Programmatic ads help brands automate and optimize their campaigns

Programmatic advertising, in simple terms, is the automated trading of online advertising space. It leverages Machine Learning (ML) and Artificial Intelligence (AI) to buy and optimize online campaigns. This reduces manual effort and negotiations with publishers, ensuring the focus stays on optimizing campaigns in real-time.

The process is smart and instant too. Here’s how it works:

• When a person visits a website, the ad impression is put up for auction (Supply side platform)
• The interested advertisers offer their bids for the ad impression (Demand side platform)
• The highest bidder is selected to showcase their ads.
• The ad is served to the user.

Programmatic ads can be useful for companies across industries. Back in 2014, Kellogg’s saw some impressive results. It ran programmatic ads in the digital space to drive offline sales. The brand enjoyed +70-80% impressions and 2X improved targeting. This was topped up with hyper-targeted ad campaigns.

Programmatic ads promise enhanced reach and improved marketing ROI 

It is estimated that 88% of US digital ad spending will be programmatic by the end of 2021. It offers a more efficient and effective strategy for marketers looking to better their performance and returns. The major advantages are:

1. Increased reach and scale: Multiple ad exchanges and networks work together to offer ad space and inventory to advertisers. Advertisers can thus run campaigns at scale, while enhancing the reach.
2. Real-time optimization: Access to real-time insights helps advertisers focus on optimization techniques. This is better than spending energy on negotiating for better/more ad space.
3. Less wastage: Since the process is automated, impressions are not wasted. Marketers are also in better control of their campaigns as adjustments and enhancements can be made proactively. 
4. Better marketing ROI: The focus is on getting relevant visitors. This ensures better CTRs and enhanced ROI.
5. More transparency: Marketers have a better understanding of the sites on which their ads are appearing. Impressions, prospect activities, and other relevant stats also help make the process smoother.

Programmatic ads offer a range of targeting options

4 key types of targeting work in the world of programmatic advertising. Let’s take a look:

• Audience/Behavioural targeting: It targets users based on their behaviour, browsing history, and/or demographic data. Data like gender, income, age, location, etc. are looked at. The issue with this type of targeting, however, is that it depends on a users’ private data. This has become problematic in the recent past. With cookies phasing out soon, this strategy might not give long-lasting results.
• Website targeting: It targets specific websites for the ads to be rendered on. This strategy works best when marketers know which websites are relevant to them. But, it could limit the playing field as other relevant sites might get missed out.
• Retargeting: It re-engages users who might have previously interacted or seen a particular ad from a brand. This strategy focuses on getting users back to a brand’s website or to continue an action. It works well for persuading users to complete an action like purchasing an item or downloading a content piece. This again is a tricky territory as the dependency on user data is massive. Also, the websites where the ads get rendered might be irrelevant. 
• Contextual targeting: It targets relevant content and context instead of users. This is a better strategy as there is no dependency on user data. It targets websites/pages based on the relevance of their content to a product/service being advertised. AI helps make the targeting a lot more precise. Sentiment analysis, brand safety, relevancy, and brand suitability make this a potent combination and strategy for marketers.

Contextual targeting – A marketer’s best bet

As we saw above, there are different types of programmatic ad targeting strategies but they all have some dependencies on user data. This, however, is not true for contextual targeting. 

Let’s say you have clicked on an advertisement or simply visited a website. An ad of that particular brand might appear many times as you surf the web, leading to ad fatigue and poor user experience. Often, these ads appear on random websites too. 

This is the problem with audience targeting and retargeting strategies. Even if you consider website targeting, the marketing universe could sometimes become a little limited. For example, assume that you are a brand selling luxury cars. There are only a limited number of sites that you can list down for website targeting.

With contextual targeting, you can expand your universe to list down relevant sites like fashion or lifestyle. These categories will help you reach your target audience in a smart, well-rounded manner, while still being relevant. It helps look at the complete context of a website and undertakes a human-like analysis of the page and all its elements. Text, video, imagery, URL – all of these are analyzed in totality to understand the context well. Hence, the ads can be placed in a way that matches the environment around them.

A good contextual advertising tool can help take your brand places. In fact, it can help you take your brand to all the RIGHT places, guaranteeing better marketing ROI. Your brand can leverage the power of AI and ML to optimize ads and keep innovating. Contact us today to know how!

Contextual Targeting·

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