Almost every business on earth had to embolden its digital presence last year, thanks to the COVID-19 pandemic. It increased the online competition, as well as the pressure on digital marketing professionals.
Organizations need a more strategic approach for their paid search programs and expect their digital marketing teams to unify the efforts with the overall business plan. Digital marketers also need to justify the performance of various marketing channels. They need to prove that these channels have a direct impact on revenues and profits.
We have noticed that many digital marketers are relying on machine learning to gain better performance and sites to automate and optimize their key functions.
Machines can analyze big data in real-time, automate bid adjustments, select target audiences, and create powerful ad messages. They complete all of these functions based on various factors, such as consumer devices, geo-targeting, and other customer preferences.
A machine can indeed gather and analyze data faster than human beings. However, a digital marketer or a Search Engine Marketing consultant still needs to create the right SEM strategies.
Machine learning tools will follow these strategies to collect the relevant insights and utilize them accordingly. In other words, using machine learning without proper directives for SEM can lead to poor performance and wastage of budget.
Evolving From PPC Technicians to Strategists
Machine learning tools used for SEM will not steal a PPC professional’s job. However, the ability of these tools to automate essential tasks will transform a professional job role. Their primary function would be to create the necessary strategies so that machine learning solutions can perform as required.
Professionals will have to understand the marketplace and align the business operations with the market. It will enable them to connect the PPC efforts to the overall growth of their digital marketing program. The machine learning tools can be used to analyze data, identify trends, and execute everyday tasks faster than human beings.
PPC professionals also need to have a firm grasp of the KPIs and metrics most important to the organization. For example, a company might have multiple PPC goals, such as increasing the volume and managing Cost per Action (CPA). Professionals need to understand which of these goals are more important to the organization.
Understanding the priority of these goals will enable them to minimize misalignment. They will know what kind of machine learning data they should collect and how to utilize them properly. They should also be able to foresee obstacles like high CPC or low conversion rates that could prevent them from meeting those objectives.
Identifying the Technological Resources
Automation and machine learning are bound to play a bigger role in Search Engine Marketing in the future. Paid search marketing and social functionalities are becoming more complicated than before. Professionals need to manage a large number of platforms and networks continuously. Organizations also need deeper analysis and insight into cross-channel avenues for better results.
These dynamics can put a lot of pressure on marketing teams that are still engaging in manual work. Therefore, once the digital marketing team has created the right strategy, they need to identify the technological resources required to achieve their objectives.
They will also have to determine if they need more human resources or tools depending on the workload, job complexity, and company budget. There are many technological resources available in the market, ranging from light platforms to complex automated solutions.
Some of these platforms offer PPC management functionalities, such as automating bids, choosing keywords, selecting add groups, and managing campaigns based on predefined criteria. The teams can also integrate the inventory or CRM data into their paid marketing campaigns.
Demonstrating the Value of Machine Learning
Digital marketing teams still have a tough time selling the need for a machine learning approach to the company stakeholders. They have to justify that the use of machine learning technology in SEM will have a guaranteed impact on revenue and profits. Team members may also feel that introducing machine learning can make their jobs obsolete.
Therefore digital marketing managers need to demonstrate the value of the machine learning approach to convince the stakeholders and the team members. These are some of the ways to emphasize the value of machine learning and search engine marketing.
- Machine learning tools will transform the job role of the PPC team from technicians to strategy creators. It would also help in connecting the paid search marketing channels to the overall business marketing strategies.
- The teams will have to endure less “downtime” for collecting and organizing and data. Therefore, they would be able to spend more time interpreting the information and plan the subsequent steps for the company.
- Professionals would be equipped better to tap into the invisible aspects of paid marketing. Advertising platforms tap into a multitude of data signals that can be utilized for better targeting and bidding. Only technological tools can follow these signals for better optimizations to achieve superior results and gain an edge over their competitors.
The value of the machine learning approach can be best exhibited through positive results. Therefore, marketing teams should be prepared to demonstrate a positive impact of technological resources on revenues and profits to convince the stakeholders.
Machine learning algorithms may be able to achieve unprecedented results in search engine marketing. However, these tools would not be as useful without human intervention to monitor and manage them. Therefore, people and technology need to work together to achieve the desired results.
Professionals should also embrace machine learning technologies without feeling the loss of their jobs. In fact, these tools can enhance their performance to produce better camping structures and exceed their expectations of stakeholders.