Commentary

Turn Influencers Into Brand Advocates

Social media brand advocates can have a powerful influence on the purchase decisions of others, and predictive analytics software can provide the necessary data to help companies locate the right influencers, and craft engaging content that turns them into brand advocates.

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According to a new report by SoftwareAdvice, Dmitri Williams, founder of social analytics company Ninja Metrics, estimates that just 5 to 10% of social media users are responsible for 60 to 80% of influence. As such, businesses turn influencers into “brand advocates” by providing them with personalized experiences that motivate them to share positive brand impressions with others.

However, says the report, the sheer volume, velocity, and variety of unstructured data available on social media channels makes this a daunting process. Companies must locate quality influencers and then engage them quickly and meaningfully. Predictive analytics is increasingly being used in social media marketing to address these challenges.

By uncovering patterns and associations in unstructured social media data, predictive analytics software provides nuanced insight into users’ behavior, attitudes and preferences to forecast how users are likely to behave in the future. Marketers then act on these insights to provide the right content at the right time to the right audience, via the advocates best fit to influence them.

SoftwareAdvice asked marketers to share their experiences and challenges with social media advocates; then surveyed advocates to learn more about their preferences. and how predictive analytics software can help overcome the challenges of advocacy-based social media marketing and create content that resonates.

The study investigates how predictive analytics can be used to identify quality

social media influencers, connect with them, and generate the type of content they are most likely to share as brand advocates. Key findings show that:

  • 46% of marketers surveyed say they struggle to identify and communicate with social media influencers
  • 46% of marketers say they struggle to predict the preferences and behavior of social media influencers
  • Although they struggle making predictions about social media behavior, 68% of marketers aren’t yet taking advantage of predictive analytics software.
  • 27% of marketers feel challenged by advocates’ privacy concerns, but 75% of advocates say they are comfortable being approached by brands.
  • 27% of Advocates prefer to share brand posts on entertaining stories, products they recently researched (23%), and contests or giveaways (22%).

To get background on how predictive analytics software helps companies succeed in the social media space, marketers chose, from a list provided, the top challenges faced working with social media advocates.

Marketers’ Top Challenges Working With Brand Advocates

Challenge

% of Respondents

Competing with other brands

62%

Identifying advocates

46

Communicating with advocates

46

Predicting behavior

46

Privacy concerns

27

Source: SocialAdvice, July 2015

62% of marketers say that competing with other brands for the attention of social media advocates is a top challenge. Marketers struggle with identifying influencers who make the best advocates (46%), and communicating with advocates (also 46%). Though marketers recognize the competitive advantage of finding people who both have purchase intent and are inclined to speak for their brand, 46% say they struggle to predict the behavior of influencers and advocates.

The business case for using predictive analytics software seems clear. However, the survey reveals that many marketers aren’t using it yet for the purpose of advocacy-based social media marketing.

Current Social Media Marketing Strategies

Strategy

% of Respondent

Posting advertisements

70

Social listening/monitoring

68

Posting current events

65

Offering incentives

59

Sentiment analysis

35

Predictive analysis

32

Text mining

30

Source: SocialAdvice, July 2015

The majority still rely on traditional social media marketing tactics, such as posting advertisements, and posting about current events. 68% are listening in and monitoring what’s being said on social media channels, while 59% are offering incentives to nurture advocates. However, only 32% of marketers surveyed currently use predictive analytics as part of their social media strategy.

When the advocates in the sample, says the report, are asked how they would feel if a brand messaged them directly through social media, a combined majority say they are “comfortable” with the practice. 43% say they would be “extremely comfortable,” while only 5% would be “somewhat uncomfortable”—and none of the advocates we surveyed say they would be “extremely uncomfortable” being messaged by a brand.

Advocates’ Comfort Level With Being Messaged by Brands

Comfort Level

% of Respondents

Extremely comfortable

43%

Somewhat comfortable

32

Neither

19

Somewhat uncomfortable

5

Source: SocialAdvice, July 2015

While marketers are right to be cognizant of how they approach anyone on social media, this needn’t slow their proactivity, says the report. However, they should be sure that content and incentives are palatable and relevant.

Whatever the social strategy, and particularly when using predictive tools for social media, a “human element” still needs to be a part of the package, says the report.

Technology is great, but not at the expense of human interpretation that’s needed for social channels, above all others. A blend of a sharp social marketing team combined with best-in-class tools to understand the content and the types of people they are engaging with.

Once a company has identified quality influencers and target audiences, the next step is generating user-centric content. This increases the likelihood content will be shared. When people are interested in something, they are more likely to share it and present it in an engaging way, so the stuey asked advocates what types of brand content they’d be most likely to share on social media channels

Types of Posts Advocates Are Most Likely to Share

Post Type

% of Respondents

Entertaining or funny story

27%

Produce recently researched

23

Contest or giveaway

22

Human interest story

18

Relevant to recent share

8

Re-share friend’s post

3

Source: SocialAdvice, July 2015

The advocates responding say they are most likely to share posts with entertaining or funny stories (27%), or about products they have recently researched online (23%). Information about contests and giveaways (22%) and human interest stories (18%) are also favored. Advocates are least likely to re-share a friend’s post about a brand (3%), or to share a brand’s post that is relevant to something they recently shared about themselves (8%).

Advocacy-based social media marketing can be an extremely effective way for companies to reach larger and/or more targeted audiences, concludes the report. However, the amount of information available on social media channels can be overwhelming to work with and interpret without the right tools. Predictive analytics software can help companies improve their advocacy-based social media marketing by:

  • Quickly digesting and sorting copious amounts of social media data
  • Offering a real-time analysis of information found on social media channels
  • Identifying those influencers most likely to boost engagement
  • Identifying the target audiences most likely to respond to certain content
  • Forecasting engagement and conversion metrics

When using predictive analytics software, marketers can not only be more confident that they are identifying the right influencers to use as advocates, but also that the content they are generating is targeted at the right audience for the message. Getting this key information in real time helps companies remain competitive on social channels.

N.B. Results are representative of the survey sample, says the report, not necessarily the population as a whole. Expert commentary solely represents the views of the individual. Chart values are rounded to the nearest whole number.

For additional information from SoftwareAdvice, please visit here.

 

 

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