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Everything You Need to Know About Influence Marketing and Artificial Intelligence

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One of my professional resolutions for this year was to learn as much as possible about artificial intelligence (AI) and blockchain. Half of this research has already resulted in a free ebook, titled "Everything You Need to Know About Marketing Analysis and Artificial Intelligence." One of his chapters focuses exclusively on marketing and marketing. Influence and AI, and I would like to share with you I've learned that you can make the best decisions possible when choosing a supplier.

There are two types of influence marketing solutions that fall into one of these categories: paid media or earned media. In general, I'm talking about paid solutions like Influence Advertising (it's one of the oldest forms of native advertising). The term influence marketing is generally used just to describe the solutions gained. The main difference between the two is whether a solution can facilitate a financial transaction or a type of counterpart transaction between the brand and the influencer.

The vast majority of artificial intelligence-based influence marketing solutions today fall into the category of deserved media – which means that they only identify one another. influencers and let the marketer communicate with them. Whether or not the marketer offers them a financial incentive is irrelevant to the solution used to identify them, it is still considered a media solution won.

Paid media solutions, influential advertising, tend to use IA differently because their networks of influencers are already established in their closed ecosystems. This allows them to access unique data feeds, such as past campaign performance and the prices charged by influencers.

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Of the 23 technology providers identified in this space, only a handful of them claimed to use the AI.

Influencer won Media Solutions and AI

There is a marked difference between AI-powered marketing solutions and those that are not.

Solutions without AI usually focus on tracking engagement and outreach – vanity measures in the social field that can often be faked. This information is considered a structured data that can be pulled directly from the social networks themselves for pay and analyzed by a technology other than the AI ​​to identify who is influential by these parameters.

Artificial intelligence solutions, on the other hand, analyze structured and unstructured data to decide which accounts are most influential. These solutions are not blocked by exploring a data source, but rather, have unfettered access to almost 100% of the sphere of potential influence of a brand.

He uses network science to determine relevance and timing. This helps to establish the most connected (most powerful) influencers by talking about the most relevant topics at a particular time.

In addition, artificial intelligence is used to map the relationship between social content and content (traffic efficiency, engagement and sales) because the two channels are closely related. Machine learning and natural language processing are essential elements in the fight against unstructured data such as content.

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This feature also includes the content of a brand: it can associate each article to the best social influencers active in the sphere of influence of a brand, recently wrote / talked about similar topics and has a very engaged public. This approach can help improve any content distribution strategy.

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Solutions such as these allow marketers to choose the right influencers for their campaigns the first time, easing the challenges of choosing false positives.

Influencing Advertising Solutions and AI

Although it is advertising of influence, I have chosen to include it in the marketing of influence for obvious reasons. In addition, your average marketer does not discern between earned and paid influence marketing solutions.

Research has uncovered four major uses of AI technology in advertising-based advertising. As mentioned earlier, these solutions have a closed ecosystem of influencers. Their influencers have agreed to enlist in their community.

  1. Natural language processing of past social posts (both the influencer and his followers) to determine the relevance of a mark.
  2. A determined AI score that includes unstructured data such as engagement, content, followers sentiment, traffic, views, clicks, influencers costs, past campaign performance, and so on.
  3. Disclosure is the law in the United States for native advertising. The FTC has rules governing this and influencer advertising is no exception. The AI ​​is used to signal the content of the influencers that should be disclosed. This is an added insurance policy for the brands.
  4. Alas, some of these solutions still boast their use of image identification and personality detection using artificial intelligence. This is a basic use of AI that has been around for many years and does not provide near value as advertised.

Multiple studies show that for every dollar spent on marketing influence, it returns six or more. This is a good sign for marketers who are embracing this approach to marketing, but it's an even better sign for influencer software companies that incorporate AI.

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This means that influencer identification will become smarter, a preferred level of scale will be achieved, and the impact and performance of the campaigns will be even better. I predict that in the coming years, we will see this return on investment continue to improve.

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In the past two years, artificial intelligence has slowly been imposed in the marketing of influence. Not so long ago, brands were forced to analyze lists of supposedly influential people who were building their suite using bots, software and shenanigans to determine who was genuine and who did not. ############################################################### Was not. These days are now over.

To learn more about AI and marketing continue to read my column on relevance, check out Paul Roetzer's Marketing Institute AI Institute and download my new ebook free. A version of this article was published on SMT .