The technology behind influencer marketing has come a long way in recent years, allowing brands to scale their campaigns and take labor-intensive research and planning out of influencer marketing. As a result, influencer marketing has grown in ways we never imagined and is now a standard part of any brand’s marketing mix.
The rapid success of influencer marketing has been astounding. But when this type of success story occurs, it is always a good idea to look at past advertising trends to avoid past mistakes. Automated advertising is one of the prime examples of the advertising trend that has spread in the past 15 years.
Programmatic advertising paved the way for a new digital marketing landscape and enabled brands to automate the purchase of ad space. While there were great benefits to automated advertising, there were also weaknesses as well.
In this article, we explore the pros and cons of automated advertising, and break down the lessons we can learn from this era.
What is automated advertising?
Automated advertising is the automated buying and selling of digital advertising. This method of advertising allows brands to purchase ad space using artificial intelligence and machine learning, and place their creations on sites that aim to reach their target audience. The most recognizable forms of automated advertising are things like banners and buttons on websites.
The automated process of purchasing ads is done using a Demand Side Platform (DSP), which optimizes ads based on the audience and actions they want to promote. DSP uses algorithms to purchase ad impressions and ad space from multiple publishers. In this sense, brands can purchase ad space across a variety of formats and platforms in milliseconds.
By using specific data points such as location, demographics, user behavior, and online activity, ISPs can target the user with content that meets their needs. It’s a win for both the publishing site and the brand. Publishing sites can host ads that their users actually want to see, while also making money from ads without any manual work.
On the other hand, brands also benefit from very low labor costs and can use data and technology to reach the right people at the right time. Automated ads always target a specific audience using different data points, making it a low-effort, data-driven method that is easy for brands to use.
Automated Marketing vs Influencer Marketing
Programmatic advertising has many similarities with influencer marketing and many similar benefits as well.
Lower labor intensity for brands
Brands love both automated advertising and influencer marketing because it requires less customer labor.
Programmatic advertising improves digital campaigns, without the need for planning and manual research. Running successful campaigns doesn’t require a lot of specific knowledge and can save brands time and money.
Likewise, influencer marketing uses the intelligence of the creator to craft campaigns. By taking advantage of audience insights and creative abilities, influencer marketing can be a very ineffective approach. Like automated advertising, influencer marketing can be powered by technology that helps optimize campaigns and reach a highly targeted audience.
Allows brands to operate at scale
One of the many benefits of a programmatic approach is that brands are able to pay for high-performing content, based on data-driven algorithms. By taking a less specific approach to the publishing sites they work with, brands can scale their campaigns in no time.
This is similar when working with content creators, where brands can draw from hundreds of content creators and work at scale to bring their products or services to their target audience. Operating at scale is valuable for brands looking to push a product or service quickly, such as during the launch or growth phase.
Enables brands to reach a broad audience
By using algorithmic purchasing of ad space, brands can reach a broad demographic of an audience. Purchasing ad space programmatically means that brands can decide on the design and then submit it to a variety of potential publishing sites.
The same is true for influencer marketing. If a brand wants to run multiple campaigns targeting a variety of audiences, it can. Collaborating with a variety of content creators means that a brand can easily reach a broad demographic of an audience. This is especially useful for brands looking to explore different demographics.
What can we learn from programmed mutation?
While automated advertising has boomed dramatically, there have also been challenges that those in the influencer marketing industry can learn from.
Some of the main lessons we can learn from are:
Impressions are important, but integrity is more important
The downside of relatively quick and cheap results is often a compromise on quality. This often comes when brands see their ads on websites that don’t match their values.
One example of this subtle danger starting to pay off was when JP Morgan Chase accidentally displayed ads on a site titled “Hillary 4 Prison”. DSP picked low-quality impressions as part of its automated campaign, hoping to draw the attention of millions to its ads. While gaining a lot of impressions can be great, it is only useful if the site is relevant. In this case it certainly wasn’t.
For brands that keep their reputations high, an automated approach is not the safest option, as their ads may end up in places they don’t necessarily choose. Without quality assured placements, brands run the risk of gaining a negative reputation as a brand that lacks integrity. In cases where a software error occurs, a PR nightmare can ensue.
Influencer marketing can learn from these mistakes and take into account any brand risks. These could be things like partnering with an unreliable creator whose ethos doesn’t align with their own, retargeting the audience too often, or placing their ads in front of an unbalanced audience.
If anything can be learned from the mistakes of automated advertising, it’s that working at scale is important, but brand integrity is even more important. With both automated marketing and influencer marketing, brands have to keep in mind that while they are guaranteed to reach their audience, that doesn’t necessarily mean the partnership is a good match. In fact, it could be the other way around.
Always subject to approval processes
One of the main challenges affecting bot ads is seeing ads across multiple formats and devices. Automated advertisers often end up seeing their ads display in all kinds of weird ways on devices that the creative wasn’t designed for.
There are not necessarily approval levels when it comes to posting content, as the process is automated. This can lead to errors in the design.
What can influencer marketing learn from this fatal mistake? You always have a certain level of approval process. Asking the right questions and making sure all restrictions are discussed before agreeing is key, no matter what form of advertising you use. Having at least one level of approval reduces the error space!
The Waves by Influencer platform provides clients with multiple levels of both creator and content approval, in order to ensure brand integrity. Waves’ creator approval process provides clients with a panel that allows key stakeholders to move creators through the various stages of the approval process; Allow collaborative feedback among all stakeholders to improve productivity. Similar to the creator approval process, customers will be able to review content that has already been thoroughly vetted and approved by the expert Influencer campaigns team within the company. The content must then be signed by the brand or agency if appropriate.
Reliance on third party cookies
One of the main problems faced by automated advertising is data protection and privacy concerns. Automated ads rely on third-party cookies, which are slowly becoming unfavorable to the masses. Behavioral targeting relies on this specific audience data to customize campaigns, and without it audience targeting can be very random.
10 or so years ago, third party cookies were not an issue. Most users didn’t have a problem with them, and many didn’t know what they were. It’s only in the past decade that users have begun to decline third-party cookies, which has made automated advertising very difficult. Without access to behavioral tracking and audience insights from third-party data, automated ads struggle to target audiences precisely as they did before.
What can influencer marketing learn from this? Not relying on third party data to market to their audience. Influencer marketing techniques such as Influencer.com ensure brands reach their target audience through formal partnerships with social media platforms. It also collects first-party data directly from the creators to ensure that the brand’s message can be as highly targeted as possible.
lack of transparency
When the software first flourished, there were very few controls in place. In many ways, this was similar to the early years of influencer marketing where there wasn’t much regulation on ads.
As a result of the lack of standards and regulations in the programs, agencies can inflate costs and incur clients’ advertising expenses for themselves. In the initial program boom, it was common for brands to pay huge fees to agencies that weren’t transparent. For every £1 a brand thought was spent on advertising, 25p would go straight into the agency’s pocket.
Brands looking to take advantage of influencer marketing should consider this lesson and look for influencer marketing companies that fully comply with influencer marketing regulations, such as those that ensure creators are transparent about ad labeling.
When automated advertising hit the scene, it has completely boomed and is still seeing huge successes for many advertisers. While the industry initially had some issues, many of them are now settled and can serve as a blueprint for things to be avoided in other similar industries, such as influencer marketing.
The influencer marketing industry has experienced tremendous growth over the past few years and is well on its way to continuing this path of success. To continue going in this direction, it is important for the industry to look at the trends of the past few years and learn from some of the mistakes others have made.
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