ABC of Evaluating the Success of Your Social Network Analytics Initiatives

Mar 13, 2020

online retailer

Data analytics capabilities of businesses across industries have witnessed a major transformation in recent years. With data volumes growing exponentially, sophisticated algorithms, and social network data analytics tools have been developed and the computational power of data management systems has steadily improved. The convergence of these trends is not only fueling rapid technological advancements and business disruptions but is paving the way for social media platforms to act as a powerful tool for social media reporting and insight generation.

With leading companies across the globe trying to drive outcomes through online channels, social media reporting comes under increasing scrutiny as a platform that can be leveraged further to improve sales and outcomes. However, with the ongoing technological developments, evaluating the success of your social network analytics initiatives can be as easy as analyzing its ABCs. The goal is to determine if the social network analytics initiatives will have the desired impact on your organization as a whole.

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To get started, evaluate the ABCs of your social network analytics initiatives by finding answers to the following questions:

1: Are your social media objectives tied to the business goals you wish to achieve?

To use social media analytics as a tool to drive outcomes, it’s crucial to note that not all social media campaigns, platforms, and metrics play a pivotal role in driving better business outcomes. While some are designed for awareness, others focus more on revenue generations and other critical business aspects. The widespread nature of social media is one of the main reasons why you must factor in the constraints into your measurement strategy and ensure your social media objectives are tied to your business goals.

2: What social media metrics determine success?

To be able to answer this question, it is essential to first determine how you will measure success from a business perspective and to do so, it’s crucial to analyze what you wish to achieve using social network analytics- whether it is to improve brand awareness, source competitive insights, improve visibility, reduce marketing costs, generate leads, or simply analyze social data before you approach it from a business perspective. Once these factors are determined it becomes easier for businesses to identify and gauge the metrics that drive success.

3: Are you well-prepared to measure the success of your social media platforms?

The ability of a company to track and monitor success rates is crucial when it comes to devising a social media measurement strategy. But to be able to answer this question, one must first assess their resources, the technical expertise, and domain knowledge along with the current state of internal and external collaborations. Many companies lack the expertise and well-trained social network analytics professionals who can analyze and gauge social data sets. This can be attributed to the lack of detailed social network data analytics roadmap.

4: Did the insights obtained from social network analytics campaigns help drive outcomes?

Monitoring brand health on an ongoing basis can help you track and measure customer behavior and factors impacting them. This is of utmost importance from a business viewpoint and is also one the most common use case across industries. Leveraging insights obtained from social network data analytics tools can help your brand drive outcomes by better understanding the opportunities and threats in the industry. Besides the other benefits offered by web and social network data analytics what measures the success of your initiatives is the answer to this question- have the insights helped you achieve your goals? Applying social insights to your brand strategy can help you mitigate risks, prevent a crisis, and uncover new value-driving opportunities.

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Our social network analytics solutions portfolio includes:

  • Sentiment Analysis
  • Topic Modeling
  • User Reviews and Rating Analysis
  • Opinion Mining
  • Text Mining
  • Word Cloud
  • Offer Recommendations
  • Influencer Analysis
  • Lead Mining

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