Ricky Ray Butler is CEO of BEN, an entertainment AI company that places brands into influencer, streaming, TV, music and film content.
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Today’s brands can leverage influencer armies to activate marketing campaigns of all sizes — whether it’s a targeted push with a few local creators or a multi-million-dollar activation with hundreds of creators internationally. But even as the creator economy continues to grow and decentralize, “96.5% of YouTubers makes less than $12,140 (the federal poverty line),” Fast Company reports.
What if another reality is possible — one where brands can almost instantly scale to work with millions of social media creators a month and reach endless audiences? A future where more than 3% of creators can form valuable partnerships with brands? It may sound outlandish, but that reality is much closer than you might think — and it’s all thanks to automation.
Taking a step back, it’s important to contextualize influencer marketing against the backdrop of the evolution of modern-day advertising. Today, the advertising industry faces a new, unruly set of challenges: according to research, roughly 40% of adults use ad blockers, 90% of people skip pre-roll ads, and more people are turning to ad-free streaming platforms like Netflix than ever before. Besides diminishing the efficacy of traditional advertising methods, these behavioral changes point to a deep desire for brand-to-consumer interactions that are more authentic, natural and, most importantly, non-disruptive.
Even with these challenges, entertainment advertising continues to be largely driven by human intuition and relationships. It’s no surprise, then, that there is a significant appetite to infuse marketing with the analytics, predictive capabilities and scale that AI has to offer. We’ve begun to take a step in that direction with increased AI capabilities, but in order to fully implement this type of technology more widely, we must turn to automation.
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Learning From Past Lessons
Why is it that automation has failed to take off so far? At the most basic level, algorithms require a significant amount of data input to effectively predict and automate tasks, and previous attempts at automation have only scraped the surface of capturing all possible data. That’s where the problem lies: no one program has tackled 90% of the data — both structured (including likes, clicks and views) and unstructured (images, audio and video) — required to capture the elements of human creativity necessary to build an effective influencer marketing campaign.
However, the growing appetite to scale influencer marketing is creating urgency around developing an end-to-end, automated marketplace for campaign partnerships. To do this, we need to identify the objectives and opportunities of each piece of the influencer marketing pie. From there, we can build and train algorithms that are able to make decisions that take into account the nuances of creative marketing campaigns. This can only happen with more data, which is only continuing to increase in a world of decentralized content and creators. This also ties into attribution and execution at scale — something marketers and advertisers never had enough data to experiment with.
To meet this goal, we must begin with predictive analytics, such as algorithms that can predict story views and identify key influencers based on predetermined criteria. By first focusing on predictive analytics, agencies can minimize the guesswork involved with a brand and creator collaboration and provide an educated estimate of the ROI of a campaign as well as fuel attribution.
The industry has already begun to make strides in predictive analytics, introducing features like fraud detection that predicts what percentage of a creator’s audience is bots. Other tools, like image and audience mapping, can identify ideal creators or audiences by feeding deep-learning algorithms to identify creators with similar content or overlapping engaged audiences. However, to effectively gain these insights, the models must measure and analyze both structured and unstructured data.
With strong predictive analytics models in place, the influencer marketing industry must continue developing algorithms and conducting regular post-mortems to improve AI capabilities. That feedback loop is critical for ensuring that automated processes continue to become smarter and more effective over time.
Automation has historically struggled to replicate the nuances of what we call the “human touch” — things like recognizing the difference between a Reel and a TikTok video, even if on the surface they look the same. Furthermore, influencers and consumers are not machines, and they are guided by both emotion and logic to make decisions — something algorithms often fail to account for. Every creator is unique, and humans can often navigate these intricacies more seamlessly than AI.
To effectively address this challenge and build AI that effectively captures the nuances of human creativity, we must develop collaborative AI. This will require a best-in-class team working alongside algorithms to correct mistakes and ensure that processes can scale quickly. When scaling AI, models can easily become oversaturated and fail to distinguish platforms, patterns and content opportunities. With humans working closely to train these models, they can guide the algorithms and avoid oversaturation as well as model drift — without requiring 20 years for training.
Creating Better Opportunities For Brands And Creators
As we drive toward an automated future, we will be able to click into influencer marketing with the same ease and efficacy of digital advertising on Facebook. Soon, any company — from a mom-and-pop shop to a major corporation — will be able to input a set of parameters, such as target audience and KPIs, and learn instantly what sort of ROI to expect from an influencer marketing campaign.
This is an exciting development for both creators and brands: More creators will be able to build and sustain businesses based on brand partnerships alone while the barrier to participate in influencer marketing will be drastically lowered for brands. In the same way that ATMs made banking easier, now, automation will make the creator economy thrive like never before.
If done correctly, we can learn from the last 100 years of advertising and invent a new, authenticity-driven path forward for influencer marketing that empowers brands and creators.
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Author: Ricky Ray Butler, Forbes Councils Member
