5 Problems with Programmatic Native Advertising and How to Fix Them with AI

[Sponsored] There have been many complaints over the years concerning digital paid media in general and programmatic native advertising was supposed to help fix this. It hasn’t for some very fundamental reasons.
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Chad Pollitt

By Chad Pollitt
VP of Marketing at inPowered
Indiana, USA
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This is a sponsored post by inPowered

There have been many complaints over the years concerning digital paid media in general. From banner blindness and fraud to pricing schemes and budget waste, programmatic native advertising was supposed to help fix this. It hasn’t for some very fundamental reasons.

However, before we get into the way it can and should fix these problems, let’s explore some of them.

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  1. Paying for impressions – Fraud runs rampant across all forms of digital paid media. Ad units can be seen by a lot of bots and few humans, load behind other ad units or graphics and never get seen, don’t fully load, or are simply shown to the wrong audience, altogether.  
  2. Paying for clicks – This actually works fairly well for search and its advertisers. Google has defined four micro-moments – I want to know, go, do or buy moments. Therefore, searchers have a specific intent when they query a search engine. This isn’t the case with programmatic native advertising delivering top funnel content.
  3. It’s not display so quit treating it as such – this channel has long been used to deliver mid to bottom funnel content. Sure, it has been used as a brand awareness channel, but the problem with that is (according to Nectar) 91% of total ad spend is viewed for less than a second. Some advertisers are using these blind banner positions and trying to make them look like native units while delivering the same old mid to bottom funnel content. It’s still display and suffers from the same problems. A pig with lipstick on it is still a pig.
  4. Two out of three people that click bounce in 15 seconds or less – This was a study by Chartbeat Analytics and shows that marketers and advertisers must pay for three clicks to get just one meaningful engagement with top-funnel content on programmatic native channels. It also means that 66% of programmatic native advertising is wasted. An engagement, in this case, is defined as 15 seconds or more.
  5. Content marketers want engagement – There have been very few successful attempts from programmatic native advertising technology to optimize towards top of the funnel content engagement. Instead, almost all of them optimize towards clicks or impressions. This is problematic if it’s engagement sought by content marketers.   

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Even though almost all the programmatic native advertising platforms charge based on impressions or clicks, it’s possible to use an AI layer to move into a cost per engagement (CPE) model.

Each issue mentioned above could indeed have their own articles written about them. It means there’s plenty of room for improvement to be had with programmatic native advertising as a channel to amplify content at scale. Recent technological advancements in artificial intelligence (AI), machine learning, deep learning, etc. is the solution.

AI is most impactful when it has very big structured and/or unstructured data to access. The more data it has the better and faster it learns. Even though almost all the programmatic native advertising platforms charge based on impressions or clicks, it’s possible to use an AI layer to move into a cost per engagement (CPE) model with pricing that dynamically drops lower over time (dCPE).

However, to make this happen requires a massive amount of scale. To achieve this level of scale requires technology that can reside over dozens of programmatic networks. By themselves, each programmatic network will struggle to get the scale needed to use AI to change pricing into dCPE. Here’s how it works.

AI-powered CPE (dCPE) is designed to eliminate the above problems with programmatic native advertising today and give content marketers what they really seek

According to Rebecca Lieb, Analyst and Founding Partner at Kaleido Insights, “inPowered’s AI technology doesn’t just give brands what they’ve always wanted, engagement with their content, but it does so at the most efficient price possible.”   

In the past year, inPowered has formed strategic partnerships with leading brands to determine the price to charge for 15 seconds of post-click engagement based on the actual cost it would take to deliver that engagement.

They have the scale necessary to achieve this by integrating with 35+ native advertising and social channels and has developed AI and deep learning to offer brands the ability to only pay for the cost it takes to get consumers attention for 15 seconds or more in real time.

AI-powered CPE (dCPE) is designed to eliminate the above problems with programmatic native advertising today and give content marketers what they really seek – engagement with the content being promoted at the best price.

This is a sponsored post by inPowered


Would like to know much more about native advertising, join us in Berlin for the world’s foremost conference on native advertising, Native Advertising DAYS

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