SAS for Closed Loop Campaign Management On Google & Meta Ads
It's no secret who the two biggest players in digital ad media are. Google and Meta (Facebook) quickly come to mind. For those who aren't familiar, Google Ads and Meta (Facebook) Ads are online advertising platforms enabling marketers (and brands) to find customers.
When we consider Google Ads, brands have the opportunity to connect with current and prospective customers across Search, Display, Shopping, Video and App. Pivoting to Meta Ads, marketers can reach new/existing customers as well as their networked communities on Facebook, Instagram, Messenger and WhatsApp.
With this stated, reflect for a moment on the business opportunity to:
- Maximize qualified leads and conversions
- Increase online sales
- Drive in-store foot traffic (or send more users to your website)
- Show your brand to more people to increase awareness, reach and engagement
- Market your app to new users (or increase app installs)
Now consider how many human beings on Planet Earth use Google and Meta (Facebook). It's not thousands or millions. It's billions. Hopefully we have your attention, and let's proceed to connect the dots to SAS.
SAS Customer Intelligence 360 is a martech solution to support adaptive planning, journey activation, personalization and AI-elevated decisioning to help users create appealing, moments-based customer experiences that boost profitability and strengthen brand loyalty. Within it, marketers are provided out-of-the-box (OOTB) connectors that are preconfigured for data integration with external applications. Brands can use connectors to retrieve or transfer data between SAS Customer Intelligence 360 and on-premises or cloud-based applications. Our design intent with these OOTB connectors is to offer brands time-to-value acceleration in activating commonly used data integration flows.
Now what would a software technology company like SAS with guerrilla-like data science powers that can be applied to customer analytic topics like segmentation, propensities and optimization, as well as journey orchestration and marketing activation capabilities be up to here?
The Google Ads Connector
SAS Customer Intelligence 360 provides a Google Ads connector that marketers can use to access the Google Ads API (no coding required) and to set up data integration with the ad platform. By using the connector, users can select a segment of their 1st party customer data that is stored in SAS Customer Intelligence 360 and upload it to Google Ads. The Customer Match feature from Google Ads enables SAS users to target a rule-driven or algorithmically-derived segment of your existing customers and deliver personalized messages via Google Ads.
For emphasis, when SAS states algorithmically-defined segment using your brand's 1st party data, this is where together is better. Do-it-for-me (DIFM) or do-it-yourself (DIY) segmentation specialists, everyone is welcome to the paid search and display media party!
Google Ads uses the uploaded data from SAS to build a Customer Match segment of your selected customers (who are also Google users), and enables brands to engage with them through Google applications such as Search, Display, Shopping, Video and App. Users can define the customer segment that you want to target by using any of these identifiers:
- Email address
- Customer Identifier
- Phone number
- Name
- Location
Marketers can use the configurable templates that are provided by SAS Customer Intelligence 360 to configure multiple out-of-the-box (OOTB) connectors that are associated with their Google Ads account(s). To use Google Ads and the Google Ads APIs, brands need to create a Google Ads business account and a Google manager account. After creating and configuring the Google Ads connector, to synchronize your selected customer data with Google Ads, users simply create a Google Ads task in SAS Customer Intelligence 360.
The Meta (Facebook) Ads Connector
SAS Customer Intelligence 360 provides a Meta (Facebook) Audience connector that brands can use to access Meta’s marketing APIs (once again, no coding required) and to set up data integration with the ad platform. Similar to the Google Ads connector, users can select a segment of their brand's 1st party customer data that is stored in SAS Customer Intelligence 360 and upload it to Meta Ads.
Another use case for AI-driven audience segmentation points to Supervised Learning and Profit Matrices prior to activating customers in Meta Ads. Determining an appropriate cutoff as to who to target (and who shouldn't) with paid media advertising is critical from a revenue optimization perspective. Leveraging an optimization approach using a Profit Matrix, which is a formal approach to determining the optimal cutoff of audience segmentation, meets this objective. The approach starts by assigning profit margins to true positives and loss margins to false positives. The optimal decision rule maximizes the total expected profit. As an analyst/data scientist, when one can communicate the value of modeling efforts in monetary terms, every executive paying attention is going to lean in and focus. Passing these insights to influence our marketing teammates will directly impact their segmentation strategies and KPIs. Remember friends, data science and martech together is better!
Returning back to the Meta Ads connector, the uploaded data from SAS is used to build a custom audience segment of Facebook, Instagram, Messenger or WhatsApp users whom marketers can target with personalized content. Users can define custom audiences by using any of these identifiers:
- Email address
- Customer Identifier
- Phone number
- Name
- Location
Matching the user experience with the Google Ads connector, marketers can use the configurable templates that are provided by SAS Customer Intelligence 360 to configure connections to their Meta accounts by accessing the relevant applications. To access the Meta marketing APIs, users need to set up a Meta developer account. To upload custom audiences to Meta Ads, brands also need to set up a Meta Business Manager account and associate the Meta ad accounts to the Meta Business Manager account. This will allow SAS Meta (Facebook) Audience connector to use the Meta Graph API to read from and write data into the Meta Ads platform. After creating and configuring the Meta Ads connector, to synchronize your selected customer data with Meta Ads, users simply create a Meta (Facebook) Ads task in SAS Customer Intelligence 360.
Customer Match
In the context of Google Ads, Customer Match lets marketers use online and offline data to reach and re-engage with customers. Using information that your brand’s customers have shared, Customer Match will target ads to those customers and other customers like them.
Customer Match is useful for many business goals, from increasing brand awareness to driving conversions. Here are a few examples of different audiences marketers can target with Google Ads and Customer Match:
- On the Google Search Network and the Shopping tab, users can optimize campaigns by adjusting bid amounts based on customer activities.
- On Gmail, brands can reach customers or new potential customers with similar interests using personalized ads at the top of inbox tabs.
- On YouTube, marketers can reach new segments, by targeting segments similar to your brand’s most valuable customers.
- On Display, reach customers or new potential customers with similar interests using personalized ads on the Google Display Network.
Your brand’s match rate using the Customer Match feature is the percentage of the uploaded customer list that could be connected to Google users. In other words, how much of your first party customer data can actually be leveraged for campaign use cases.
Users can create a customer data file based on 1st party information (for example, customers who have signed up for your business’s newsletter, customers who have bought from you before that have churned, etc.). Your list will be uploaded by a secure hashing algorithm, such as turning the emails into codes that cannot be unencrypted. Google does not receive the actual email addresses, nor can Google see the contents of the list. Google accounts are also in hashed codes, and the codes are compared to determine if there’s a match.
After this process is done, your data file is deleted. Whether or not there’s a match, Google doesn’t keep this data or use it for any other purposes. In accordance with Google Ads user best practices, to improve your match rate, SAS recommends adding as many match keys (i.e., customer identifier, email, etc.) as possible.
In the context of Meta (Facebook) Ads, it’s similar. A custom audience made from a customer list is a type of audience marketers can create to connect with people who have already shown an interest in your brand’s business or product. Prior to use, Meta hashes shared customer information. Then, Meta will use a process called Matching to connect the hashed information with Meta technologies profiles so that users can advertise to their customers on Facebook, Instagram and the Meta Audience Network. The more information brands can provide, the better the match rate. Additionally, Meta doesn't learn any new identifying information about your customers.
Moving on, most digital ad targeting use cases tend to NOT include 1st party customer data. Frequently, when we (SAS) work with our customers, it is a common observation to view search and social ad teams primarily using the behavior of anonymous visitors, and here is where SAS comes into play!
Because SAS Customer Intelligence 360 can automate the process of segmentation, activation and auto-scheduling, the process of creating and uploading analytically-driven 1st party segments for Google & Meta Ads can avoid manual and infrequent audience updates.
If you consider yourself an analyst or data scientist who helps your organization’s marketing efforts, aligning yourself with teammates who manage Google & Meta Ad campaigns (and their associated budgets) is the opportunity being advocated. For example, a key value proposition is the ability to scale with automation. However, it gets better when analytical segmentation insights layer on a second value proposition to motivate the union. In other words, think bigger about the variety of use cases that can be addressed.
SAS advocates the topic of Customer Match as an important consideration in support of brands desiring the maximum benefit of investing in paid media campaigns. In support of this statement, let me share a short story.
A best practice conducted internally prior to the release of new user features in SAS Customer Intelligence 360 is working with our current customers as early adopters. A non-profit globally recognized brand recently presented at SAS Explore 2023 on the topic of constituent journey management and digital personalization. A portion of their presentation story highlighted their efforts to use tasks within SAS for Google and Facebook Ad campaigns to target and re-engage inactive donors. A relevant and important milestone in their experience centered on challenges with Customer Matching.
This challenge exists for both Google and Meta (Facebook) Ads across any industry. So, what did this non-profit brand do to address the obstacle? It was a collaborative effort between the organization’s analytics & digital marketing teams. Supervised learning, champion-challenger modeling and the design of a customer match rate estimation model was an innovative solution to help the company maximize the match rates between Meta & Google Ads (above and beyond the traditional best practices of using multiple identifiers). The beauty of this was its simplicity!
Simply adjust your thinking of predicting who is likely to convert and pivot to who is likely to be matched. Now you get it…
The results of these match rate models provided improved clarity and expanded the marketable universe. In addition, the brand knew which customers should be prioritized for Meta Ads vs. Google Ads driven by predictive match rate propensities. In other words, the brand optimized (or maximized) the match rates using a data-driven approach. Nicely done!
Closed Loop Campaign Management
A customer journey in its purest form represents a series of brand-orchestrated connected experiences addressing customer desires and needs — whether that be completing a desired task or traversing the end-to-end journey from prospect to customer to loyal advocate. When you reflect on this, the customer experience is the totality of cognitive, affective, sensory, and behavioral consumer responses during all stages of the consumption process including pre-purchase, consumption, and post-purchase stages.
SAS is frequently requested by our customers/prospects and challenged by the analyst community to showcase how we help marketers design and manage journeys. This tends to involve:
- Audience segmentation
- Creation, management and planning of the timing/sequencing of a diverse set of channels/touchpoints
- Journey-based optimization and conversion attribution
Objectively, SAS strives to enable marketers to provide a mutual value exchange on digital channels across the full customer journey by optimizing orchestration capabilities and using customer-directed engagement models to guide personalization strategies. The intent is to provide increasing customer lifetime value (LTV), progressive returns on engagement, more personalized interactions, and sophisticated orchestration across the customer's end-to-end journey. It is well recognized every brand is striving to prove the value of martech in a volatile business environment, connecting marketing and customer outcomes, implemented through increased usage of journey orchestration technologies.
This is why SAS built the Google and Meta Ads connectors for SAS Customer Intelligence 360 users. The vast number of use case opportunities to bring 1st party data, best-in-class AI/ML within customer analytics and the activation layer to optimize customer journeys is here. This is much bigger than just serving an ad on a search engine or social platform driven on 3rd party data targeting.
In SAS Customer Intelligence 360, events enable users to enhance their ability to understand, target, and interact with customers in a meaningful way. Events are used to track user behavior and to provide input conditions for other items such as spots, segments, tasks, data views, and activities. For example, events are used in some of these ways:
- Record when customers click a spot on a web page or in a mobile app
- Observe when products are left by a customer in a shopping cart
- Trigger the inclusion of an uniquely behaving customer for a Google or Meta Ads campaign
Tracking user interactions is one of the core features that enables a brand to respond in real time to users based on their profile, origin, browsing behavior, and so on. The interactions that are monitored are the driving force behind many of the features that SAS Customer Intelligence 360 offers. This includes the ability to play a meaningful role in paid media campaigns for:
- The inclusion (or exclusion) of customers for paid media campaigns
- The journey-based personalization and optimization after served impressions and customer media clicks
Show Me The Demo
To bring this to life, please view the short introductory demo video. It exemplifies closing the loop on campaign management is more than getting clicks. SAS takes the baton from Google and Meta within a customer journey (websites, apps & other brand-owned properties) using data science muscle (testing, propensity-driven retargeting, algorithmic recommenders, etc.) to improve conversion metrics and monetary-driven objectives
For readers who have a desire to learn more, interactive demo videos for active users of SAS Customer Intelligence 360 are available below:
Google Ads - Task Demo
Google Ads - Connector Set Up
Meta (Facebook) Ads - Task Demo
Meta (Facebook) Ads - Connector Set Up
Finally, go here to gain incremental awareness about how SAS can be applied for customer analytics, journey personalization, AI decisioning and integrated marketing.
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