The news concerning ad investments has been quite constant. Only 14.7% of APAC organizations indicated they will cut media spending in the new year, while 50% said they will maintain existing spending in 2022. A little more than a third (35%) of APAC firms want to increase media expenditures cautiously in 2023. While the sector is predicted to grow, it is expected to be slow due to the global crisis and massive layoffs.
Brands are becoming more aware of their ad expenditure and are continuously on the hunt for new ways to improve their ROI. In times of uncertainty, previous purchasing and spending habits become less predictive of future behavior. Marketers must be able to learn on the go and adapt to what they observe in real time. This will require the use of data-driven solutions that offer access to data that they do not already have or cannot get fast enough. Here are the conduits towards leveraging and harnessing data-driven strategies:
Personalization
- One of the key reasons to invest in data is to tailor marketing strategies. Businesses may design customized marketing strategies that speak directly to the needs and interests of individual consumers by collecting and analyzing data on customer behavior, preferences, and demographics.
- Data-driven personalization can be done at the creative level using Google’s DV360. The ads can be personalized based on device, weather, ad placement, behavioral information, demographics, and other information collected previously. Here’s an example of personalization in a weather ad.
- On this occasion, the user’s city, time of day, and weather have been taken into account to show a personalized creative adapted to the context. In this way, we give the ad a context that makes it much more relevant. In 2023, we can expect a sustained emphasis on personalisation as organizations attempt to provide relevant, tailored client experiences.
- Marketers are evaluating the most optimum platforms and tools that enable effective personalization in a compliant manner, implementing them within their existing marketing technology stacks is a growing area of resource and investment, such platforms offered by Flashtalking, Smartly or Ad-Lib.
Artificial Intelligence and Machine Learning
- How businesses examine and use data is changing thanks to artificial intelligence (AI) and machine learning (ML).
- Machine learning is used by programmatic marketers to monitor a customer’s activity on social media sites such as Facebook and Twitter. The information gathered from these sites is then used for market research or even customized marketing materials. As a result, they cater to each user’s preferences (and thus increase conversions).
- A business wants to improve its campaign performance by targeting ads to potential customers who are likely to purchase its products. To do this, the business uses machine learning algorithms to analyze data from different sources (e.g., past customer purchases, website traffic, social media posts) and identify patterns among them. This analysis allows the business to better understand which customers are most likely to buy its products. Then, they can target those individuals with targeted ads. As a result, the business’s campaign performance improves as it reaches more of the right people with its advertising messages.
- In order to maximize their marketing efforts and improve outcomes, more companies, including those with smaller budgets, are likely to use AI and ML in 2023.
Predictive Bidding
- This is another type of AI-powered bidding system that helps a marketer determine the type of bidding that will be best suitable as per the business strategy. This allows advertisers to minimize their cost per impression and maximize the efficiency of each advertisement.AI in programmatic advertising determines the value of each keyword you bid on in a bidding campaign.
- AI assesses how changes in cost-per-click (CPC) might affect costs and clicks after assigning a value to the terms. Following that, it determines the best bid for each keyword based on your specific objective.
In 2023, advertising will undergo a transformation, with privacy-first advertising and a cookie-less future. Adoption of industry standards and personalization of advertisements to consumers, the development of transparent data exchange mechanisms, and investments in data that will help drive better business decisions will be critical to the industry’s ability to adapt and thrive. Bidmath is a global, transparent digital and technology partner. Powered by machine learning and real-time personalization, we deliver data-driven marketing for global brands. If you would like our experts to assess your business opportunities, get in touch with us today.
The news concerning ad investments has been quite constant. Only 14.7% of APAC organizations indicated they will cut media spending in the new year, while 50% said they will maintain existing spending in 2022. A little more than a third (35%) of APAC firms want to increase media expenditures cautiously in 2023. While the sector is predicted to grow, it is expected to be slow due to the global crisis and massive layoffs.
Brands are becoming more aware of their ad expenditure and are continuously on the hunt for new ways to improve their ROI. In times of uncertainty, previous purchasing and spending habits become less predictive of future behavior. Marketers must be able to learn on the go and adapt to what they observe in real time. This will require the use of data-driven solutions that offer access to data that they do not already have or cannot get fast enough. Here are the conduits towards leveraging and harnessing data-driven strategies:
Personalization
- One of the key reasons to invest in data is to tailor marketing strategies. Businesses may design customized marketing strategies that speak directly to the needs and interests of individual consumers by collecting and analyzing data on customer behavior, preferences, and demographics.
- Data-driven personalization can be done at the creative level using Google’s DV360. The ads can be personalized based on device, weather, ad placement, behavioral information, demographics, and other information collected previously. Here’s an example of personalization in a weather ad.
- On this occasion, the user’s city, time of day, and weather have been taken into account to show a personalized creative adapted to the context. In this way, we give the ad a context that makes it much more relevant.In 2023, we can expect a sustained emphasis on personalisation as organizations attempt to provide relevant, tailored client experiences.
- Marketers are evaluating the most optimum platforms and tools that enable effective personalization in a compliant manner, implementing them within their existing marketing technology stacks is a growing area of resource and investment, such platforms offered by Flashtalking, Smartly or Ad-Lib.
Artificial Intelligence and Machine Learning
- How businesses examine and use data is changing thanks to artificial intelligence (AI) and machine learning (ML).
- Machine learning is used by programmatic marketers to monitor a customer’s activity on social media sites such as Facebook and Twitter. The information gathered from these sites is then used for market research or even customized marketing materials. As a result, they cater to each user’s preferences (and thus increase conversions).
- A business wants to improve its campaign performance by targeting ads to potential customers who are likely to purchase its products. To do this, the business uses machine learning algorithms to analyze data from different sources (e.g., past customer purchases, website traffic, social media posts) and identify patterns among them. This analysis allows the business to better understand which customers are most likely to buy its products. Then, they can target those individuals with targeted ads. As a result, the business’s campaign performance improves as it reaches more of the right people with its advertising messages.
- In order to maximize their marketing efforts and improve outcomes, more companies, including those with smaller budgets, are likely to use AI and ML in 2023.
Predictive Bidding
- This is another type of AI-powered bidding system that helps a marketer determine the type of bidding that will be best suitable as per the business strategy. This allows advertisers to minimize their cost per impression and maximize the efficiency of each advertisement.
- AI in programmatic advertising determines the value of each keyword you bid on in a bidding campaign. AI assesses how changes in cost-per-click (CPC) might affect costs and clicks after assigning a value to the terms. Following that, it determines the best bid for each keyword based on your specific objective.
In 2023, advertising will undergo a transformation, with privacy-first advertising and a cookie-less future. Adoption of industry standards and personalization of advertisements to consumers, the development of transparent data exchange mechanisms, and investments in data that will help drive better business decisions will be critical to the industry’s ability to adapt and thrive.Bidmath is a global, transparent digital and technology partner. Powered by machine learning and real-time personalization, we deliver data-driven marketing for global brands. If you would like our experts to assess your business opportunities, get in touch with us today- [email protected]
Source: Bidmath