly extracts relevant data from many data sources for consolidation into a data warehouse of your choice for more effective analysis. The best part analysts and developers can put Daton into action without the need to write any code.

Here are more reasons to explore Daton:

  • Support for 100+ data sources – In addition to Google Ads, Daton can extract data from a varied range of sources such as Sales and Marketing applications, Databases, Analytics platforms, Payment platforms, and much more. Daton will ensure that you have a way to bring any data to Snowflake and generate relevant insights.
  • Robust scheduling options allow users to schedule jobs based on their requirements using simple configuration steps.
  • Support for all major cloud data warehouses including Google BigQuery, Snowflake, Amazon Redshift, Oracle Autonomous Data Warehouse, PostgreSQL, and more.
  • Low Effort & Zero Maintenance – Daton automatically takes care of all the data replication processes and infrastructure once you sign up for a Daton account and configure the data sources. There is no infrastructure to manage or no code to write.
  • Flexible loading options allow you to optimize data loading behaviour to maximize storage utilization and also easy of querying.
  • Enterprise-grade encryption gives your peace of mind
  • Data consistency guarantee and an incredibly friendly customer support team ensure you can leave the data engineering to Daton and focus instead of analysis and insights!
  • Enterprise-grade data pipeline at an unbeatable price to help every business become data-driven. Get started with a single integration today for just $10 and scale up as your demands increase.

For all sources, check our data connectors page.

We Saras Analytics can help with our eCommerce-focused Data pipeline (Daton) and custom ML and AI solutions to ensure you always have the correct data at the right time. Request a demo and envision how reporting is supercharged with a 360° view.

Other Articles by Saras Analytics,

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