How AI is changing search engine advertising
The fact of having the World Wide Web around for 30 years now - and Google for 20 years - deserves taking a closer look at the future of search engine advertising.
For dealers, the product search and displaying shopping ads for performance purposes are particularly lucrative, but good for image management via display marketing and remarketing as well, while search engines attract with unusual and cost-effective targeting options. The possibilities to reach target groups and campaign goals are almost limitless, making it therefore quite challenging to keep up with the trends.
Challenges for campaign managers are increasing
To set up and manage a campaign successfully, the account manager must consider all important factors. The list is infinitely long and ranges from industry-specific conditions, seasonal requirements and competition to the current development in data protection. Retailers are faced with the time-consuming task of maintaining the product data of a changing product range and of counteracting intense competition with often low margins. Banks, insurance companies, manufacturers in the field of fast-moving consumer goods or clothing manufacturers in turn have completely different problems. As if considering all these issues is not challenging enough, other factors such as Google policies or country-level legislation come into play, too.
The recipe for a successful campaign
First, it is important that the campaign manager has clear goals and pursues a consistent strategy. In the run-up to a campaign, important questions must be answered: What strategy is the company pursuing? How well known is the brand and what is the competitive environment? What are the budget requirements - is a growth or consolidation course being pursued? The careful planning and budgeting of a SEA campaign is becoming increasingly complex; hence, the strategic basis is fundamental to the success of the campaign and should not be taken lightly. When the goals and KPIs are fixed, the campaign manager must use the full range of instruments to achieve them.
AI and automation are changing search engine advertising
Intelligent technologies are already taking over some operational activities in search engine advertising (SEA). For example, Google uses "smart bidding" machine learning to make bidding smart. With Dynamic Search Ads, Google can crawl sites now of a keyword search and build the appropriate headline based on a dummy ad stored. Manual creation of ads will increasingly be eliminated. The time saved can and must be used to optimally set up and supervise the campaigns. Even as systems are increasingly deployed, that promise largely automated campaign creation and control, experience shows that continued optimization is still required. Particularly in the event of deviations from the expected, operative SEA - craftsmanship will continue to be in demand in the future.
Understand and master technology
Campaign control through AI and automation will continue to improve. The more information available as data for decision-making, the more operational human labor is reduced. But who guarantees us that the algorithms always meet the needs of consumers and meet the high expectations that we place on AI? Advertisers are likely to have questions even when everything seems to run perfectly. At the latest, when sales collapse, growth fails or certain products and offers are no longer in demand, someone must give an explanation. Humans must adjust the systems and be able to make individual adjustments according to their concept, strategy, industry and goals. Only those who understand the technology can unleash it in the right moment and setting - and thus develop the potential of AI and automation. This requires experienced specialists or trustworthy partners who combine operative experience, technical know-how and industry knowledge.
The problems and limitations of AI
If systems ultimately only regulate numbers, facts and hard KPIs, campaigns quickly reach their limits. The most important thing is and remains the interested and ready-to-buy consumer. Whether local retailer or mega-online store, visitors are always the most important asset. The number of highly qualified visitors is a central and often neglected core. Visits lead to direct or indirect purchase, but also to the branding of the shops or the image. It is important to keep an eye on this crucial factor across all measures. Regardless of the bright performance figures, human experience and intuition will continue to play an important role in the future. As automation increases, more and more resources are needed for Paid Search planning and control. The know-how about new technologies and the operative experience and expertise merge into the marketing skill of the future. If AI is used properly, it will make search engine advertising better in the future.
Why marketers should focus on machine learning
Machine Learning (ML) actively supports advertisers in analyzing user behavior and displaying targeted ads. Machine learning can map the entire buying process across multiple devices and channels, making machine learning an indispensable technology in order to stand up to the competition and efficiently win new customers.
Due to the increasing use of smartphones, the usage and search behavior is changing. Mobile devices have long overtaken the desktop in use, but typing is annoying for many users, so they increasingly access the language assistant. The search terms are simply spoken. In the Google App, 20% of searches are already done by voice, hence, Google is heavily working on a perfectly functioning online search for Artificial Intelligence. The Google Assistant is about voice search to find pictures and answers to complex questions. As the search changes, advertisers must also go new ways, which means advertisers won’t be able to get past Voice Search.
This development also has a new requirement for technology, since the traditional keyword set does not work anymore, but machine learning. The amount of voice input is challenging itself. Users ask very specific questions and expect accordingly very specific results.
There are many suppliers in the market by now, but so far Google AdWords campaigns have been created and optimized manually or via bid management tools. Machine learning algorithms automate targeted playout and optimization. A possible example would be an evaluation of whether the user was searching from an iPhone, Android device or browser. AI can capture this and deliver targeted ads.
The work of SEA experts is facilitated by ML, as the technology can simplify data analysis and campaign automation. In addition, the evaluation of the customer journey is simplified, and the editorial part positively influenced. Considering all arguments, advertisers should put the topic of voice search on top of their agenda.
By Daniela La Marca