A lot has changed in the online advertising and marketing world over the past decade. One may think new technologies and advancements would pave the way for seamless and streamlined online advertising, but the ground reality portrays a different story. The steep competition coupled with increasingly demanding clients puts the onus on advertisers to attain the desired results quickly.

Besides, state and country-level laws around cookies have made it challenging for online advertisers to collect consumer information. For instance, the California Consumer Privacy Act (CCPA) and Virginia Consumer Data Protection Act (CDPA) deem cookies as personal information. Thus, websites are required to obtain consent from visitors to collect data. 

Can advertisers work around these problems? Of course. This is where machine learning in advertising comes into the fray. The adoption of machine learning solutions has witnessed exponential growth worldwide over the past few years. The analytical depth and error-free insights provided by machine learning solutions are tipped to revolutionize the way advertising works. 

We believe that AI-based advertising is the future of advertising and for good reasons. In this article, we will explore the benefits of machine learning in advertising. 

Let’s begin.

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Machine learning in advertising – the way forward?

Machine learning solutions are capable of processing large volumes of data and identifying patterns. Marketers can leverage these insights to determine consumer behaviour and advertise relevant content to them at the right time. 

With artificial intelligence (AI) and machine learning models, advertisers can create hyper-relevant ads and attain the desired return on investment (ROI) for every digital campaign. 

Benefits of machine learning in advertising, what advertisers need to know

1. Improved personalization

Personalized ad on a mobile

In today’s day and age, it is pretty clear that customer experience is a key differentiating factor between a good and an average brand. In their quest to provide seamless customer experiences, brands have turned to personalization to achieve this objective. This is exactly why the focus has shifted toward displaying the most relevant ads to their audience. 

Data shows customers love the flavour of personalization. Around 80% of regular shoppers state they prefer shopping from brands that offer a personalized experience [1]. It is also worth noting that customers will turn their back on companies that offer poorly orchestrated personalization to them [2]. Therefore, personalization has become an extremely important factor for brands today. 

Machine learning in advertising considers monstrous volumes of data to help advertisers create and deliver personalized ads. These can be delivered through conversational marketing strategies or based on location, seasonality, or the weather. For instance, if you are in London, it would be a good idea to advertise winter clothing or Christmas gifts instead of hot cereals. 

2. Informed decision-making with machine learning

Nothing against humans but we make mistakes. When compared to the decision-making prowess of computers, we are no match. Organizations that largely rely on human decision-making processes will find it difficult to make informed decisions. 

It’s challenging to distinguish biases from analysis and even more so to pick out the most vital information from the huge amounts of data accumulated. Businesses are aware of these issues and are utilising machine learning to address them.

Around 65% of businesses that are adopting or planning to use the technology acknowledge the importance of AI for data analytics.

When marketers adopt an AI- or machine-learning-based product, the algorithm takes into account all the data and information they have on a certain subject and uses it to make the best choice it can. As the system continues to collect more data, these decisions get progressively better.

Better decision-making has become increasingly crucial for advertisers that want to ensure that their advertisements apply to the target audience. Poor advertisement can harm a brand’s credibility as well as frustrate users. According to research, 90% of customers feel that advertisements from businesses that are not personally relevant to them are “annoying,”.

AI can assist advertisers in making wiser decisions in areas other than just the creative side of things. The advertising landscape is constantly changing, therefore it’s critical for businesses to adjust. For example, during the pandemic, shoppers turned to online buying over going to physical stores. Machine learning, which can also choose what information is relevant and determine what action to take next can consider these changes.

3. Machine learning in advertising paves way for personal interactions

A young kid interacting with ads online

AI and machine learning models including conversational marketing can provide a personalised experience to customers. The popularity of such tools is expected to grow more and more as customers continue to move toward a digital world, but still want a feel of an in-store experience. Advertisers can now recreate a similar experience by leveraging AI-based tools to provide a personalized touch to their audience. 

Advertisers can develop distinctive, personalised interactions with customers across a myriad of touchpoints in the buyer’s journey with the use of conversational marketing tools. This could appear as personalised, interactive advertisements at the front of the user’s browser or an AI-powered chatbot that supports a customer by responding to their inquiries and pushes them through the sales process.

Additionally, in today’s quick-paced environment, customers expect faster response times from businesses. Nearly 82% of customers want a prompt response to inquiries regarding sales and marketing. You may handle issues or inquiries more rapidly by using the power of conversation marketing, which will increase client satisfaction and retention.

4. Data to be more creative – do it with machine learning in advertising

If you work in the advertising or marketing realm, you may have a fair understanding of what A/B testing is. AI tools can take A/B testing to a whole new level by making predictions about how different campaigns are likely to perform even before they go live. 

These insights help marketers take a proactive approach to creating personalized campaigns which can generate more leads and higher engagement rates. 

The application of historical data to determine what types of visuals and content will appeal to consumers and drive sales is one example of how machine learning may maximise the creative elements of your advertisements. 

Machine learning may also identify the context of an advertisement to determine its placement on a website. Personalization can produce creatives to target consumers according to their location and the weather. 

5. Is targeted advertising using machine learning possible?

As the name suggests, targeted advertising is a type of online advertising that micro-targets its customers. It primarily relies on the behavioural patterns of people from different demographics. Now that most of us spend a considerable amount of time on the internet, we are giving away personal information either intentionally or unintentionally. Simply put, if the device you are using is connected to the internet, you are leaking personal information to advertisers in one way or the other. 

Targeted advertising has been around for quite some time now. Today, most brands have recognized that their target audiences are diversified and the “one campaign fits all” approach will not get them the desired results. Therefore many businesses are turning to targeted advertising to increase engagement and boost revenue. 

Tech giants including Google and Facebook are on board with the idea of targeted advertising using machine learning. These companies earn a noteworthy chunk of their revenue by micro-targeting the users and advertising products to them. 

Thus, it is a good idea to explore the possibility of targeted advertising using machine learning to get the best results. 

6. Advertising without cookies

Internet cookies during online shopping

Industry research confirmed that many marketers overspend on ineffective advertising. It might be expensive to convey your message to the wrong set of people.

However, without cookies, advertisers may have a hard time using data to achieve results. Additionally, businesses must offer personalized experiences without coming across as intrusive in light of new legislation and rising pressure from consumers demanding privacy.

Companies may identify which messages appeal to their audiences by utilizing machine learning and ad targeting. AI can then use contextual cues and precise weather data to evaluate which advertisement is most likely to result in conversions. Machine learning can deliver these ads and messages without using cookies and while maintaining data privacy.

Final thoughts

All the points mentioned in this article indicate the benefits of machine learning in advertising. Machine learning models are accurate, effective, affordable, and give you the best results. Today, nearly 41% of advertisers are leveraging machine learning to offer customization at scale [4]. 

All these trends suggest that machine learning will play a key role in shaping the future of advertising. We expect brands to forge stronger relationships with customers by personalizing their ad campaigns. 

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Feature Image Source: Photo by John Schnobrich on Unsplash

Image 1 Source: rawpixel.com

Image 2 Source: rawpixel.com

Image 3 Source: rawpixel.com


[1] [2]  Morgan. B (2020) “50 Stats Showing The Power Of Personalization” Forbes [online] Available from: https://www.forbes.com/sites/blakemorgan/2020/02/18/50-stats-showing-the-power-of-personalization/?sh=4f01c6d02a94 [accessed October 2022]

[3] (2022) “2022 STATE OF MARKETING AND SALES AI REPORT” Drift [online] Available from: https://www.drift.com/books-reports/state-of-marketing-ai/ [accessed October 2022]