ListenFirst Launches Influencer & Partner Analytics

ListenFirst Launches Influencer & Partner Analytics

The comprehensive solution provides marketers with the analytics needed to identify and properly measure the performance of influencers on social media.

ListenFirst, the premier enterprise social analytics solution, announced the launch of ListenFirst Influencer & Partner Analytics™, which is used by brands to evaluate the performance of social media influencers and paid partnerships. Influencer Partner Analytics can also be used by Ad Sales teams to prove the value of their social media channels for paid partnerships posts.

ListenFirst Influencer & Partner Analytics™ (IPA) leverages ListenFirst’s unique data taxonomy which uses machine learning to categorize and track the social media footprint of hundreds of thousands of brands, influencers and public figures. That data is further categorized into dedicated universes where entire groups of brands or talent are ranked by social media metrics for a clearer understanding of relative performance.

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IPA impacts core Brand Marketing Strategy by uncovering answers to the most important question marketers must ask when partnering with an influencer or brand, through features designed to address the most common pain points around influencer analytics.

  • Audience Targeting – Through Affinities, marketers can analyze the audience of any influencer by such metrics as top interests, top hashtags, language, geography, age, ethnicity and more to get a clear picture of if the potential partner has an audience aligned with your own.
  • Dynamic Search – Rather than manually sorting through data around hundreds of posts, ListenFirst enables filtering of brand or influencer content by any tag you create or by text search. Additionally filter by sponsored or non-sponsored content, publish time, and content type. This gives marketers quicker access to the most relevant data.
  • Estimated Partnership Value – Traditionally, marketers have struggled over the question of how much a potential influencer collaboration is worth. Through the Estimated Media Value metric, ListenFirst puts a monetary value around paid promotion content, showing both before and after a campaign what that level of engagement would have cost as a CPM ad spend.
  • Customizable Sets of Brands – Track campaign effectiveness across owned, paid, earned, and influencer activity. ListenFirst’s Insight Insights feature allows marketers to manually add as many brands and influencers as desired to sets of brands they create.
  • Performance Evaluation – Benchmark the owned, paid, and earned performance of an influencer campaign against both previous campaigns and against an unlimited amount of competitors at any point mid-campaign. Additionally, through the ability to track sentiment, and specific emotions; brands can see the real-time impact influencer campaigns are having on brand reputation.

The ListenFirst Influencer & Partner Analytics™ approach of focusing on in-depth reporting and audience data is already delivering results for brands, including around ad sales for companies such as AMC Networks Inc.

“AMC Networks has a reputation for high quality shows that break through in popular culture, and social media is where we engage with fans and build true communities around our original programming,” explained Carolyn Hoffman, Director of AMCN Ad Sales Research. “ListenFirst has been an important and valuable partner in quantifying the enormous amount of conversation and attention we get on social media. They provide third-party validation of the significant social activity around shows like The Walking Dead, Better Call Saul, and Love After Lockup. We use their authoritative data to illustrate the value of our social media footprint to a variety of brands and potential partners.”

IPA complements existing Influencer Marketing Solutions. Where these IMS tools enable influencer discovery, influencer management, agreement governance, and campaign measurement, ListenFirst adds critical analytics to the marketing stack.

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