Using Data Analytics to Drive Influencer Marketing Outcomes

With an ever increasing number of consumers tethered to their phones for work, social, and everything in between, social media has become more targeted and more ubiquitous without signs of slowing. It is the playground of highly effective influencers, who with one carefully crafted message can introduce a brand to millions of activated, engaged followers. As social media use accelerated during the pandemic, it is no surprise that influencer marketing spend also increased dramatically, reaching $13.8 billion globally in 2021. Ensuring dollars spent lead to sales is underscored by intelligent data analytics solutions, adept at pinpointing the right influencer, with the right audience for the optimum result.

In the West, influencers recommend products through videos or posts and provide discount codes as well as URL links to relevant brand websites. In China, influencers often endorse and sell products directly on their own WeChat stores. In Africa 74% of consumers rely on social media to inform their purchasing decisions. Influencers world-wide wield significant power to sway shoppers and elevate brand awareness. The challenge for retailers is to keep up with changing consumer demands and preferences and zero in on the influencers who can mobilize them.

More than half of brands working with influencers have eCommerce stores. To drive traffic to the store, retailers must employ data analytics to enable a real competitive advantage in influencer marketing.

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Tracking Influencer activity to create an attribution methodology

Companies are advised to track influencers’ (and their followers’) activities to maximize success. Devising a logical system for promotional codes, which can be used at the basket stage, and making sure influencers use Google Tag Manager (GTM) tags in the links posted on the relevant social posts on Instagram, Facebook, Tik Tok, YouTube, etc, will illustrate the user journey – from post to purchase.

Brand awareness metrics such as impressions, clicks, and engagements (likes, shares, etc.) are useful indicators, but at the end of the day, revenue is what counts – and the ability to demonstrate conversions is key. A good rule of thumb is to create an influencer-friendly attribution methodology that credits a purchase to a given influencer if one of the following criteria is met:

1. The promotional code is used at the basket stage of the purchase regardless of the source of traffic
2. Any customer session arising from an influencer link (i.e., has an influencer GTM tag) forms part of the customer journey, regardless of whether it’s last click or first click

Having strict criteria in place makes it easier for retailers to examine the entire picture from the sidelines and adjust as needed. The data collected can help a brand reach a number of valuable conclusions – from ascertaining influencer engagement rates, assessing the level of authentic and relevant content and determining whether an influencer’s audience fits the brand’s target demographic. Ultimately data analytics reveal which influencers are more suitable and by extension, which are most impactful.

Displaying all Influencer Activity on a Comprehensive Dashboard

Tracking activity and creating influencer attribution logic are only the tip of the iceberg.

A good data analytics solution allows operators to measure how many new customers are acquired by a given influencer, the cost of each customer, customer lifetime value (revenue and gross profit), cost per order etc.

Ideally, all influencer-related information with regard to promoting a brand should be accessible on one comprehensive, interactive dashboard. This dashboard should be dynamic – changing daily to account for the continual ebb and flow of social media activity, enabling brands to make strategic decisions regarding their influencer marketing strategies.

A comprehensive, well-oiled data analytics platform can distinguish between an influencer producing high yields and those missing the mark, prompting a retailer to bolster relationships with the most reliable performers and reducing or removing spend on those deemed less profitable. Data analytics can help retailers determine whether low returns on influencer spend is due to suboptimal messaging or simply a misalignment in customer audiences between the influencer and the brand. Equally, it can identify the type of influencer most useful to a brand in order to inform future collaborations.

Sometimes an influencer campaign may deviate from purchases and be directed at a different call to action such as newsletter sign ups. As long as the cost per sign up is tracked and the conversion rate of newsletter audience to paying customers is known, a derived cost of acquisition (CAC) can be obtained and the profitability of the campaign properly assessed.

Experimentation of messaging is key to understand what lands well with consumers, and  following the user pathway using appropriate GTM tags or promotional codes, will affirm what works and expose dead ends.

The future symbiosis of data analytics and influencer marketing

Influencer marketing is poised to replace commercials and other forms of advertising in the coming years as it has the ability to reach different audiences across multiple platforms in a more authentic and incisive way than ever before.

In an effort to ride this wave, retailers must use all of the tools in their arsenal to create an edge. Data analytics provides retailers with increased visibility as well as a deeper understanding of the influencer marketing landscape and allows them to actively monitor social media consumer behavior as it unfolds in real-time. The marriage between data analytics and influencer marketing is one destined to ensure the right consumers interact with the right brands, establishing efficient and beneficial transactions for all involved.

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