The term “artificial intelligence” is an umbrella term that covers a variety of machines that learn, with the assistance of humans or entirely on their own. AI technologies can perform certain impressive cognitive tasks solely or better than humans. That means machines can see and identify images, read and understand text, hear sounds and understand them, physically move around obstacles, and sense their external environment. Knowingly or unknowingly, we use AI in our daily lives such as Gmail and Google Docs use AI to read what we are typing, then understand it enough to recommend what to type next through their smart compose tech. Facebook too uses AI to detect who is in our photos, then recommends who to tag. Self-driving cars use AI to detect obstacles and drive in a safe and effective way. Likewise, our phone uses AI to understand our voice commands and create responses that make sense.
Because AI has a couple of advantages over traditional software, it is transforming industries from finance to healthcare to retail dramatically which includes the transformation of how work is done, providing surprising revenue opportunities, and significantly cutting costs. Similarly, using AI in advertising could potentially help brands and marketers to leverage online space in an efficient manner.
AI-powered Contextual Advertising:
Earlier versions of the contextual targeting strategy had obvious limitations and it has been put out of sight to a small role in digital advertising. Behavioral targeting was one of the dominant approaches in a data-rich environment that allowed brands to accumulate information about users from a variety of different sources which accurately used to identify their interests and effectively target ads. To achieve the kind of specific targets, an advertiser would have to rely on labor-intensive methods such as keyword search, this leads them to suffer from the opposite problem of a lack of scale.
Today, more brands should give contextual targeting a second look because privacy concerns are a major catalyst, as growing restrictions on third-party data collection are putting a check on the several numbers of data that advertisers can use for behavioral targeting techniques. With the gradual removal of cookies and other identifiers from the digital advertising ecosystem, the brands increasingly can have an incentive to turn to established, privacy-safe methods like contextual targeting. Contextual tools now are also much more powerful than they were a few years ago which makes it easy for programmatic advertisers to quickly adapt to the changing language of the internet by leveraging machine learning algorithms and the faster computation methods that artificial intelligence provides, and can refine their search parameters to identify more users that are likely to be interested in their ads.
The benefit of contextual targeting is more than its ability to protect user data privacy as its strategic advantage is that it enables an advertiser to deliver messages to consumers when the consumers are in an ‘interested’ frame of mind. When a user is browsing content about a specific topic, it signals their intention at that moment, often a more reliable indicator of purchase behavior than targeting based on previous browsing habits. This is carried out by data that shows contextual targeting can help lower cost-per-acquisition metrics for direct marketers, and it can also be effective in driving brand awareness.
AI Accuracy and space for its improvement:
Traditional software has access to large amounts of data. The software offers clarity to a marketer because they can see all our data in one place and perform tasks more easily. But it doesn’t offer any context about the data and it won’t tell them what to do with the data or what it means.
AI has the ability to process huge datasets at scale, and it is, however, “smart.” It can analyze the data at scale, then make predictions about what that data means, after learning. Some AI-powered systems have the ability to improve their accuracy over time, either with human assistance or by training themselves. That is why AI has started to gain traction in marketing and advertising.
Brands lack time, energy, or cognitive capacity to process all of this data effectively, even after having tons of data at their disposal from CRM systems, marketing automation software, ad platforms, etc. As a result, marketing and advertising performance suffer costing brands huge amounts of time and money. That is why entrepreneurs and forward-thinking market leaders should adapt AI for its ability to increase revenue, reduce costs, and build a massive competitive advantage. However, just because a system uses AI doesn’t mean it’s accurate. If the data used is appropriate, and the system itself is built to make use of that data, only then will it be productive. This way, AI outputs can be comparable to the inputs into the system.
In a short adaption of AI for advertising can reduce costs by acting on that data faster and automatically, build a massive competitive advantage with both superior insights and superior speed, and increase the revenue by analyzing and acting on data at their scale.
Authored article by Sameer Makani, Co-Founder and Managing Director, Makani Creatives.
