Influencer marketing has grown from a vocational idea to a dominant industry within the last decade. According to a report from eMarketer, the number of US marketers leveraging influencer marketing is expected to grow by over 17% from 2019 to 2022.
In this post, we’re going to explore how technology is revolutionizing the influencer marketing space.
Why Businesses Need Influencer Marketing?
Influencer marketing is partnering with social media stars to promote a brand. These influencers can be celebrities, bloggers, or micro-influencers, who aim to connect with an audience authentically and genuinely before they start marketing brands.
The rise of influencer marketing has been fueled by several factors: the increase in mobile usage and digital advertising, the fact that brands are looking for more efficient ways to reach consumers, and increasing competition from other types of advertising, such as content marketing.
Influencer Marketing has become more popular as people spend more time on social media platforms such as Facebook, Instagram, and Snapchat. Businesses realize they have limited budgets when it comes down to advertising their products. Hence, they need innovative ways to communicate their message without spending too much money.
Influencers have grown exponentially over the past few years, which means there’s a higher chance that followers will engage with them than in traditional advertisements found on TV commercials or billboards. The reason is that interacting with followers feels like they’re interacting directly with someone they know rather than just watching something on mute while scrolling through Instagram stories all day!
How Technology Is Reshaping Influencer Marketing
Now that we know what influencer marketing is, let’s delve deep into how technology is helping accelerate this field.
Use of Artificial Intelligence for Generating Insights
The use of artificial intelligence (AI) for generating insights has been around for a while now. However, the application of the technology to the influencer marketing space is a recent development.
AI can automate generating insights and data analysis by performing tasks that humans may find difficult or time-consuming. AI can analyze data and provide insights automatically—without any human intervention. To this end, AI will also be able to identify patterns and trends in large amounts of unstructured content such as blog posts, social media posts, comments on forums, etc., which would otherwise be impossible for humans alone.
AI can also make predictions about customer behavior based on past behavior patterns, allowing marketers to plan their campaigns more efficiently by analyzing trends in customer preferences using historical data available within a Customer Relationship Management (CRM) system.
Content Creators Can Now Edit Videos on the Go
Videos have been a crucial part of marketing, regardless of your chosen strategy. Influencers use both short and long-form videos to market brands in front of their followers. While recording a video and editing it was a daunting task in the past, the advent of technology and software makes the process straightforward.
Influencers can now record, edit, and add captions to a video from a single platform. Take, for example, BIGVU. It is a video editing software platform that allows scripting, recording, editing, and sharing of videos from a single place. The platform also boasts of a capable auto-captioning feature. Marketers can use BIGVU’s auto captions feature to add captions to a recorded video within minutes. Moreover, they can translate the captions into different languages.
Similarly, multiple software platforms make recording and editing videos simpler. As the technology behind such software grows, they make video content creation easier for the influencers.
Matchmaking With Data Analytics
Matchmaking with data analytics is the process of finding the right influencer for your brand. It’s a highly data-intensive process that requires you to look at every aspect of each influencer’s following and engagement rate. However, it can also be beneficial in finding people who might be worthy of collaboration.
Since humans cannot analyze such vast data quickly, analytics comes into the picture. The first step in matchmaking is using data analytics to find potential influencers who have a similar audience size as yours but are not too similar to not cannibalize each other’s audiences. The second step is looking at their engagement rates (likes per post), indicating how much interaction they get from their followers and how engaged they are with them.
The last step is looking at what type of content these influencers use the most often; for example, if an influencer uses mostly videos or photos on their Instagram account, then that would be something worth considering when creating your own campaign strategy because you know what kind of content resonates best with them and their audience.
Data analytics can analyze all such information within a few seconds to generate actionable insights. Businesses can then use the data and insights to make better matchmaking decisions to ensure higher success rates.
Algorithmic personalization is the act of using algorithms to create personalized content for a user. For example, you might like that your favorite store sends you coupons on your birthday and offers discounts when they’re having a sale. This personalization can be applied to influencers or brands as well.
Algorithmic personalization uses a machine-learning algorithm to create user recommendations based on previously recorded behavior patterns. In terms of influence marketing, this means that brands can provide customized experiences for each consumer based on their unique preferences—a potent tool!
Measuring Campaign Results
Measuring campaign results is a crucial part of the influencer marketing process. There are two main ways to measure the results of an influencer marketing campaign: using data and using qualitative feedback from brands.
Technology allows gathering the data and analyzing it. To begin with, Robotic Process Automation (RPA) software can monitor and collect data based on the digital footprints of individual audiences. They can fetch data like who liked the influencer’s content, who engaged with it, and who didn’t.
Businesses and influencers can then use this data and break them down into various metrics to create a user persona. For example, they can find the audience’s age group likely to engage with their content, location, and other demographics. This will help them create personalized content for such audiences.
Technology can also help collect qualitative feedback from various sources. Feedback allows you to gauge customer sentiment about their experience with your product or service, allowing you to adjust accordingly if necessary. Ultimately, it’s essential not only for brands’ bottom lines but also for customers’ satisfaction (and therefore loyalty) that social media campaigns are successful!
Influencer marketing is a crucial piece of the digital landscape today. With the democratization of content creation and the rise of social media, influencers are no longer just celebrities but everyday people. This has resulted in a large creator ecosystem with different types of creators businesses need to manage effectively.
Technology provides businesses with new ways to effectively approach the influencer industry and measure campaign performance. These solutions will be crucial as companies adapt their marketing plans in a post-COVID world where much economic activity happens online.