How can AI and Machine Learning optimize Google Ads Campaign

1. How can AI and Machine Learning optimize Google Ads Campaign With many developers around the globe working to create algorithms for Artificial Intelligence and Machine Learning, their potentiality is emerging in various sectors and new applications are being discovered. Artificial Intelligence and machine learning are technologies that allow computer systems and machines to perform tasks normally like humans. This gives the computers the ability to recognize speech, make decisions, and take actions that require human intelligence. With Google Ads incorporating artificial intelligence into its frameworks, new opportunities are arising for the Search Engine Marketing companies and experts to gain an advantage over their competitors and focus more of their time to strategize their campaign. Ways in which AI can be used to use Google Ads effectively are: AUTOMATED BIDDING: As the technology of artificial intelligence is expanding, more pay per click management firms are using its ability to make effective decisions to bid on important keywords. However, there are still some challenges in automated bidding. As a vast majority of people are using Google’s internal automated bidding, it is a challenge for the AI to bid according to the PPC marketer requirement. By understanding the need of the customer, purchasing behavior, customer value, demographics, and seasonality the algorithm of automated bidding can be modified to an extent of making decisions according to the need of the advertiser. Bidding too high can lead to a decrease in ROI and bidding too low can sacrifice a chance to connect with a potential client. A successful automated bidding model must be able to elastically judge the range of the money that should be spent on a particular keyword. It should also be able to judge the effectiveness of a keyword according to the need of the bidder and its business. In response to the new data, it should iterate accordingly and understand the buying habits of the bidder.

2. Adapting according to the bidding landscape and performance of visits, capability of AI to make effective decisions will help an advertiser to gain more customers for its business. However, there are some things that a marketer should look for while using automated bidding: AI models that don’t know how the website operates, can lead to bad inferences and make inappropriate decisions while bidding. Statistical data is an important aspect that helps a bidder to bid on an appropriate keyword. But it consumes a lot of time to measure and track these statistics. An AI model that focus too much on statistical data may test a losing strategy for too long, but a model that doesn’t incorporate its significance can throw away an opportunity to get good customers. GIVING HALT TO A POORLY PERFORMING AD It can lead to lost fortune if an Search Engine Marketing expertcontinues to bid on keywords that don’t produce any return on investment. It is a disaster when there are no sales even after there are sufficient click-throughs on a keyword. Similarly, ROI is also affected negatively in a vice versa condition. A brilliant machine learning algorithm will understand when it is necessary to bid on a keyword and when it is essential to stop bidding on the keyword that doesn’t produce sufficient ROI. Some important considerations that a well-designed algorithm must account are: Based on the previous bids, performances, and statistical inference an AI should be able to estimate potential losses and chances of profit. It should not be so sensitive that it stops a campaign even before it had a chance to showcase its potential. Instead of stopping the whole campaign and leave no chance to deliver ROI, a smart AI algorithm should only halt those portions that don’t deliver effective results. For example, the time interval in a day that doesn’t produce an effective result, certain browsers that don’t work, and ad variations that aren’t performing well. DYNAMIC SEARCH ADS Dynamic Search Ads is a feature that comes in-built within Google Ads. It automatically generates taglines to catch searchers attention during a search. After you update a list of pages that you want to display, the googles algorithm will identify searches that are good for your landing pages, and build taglines on the basis of the phrases used in your pages.

3. Google also makes ad suggestion using machine learning on the basis of your previous performance and bidding habits. Machine learning approach can be used to create dynamic ad content that incorporates the following points: Linking external factors like time of day or weather condition. Incorporating random images, graphics, and audience with variegated testing and evolutionary algorithms.  CONCLUSION It may look like that you’ll need a data scientist and developers on the team to take advantage of features that AI and machine learning have brought in the sector of paid marketing. Having a large team might be better for best pay per click management companies, but small and medium business can also benefit from these technologies. Many platforms like Acquisio, Frank, Trapica, and Quarizmi can be used along with the insights discussed, in order to take full use of AI and machine learning in PPC marketing. The technology of AI has really graced the marketing industry in a vast manner. However, this technology is still in its infancy and not many enterprises are using it. With a race going on between the best SEM experts and pay per click marketing service providers to deliver the best result to their client, the company that will incorporate these technological enhancements will surely benefit first hand.