Automation within the influencer channel

In part three of a series that deep dives into different digital channels, we spoke to influencer marketing experts Buzzoole about how the influencer channel is using, and embracing, automation.

How is automation currently being used within the influencer channel?
Within the Influencer Marketing industry, automation is being used in two main areas: to measure brand affinity and to optimise campaign management.
With regards to brand affinity, AI algorithms can scan thousands of images and identify the right Creator to match the brand request. The system processes data from both the brand and the Creator (or Influencer), to analyse context, behavioural patterns, as well as visual and textual content, and identify brand affinity. Using brand affinity as the metric, companies are able to identify Creators who are most likely to become effective brand ambassadors. Brand affinity improves search relevancy, and ultimately, enhances the accuracy of brand-influencer match.

When it comes to campaign management, automation improves the management of the campaign (automated invitation, selection and approval of Influencers) and reporting (real time reporting and access to first-party data through the use of APIs). Just a few short years ago Influencer campaigns were predominantly considered as a laborious manual process, automation has changed the game allowing for a much larger scale approach, as well increasing efficiencies in other areas.

At what stage of an influencer campaign can you use automation?
While not widely adopted yet, AI enables business systems to operate with granular precision and achieve scalability that simply isn’t possible at a human level. Where it comes into its own is in data-heavy or repetitive processes. For example: During campaign selection AI is used to create efficiencies at scale by using AI and image recognition to identify (sometimes) large numbers of Creators or hone in on a very narrow type of Influencer and eliminate a manual review process to improve search relevancy, and ultimately, enhance the accuracy of brand-influencer match.

Automation is effectively used in campaign management from set-up to reporting - both at the end of the campaign and in real-time, for example through automation we can quickly analyse a wide range of metrics and easily identify the campaign posts with the highest engagement or identify the two or three Creators whose posts had the highest engagement in a campaign. Automation also allows for adjustments and optimisation of a campaign based on real-time campaign trends and easy visualisations showing the campaign’s day-to-day progress and impression peaks either as aggregated data or by activity type, engagement and/or channel. For example, sentiment analysis driven by a Creators’ content and expressed in the form of comments requires the analysis of thousands upon thousands of comments across multiple channels (FB, IG, TW, YT, Blog posts etc...). Again, not something that is possible to do accurately in a manual way.

Being able to crunch large amounts of real-time, first-party data is essential when it comes to vetting Influencers and selecting the right Creators for a brand, but also when it comes to measuring the effectiveness of campaigns and reporting. Transparency on metrics and solid tracking against a brands objectives is a must for businesses wishing to gain actionable insights and prove their value to their customers.

What are the current benefits of using automation the influencer channel?
Advanced algorithms allow scalability. Platforms drawing on AI are able to effectively search through millions of Influencer profiles, and spot talent and brand affinity in a fast and efficient way. Throwing up not only what a brand has specified or expects to see, but challenging it to look at wider pool of influence. A purely manual process tends to lead to decisions solely based on an advertisers subjective taste. The advent of both data-driven and automated approaches not only supports speed and scale, but challenges the brands preconceptions and pushes them to think differently and more authentically.

What are the current challenges to using automation the influencer channel?
There are a few things to look for when choosing an AI-powered Influencer service, the most important one is data. At the very core of the Artificial Intelligence used to automate Influencer Marketing campaigns there is statistical machine learning, which are intelligent machines that can learn from the data they analyse. That is to say they are data-driven, so the quality of the data is crucial to the entire process. There are two main types of data: first-party data –first-hand data coming from APIs or the platform where it was generated– and third-party data –often inferred or obtained through intermediaries and services that pull the data from some first-party provider.

That said, the two main challenges related to automated Influencer Marketing campaigns are:

• Quality of data: Having access to real-time, first-party data is essential when it comes to vetting Creators and Influencers, selecting the right individual for your brand and measuring the effectiveness of the campaign.

• Transparency on metrics: When choosing an agency, ensure they can provide transparent metrics and solid tracking against your brand objectives. Also, make sure you understand what that data really means and how it was calculated.

What one top tip would you give to advertisers and agencies who are running automated influencer campaigns?
Automation cannot completely replace human input. For example, Artificial Intelligence can simplify and speed up processes — it can even replace humans in certain repetitive and data-heavy processes. However, Influencer Marketing is a human-to-human activity, and as such, human interaction is still important. People are looking for engagement and meaningful experiences that AI alone just can’t provide. What AI does best is free up time for us humans to focus on value-adding activities, such as creativity.