Introduction: When was the last time you went to the Bank to get your monthly transactions updated? Or When was the last time you manually adjusted the brightness of your cell phone? Not recently, right? In both the above cases, we allow a device or mechanism to take multiple similar decisions for us, which are essentially repetitive but require manual labour. This is where Automation comes into the picture.
Automation has intercepted almost all spheres of life from Agro-bots that facilitate large farms to operate in an integrated fashion with no human employment, up to OMR sheets that allow bulk yet errorless assessment of answer scripts in highly competitive examinations around the globe. In every case, Automation has been an undeniable device to help us reduce the man-hours needed to complete multiple tasks on micro and macro scales.
Automation in Ads
Automation in Ads started back in the 90s when marketers wanted to remove redundant activities from their daily course of work to focus on core revenue opportunities. This approach saved time and allowed the reusability of ideas based on tests.
Over the last two decades, marketing and especially advertisements have grown dependent on Automation for multiple intricate activities. Tools like:
- ActiveCampaign
- HubSpot Marketing Hub
- Salesforce
- Eloqua…
All these tools have helped us automate and streamline our marketing efforts. Even within various advertisement platforms, we find features to automate mundane, similar yet time-consuming decisions that must be taken frequently.
Automated Bidding Strategies in Google Ads.
Automated Bidding helps advertisers manage their monthly budget without thinking of how much to spend on Ads and Keywords. For many advertisers over the world, it is a gargantuan task to get trained on the technical aspects of digital platforms like Google Ads which consequently makes advertisers spend more on unnecessary keywords and demographic parameters. Automated bidding strategies take help from various data sources and relieve the advertiser of the constant monitoring of competitors and trending keywords to decide keyword bids accordingly.
Automated AdCopies on Facebook
On Facebook, automated ads refer to a self-sufficient ad serving capacity. Much like Google there are few common AI functionalities on Facebook ads as well. Facebook makes improvements on our ad copies based on what part of the ad text works for us. Call to action buttons and other creative assets are automatically fetched from the page and the ad is always improving to be the best version of itself based on performance data. Optimization of ad copies is taken care of by the AI framework thus automating the process of monitoring ads and emphasising effective features.
4 Reasons that make Automation Inevitable in the Digital Ads Space?
1) Ease of Data Transactions: Monitoring your Ads can be an arduous task for businesses with elaborate marketing campaigns. Automation relieves us from the task of constantly speculating and analysing ads data. Automated campaigns on various ad platforms do not require advertisers to manually design the campaign specifics. Data is fetched from multiple linked sources and is used to show ads for that particular business.
E.g., Smart Campaigns on Google Ads just require the advertiser to set the primary levels of targeting and a budget. In contrast, the required data is fetched from past campaigns, website content, historical traffic and leads, backlinks, etc. While we get to see an overview of the performance of these campaigns, the ads are dynamically served, and the optimisation is taken care of by an automation algorithm.
2) Reusability of Assets: Almost all digital advertising platforms try to utilise an advertiser’s entire digital presence, i.e., relevant information and content about the product or service advertised, which is automatically fetched from all digital aliases of the business. This happens with the help of data extraction algorithms on the backend. Web-crawler codes can extract data from all primary digital sources available. Automation allows us to use our content to the fullest extent, relevantly.
E.g., Setting up a Display Campaign on Bing or Google hardly takes a minute as the advertiser does not have to provide all the visual and textual content manually. Instead, creatives and images from all the linked social media handles, Offline databases, Recently used creatives, etc., are scanned directly with the help of AI automation, thus increasing the content’s utilisation capacity.
3) Reduced Testing hours: Testing a marketing strategy is a necessity before permanently implementing it. This process, however, has financial implications. Testing campaigns at a reduced budget is normal but becomes expensive for companies with elaborate marketing strategies. Automation helps in testing the receptivity of our ads with the help of historical data and analysis of the market landscape while keeping the financials under control.
E.g., Drafts and Experiments are automation enabled testing devices on Google Ads. Drafts allow marketers to change a draft campaign which is essentially a copy of an already running movement, and an Experiment dry-runs that draft campaign without publishing it. Comparing data from draft campaigns with live campaigns helps conclude the viability of changes made.
4) Real-time, round the clock optimisation: The digital ads space is constantly changing and is governed continuously by moments and trends. This creates a need for monitoring our digital presence round the clock. Though this sounds tiresome, AI and Automation can help us do precisely this. Automation enables us to design rules and directives around our ads so that they augment themselves in real-time, in terms of serving ads, bidding strategies, budget changes, etc., automatically, based on what the situation demands.
E.g., Automated Rules in Google Ads enable the campaigns to autonomously change budget, pause or activate campaigns or block webpages to be shown based on directives stated in the rules. This keeps the system cost effective and smooth even without active monitoring.
Conclusion
Even though Automation makes the intricate obstacles in our life more accessible to a considerable extent, in the big picture, AI, Automation, and Machine learning pose somewhat of a threat to the job market associated with Digital Ads.
Many currently existing job roles have a big chance of being reduced to the equivalent of pushing a few buttons. But while Automation can take out most of the redundant documentation from digital ad operations, it is also expected to create newer orifices of employment in the digital landscape. Reducing man-hours required for non-revenue fragments of operations will result in higher growth in revenue with a lower effort. Increased competitiveness should be noted in ads with the currently projected trajectory of Automation.
