Unlock the true potential of Google Ads for your business using the Modern Data Stack
Google Ads with their massive reach and flexibility with budgets provide tremendous opportunities for businesses, both big and small, to reach out to relevant audiences on the internet and scale their operations. The ROI of any Google Ads campaign is much higher than that of other traditional forms of marketing, making it an absolute necessity for any business in these highly competitive times.
The modern data stack (read more in our first blog) with the data warehouse and the Reverse ETL component can help the organizations maximize the value from their ads. The orchestration of insights from Data Warehouse to Ads Platform by a Reverse ETL solution can light up a number of use cases for the marketing and sales teams and on an almost real time basis. Let’s take a look at a few of them in detail.
Running Remarketing campaigns based on User Actions
Retargeting audiences with strong intent or high value actions is a classic example where Google Ads can add value. This includes reaching out to customers who have abandoned their carts or subscribed for price drop alerts in case of e-commerce retailers or those who have browsed the website or expressed interest in case of a B2B business. The marketers can easily sync the user list (with contact details or device identifiers) from the Warehouse to Google Ads at regular frequency and with al
Cross Selling & Upselling to Custom User Bases
Cross selling and upselling have become a critical component of any online website’s strategy. Whether surfacing Jeans to customers who have purchased a T-shirt or Sports Shoes or targeting the users nearing expiry of their free trial offer with a discount on upgrade, these use cases can be really powerful means to building loyalty and retain customers. Again, custom user lists can be dynamically generated and powered by a Reverse ETL solution in a relatively straightforward manner.
Targeting Lookalike Audiences
Driving new customer acquisitions or generating valuable leads is a challenging task for most of the businesses. These campaigns are generally more expensive when compared with retention campaigns (mentioned above) and companies can benefit greatly from running campaigns on the lookalike audience of their best customers rather than targeting everyone. Reverse ETL solution can come to the rescue again as the analyst in the digital marketing team can build logic to define their crème de la crème base on top of the warehouse and simply feed it into their Google Ads account using it.
While a number of organizations employ analysts or MIS executives to manually upload the custom user bases at a regular interval or have built ad-hoc pipelines to support the above use cases, we often see that these work-arounds are poorly implemented resulting in most of these ads running on stale data. This high latency in turn results in lower effectiveness and below par returns on the investment made on ds. A bad ads strategy can do more harm than good for any organization in these times of a highly competitive market.
Castled and Google Ads Integration
Good news! Castled now offers a no-code and cloud-based solution supporting real time syncs for Google Ads. Move your data from Snowflake, Redshift or BigQuery in a few simple steps by validating your Ads account. Castled allows customer matching on your native user identifiers, mobile device ids or other contact information. Additionally, you can track click and call conversions easily and sync the data back to your Google Ads account to further personalize your ads.
You can visit Castled at https://castled.io/ and sign up to set up your data pipeline with Google Ads for free. Additionally, to know more, book a free demo here.
Update: Castled has pivoted out of a Reverse ETL solution to provide a better way to solve the same problem. Castled is a Warehouse-Native Customer Engagement Platform built natively on top of the cloud data warehouses like Snowflake, BigQuery, Redshift, etc. Please read our blog to understand why we made this pivot.
