A media agency used engagement driven proprietary index to segment influencers on social platforms.
The media agency had engaged with an ecommerce platform that is into kids apparel. They were planning to launch a campaign across major Tier II cities in India and looking to identify and engage with the right set of influencers. They wanted to develop a proprietary index based on engagement of fans on content relevant to their line of business, understand their differentiation and identify micro influencers. The index should also help them measure engagement on sponsored posts.
Doing small things in a great way
The agency was able to identify influencers and segment them based on the fan engagement, content focus, geography and other relevant metrics.
- Removed bias in influencer selection based on proprietary Influence Index
- Optimize costs of influencer sign-up and maximise return on investment (RoI)
- Segmented influencers as micro, mini, regional and national
The analysis enabled the media agency to identify the right set of influencers to maximize the reach among fans, generate engagement and awareness.
Multiple objective. Unstructured scope.
The media agency had formulated the campaign with marketing through influencers as the central theme. There were multiple challenges with this approach. They needed to identify the right platforms and forums on which the target customer base was active. The vernacular mode of communication across platforms was not helping them in making an objective decision. Besides, the motivation of users on each of these platforms was heterogenous.
One of the major challenges was to identify influencers across platforms – and compare them on a common scale. The primary focus of the agency was to reach the target audience through these influencers. We proposed a data driven proprietary index design to measure influence with a set of metrics that was easy to capture – despite the heterogeneity of the platform and diversity of fan base.
A proprietary influence index
The proprietary Influence Index is based on machine learning algorithm, utilizing natural language processing that measures the degree of influence.
With Influence Index, the media agency was able to :
a. Use the index and segment influencers into Micro, Mini, Regional and National
b. Index based monitoring of week on week variation in the engagement level and influence score
c. Measure of how well each category of influencers performed on campaign posts and sponsored content
The Influence Index based monitoring enabled the media agency to identify, monitor the engagement and performance of each segment of influencers at a monthly level and align them to campaign objectives.