Merriam Webster (2018) defines influence as ‘the power to cause changes without directly forcing them to happen’. An influencer is, therefore, a person or that affects the opinions and actions of others in an important way. In recent years, Influencer Marketing has become one of the most effective worth of mouth (WOM) strategies (Weiss 2014). To illustrate the strength of WOM, Nielsen’s 2012 ‘Global Survey of Trust in Advertising’ revealed that 92% of consumers worldwide said that they trusted word-of-mouth recommendations from their trusted influential peers. This vastly exceeded any other forms of marketing, such as advertising or branded communications (Liu et al. 2015).

The brand’s profound knowledge and the establishment of clear communications objectives & strategies are fundamental in the choice of an influencer (Booth & Matic 2011). Based on this, an influencer can be evaluated with traditional or newer (more technological) approaches (Liu et al. 2015). Academic and practitioner research unveiled the following methodology for identifying an effective influencer

1. Resonance

Resonance is the quality of the influencer to arouse her follower’s interest and desire for consumption. (Li et al 2011)

2. Activity

Influencer’s activity represents how active is the influencer in sharing information through her social media channels and/or blog site. The impact of Activity relies on the relevance and quality of the content.

3. Relevance

Relevance in Influencer Marketing refers the alignment between the Influencer and the brand’s image and core values. An influencer will not necessarily generate conversions if there is a mismatch between her and the brand she represents.

4. Engagement

The level of engagement is measured by the intensity of ‘responses, comments and shares’ from the audience. This parameter also refers to the level of engagement from the influencer towards her followers. Engagement increases the levels of trust, and trust increases WOM’s effectiveness (Nielsen’s 2012 ‘Global Survey of Trust in Advertising’)

5. Reach

“Influencers generally do have many direct ‘friends’ and ‘followers,’ but what makes them truly valuable is the number and relevance of their extended or indirect connections” (Hall, 2010 cited by Booth & Matic 2011).

6. Frequency

Frequency indicates the influencer’s ‘multiple exposures’ of the same content. Hamann 2018, asserts that higher levels of frequency generate high levels of returned visitors and loyalty.

7. Authenticity

Influencers with a unique personality, sharing genuine personal stories with less sponsored content appear to be more authentic (Hamann 2018).

8. Maintenance

Corporations are not only interested in whether an influencer is currently emerging or holding influence, but also in whether the influencer will maintain her influential power into the future (Lui et al. 2015).

9. Influencer Index

Booth & Matic (2007) developed the Influencer Index, a score that ranks the influencer based on the following variables:

• Viewers per month (vpm). The number of visits to the blog per month
• Linkages. The popularity of blog post links inbound and outbound
• Post frequency. The volume of posts per given time
• Media citation score. Volume and level of media that cites blogger/ influencer
• Industry score. Number of industry guru points based on industry events such as keynotes, bylines and panel participation
• Social aggregator rate. Level of social media participation (e.g. Twitter, LinkedIn, other bloggers/blog communities and other social media platforms)
• Engagement index. Reader response and the number of comments
• Subject/topic-related posts. Volume and immediacy of subject/topic-related posts
• Qualitative subject/topic-related posts. A qualitative review of subject/topic-related posts.

10. Influencer Platform Automation

Automated influencer platforms like Ghostlamp and Heyinfluencers are offering match-making services to companies and influencers. All the processes from finding the influencer, contracting and payment are fully automated.

11. New approach: algorithms

Digital Marketing Academics have developed complex and more accurate algorithms:

• Product Review Domain Aware (PRDA). Evaluates influencers in three dimensions: trust, review domain and time factor (Liu et al 2015). The results classify influencers into three categories: emerging, holding and vanishing influencers
• Marketing Influential Value (MIV). Developed by Li et al (2011), this algorithm combined the network-based, the content-based and activeness-based values to determine the MIV of a blog site.

 

The ‘‘uncertainty’’ problem (Li et al 2011) of resources being wasted on efficient marketing is a growing concern in Digital Marketing. Multiple methodologies of measuring influence and conversion have emerged in the last decade. Influencer Marketing has become one of the most effective WOM marketing strategies (Nielsen 2012). However, there are still a lot of myths around this Marketing technique (Forbes 2018). Some of the myths include the belief that an influencer must be a celebrity and that the Return on Investment is difficult to measure. Studies show that micro-influencers (10 000 to 100 000 followers) can present a higher impact (Ake 2017).

Further, the identification of influencers within complex social networks requires complex data analysis. New tools (like the automated algorithms) support marketers and advertisers to perform a higher cost-effective promotion of their products and services. These tools are taking over the traditional ‘popular author’ approach. Since the most important factor remains the quality of the relationship between the firm and the consumer (Booth & Matic 2011), there is a concern whether the algorithms and modern automation processes can preserve this relationship quality.

 

References

Ake, C (2017) ‘How To Choose The Right Micro-Influencer For Your Brand’ Forbes Community Voice. 2 August 2017 [Online] https://www.forbes.com/sites/forbesagencycouncil/2017/08/02/how-to-choose-the-right-micro-influencer-for-your-brand/#3c9990307885 [Accessed 30 April 2018]

Booth, N. & Matic, J (2011) Mapping and leveraging influencers in social media to shape corporate brand perceptions. Corporate Communications: An International Journal, vol. 16, no. 3, pp.184-191.

Forbes (2018) ‘Five Influencer marketing Myths That Could Ruin Your Campaign’. Forbes Community Voice, Business. 1st May 2018 [Online] https://www.forbes.com/sites/forbesagencycouncil/2018/05/01/five-influencer-marketing-myths-that-could-ruin-your-campaign/#379c739f6b34 [Accessed 1st May 2018]

Ghostlamp (2018) ‘Does influencer marketing work for your brand?’ [Online] https://ghostlamp.com/getstarted [Accessed 30 April 2018]

Hamann, H (2018) ‘5 Tips for Finding the Right Social Influencers for Your Brand’ Convince&Convert, Digital Marketing [Online] http://www.convinceandconvert.com/digital-marketing/5-tips-for-finding-the-right-social-influencers-for-your-brand/ [Accessed 30 April 2018]

HeyInfluencers (2018) ‘Build your influencer outreach list’ [Online] https://thisishey.com [Accessed 30 April 2018]

Li, Y. et al. (2011) Discovering influencers for marketing in the blogosphere. Information Sciences, 181(23), pp.5143-5157.

Liu, S. et al. (2015) Identifying effective influencers based on trust for electronic word-of-mouth marketing: A domain-aware approach. Information Sciences, 306, pp.34-52.

Merriam Webster (2018) ‘Influence’ Merriam Webster Dictionary. [Online] https://www.merriam-webster.com/dictionary/influence [Accessed 30 April 2018]

Nielsen (2012) ‘Global Trust in Advertising and Brand Messages’. Reletur Files. 10 April 2012. [Online]  https://retelur.files.wordpress.com/2007/10/global-trust-in-advertising-2012.pdf [Accessed 1st may 2018]