Even as influencer marketing has gone mainstream within social media marketing, the field is developing so quickly that it can be hard for marketers to keep up, or to know how best to take advantage of its strengths.
With consumer demands and expectations evolving at a rapid pace, the major influencer marketing KPIs are likewise in constant flux. Consequently, marketers are routinely flooded with new and better tools, services and strategies that promise to yield the best possible results for their influencer marketing efforts.
It’s no industry secret that influencer marketing already delivers results, hence its growing popularity. Some reports have even found that seven in 10 consumers are likely to purchase a product recommended by someone they follow. Moreover, according to a study from Influencer Marketing Hub, the average return on each influencer marketing dollar spent is $7.65, and can even reach as high as $20.
Yet, despite its clear worth, the technology to answer marketing executives’ million-dollar-question – what about ROI? – is still lagging. Unfortunately, measuring and improving ROI requires considerable guesswork.
Although marketers generally agree on the key ROI metrics for influencer marketing – for example, site impressions for brand awareness, social engagement for building a brand community, pageviews, bounce rates, new users and referral partners for website traffic growth – knowing how to best measure, analyze and improve on these metrics is a challenge.
As if that weren’t difficult enough, the sector is plagued by dishonest business practices, such as influencers with fake followers and a rampant lack of authenticity from many brandsOpens a new window on social media.
In fact, given the complexity quantifying a campaign’s success, ROI actually may not be the best metric at all. While ROI may look at spending versus return, it doesn’t necessarily take all the relevant performance factors into account.
Artificial intelligence can offer help in quantifying data and assessing results.
Artificial intelligence: converting data into guaranteed results
Fundamentally, brands and companies that work with social media influencers are looking for the most relevant figures that provide access to, and can best connect with, a target audience.
Whereas AI primarily has been been used by the sector for simple data processing, the latest technologies are capable of analyzing billions of data points to produce in-depth and valuable influencer marketing insights that go far beyond the basic online marketing metrics mentioned above.
The use of social media influencers, often approached warily by marketers, is now evolving into a more rigorous practice – thanks to data. AI goes hyper-granular to unearth more relevant information from a company’s social ecosystem, enabling more straightforward and streamlined influencer-brand partnerships and sponsorships.
Indeed, with that information in hand, marketers can approach influencer marketing as they do any other type of media buy – for example a TV spot, mobile or internet ad campaign.
Analyzing influencers like never before
With AI, marketers can track and categorize the type of content most shared by an influencer, as well as how engaged their followers are – in order to support a scalable approach based on predictive behavioral data rather than guesswork or results from sponsored studies.
In other words, this information allows marketers to examine an influencer’s reach, user engagement, social authority and influence to help identify whose tone, approach, values and followers most align with a brand’s ideals and campaign goals.
Consider the depth of AI: It can classify influencer qualities by detail, examining specific data sets ranging from follower and audience breakdown to brand affinity to past sponsorhip performance. It can even predict whether a specific influencer will produce results for a particular brand’s distinct goals (e.g. improving brand awareness, generating leads or qualified traffic and sales).
Crucially, AI can scrutinize an influencer’s past performance data, discovering which brands with which he or she has worked and identify the influencers who regularly drive high, qualified engagement with the products or types of content most relevant to a specific campaign or company.
And it can be done in minutes.
Targeting the right audience
These new AI tools enable companies to scale and increase engagement on every social media platform. As with the influencers themselves, AI can use data sets to help companies get their message in front of different demographics and geographic segments, using influencers to target audiences based on age, location, ethnicity, education level, life stage and even annual income.
Understanding sentiment analysis
AI-powered sentiment analysis means brands can be informed instantaneously on how a particular message is being received online by consumers. Real-time analytics and reporting in social Opens a new window mediaOpens a new window allows marketers to adjust and relaunch an influencer campaign or message while knowing the exact reactions from social media audiences, making it possible for fast and adaptive data-based decisions.
Fraud detection
Finally, fraud in influencer marketingOpens a new window has been a major issue in the sector. AI, however, provides marketers with tools that use data to identify which influencers are high risk due to suspicious activity. At last it’s possible to distinguish between influencers with real and fake followings.
So don’t be afraid to start experimenting with the AI power now at your fingertips…to keep them from getting burned.