The number of social media users worldwide was rising steadily before 2020. However, the pandemic snowballed the number of social media users causing unprecedented growth. This trend has continued post-pandemic. Presently, there are 4.8 B social media users, and the count continues to rise!
Consequently, social media is a great data source and generates volumes of data in the form of content, comments, customer interactions, etc. This data reveals facts about your audience that can be used for creating customised strategies. Social media marketing strategies can be augmented to reach a wider audience and amplify customer experience through personalisation.
In fact, businesses can curate strategies in a way that generates income from their audience on social media channels, also known as social media monetisation. Social media can be monetised through content creation, awareness/ engagement, and promotion on social channels. This in turn can convert your audience into paying customers. This article will delve into how data analytics can be deployed through different stages of building a social media monetisation framework.
Focus areas for building social media monetisation strategies:
Who is your audience?
One of the foremost steps for creating a social media monetisation strategy is to understand your audience. Analytics provides data such as demographics, location, behaviour, and more. You can create more targeted strategies by segmenting your audience based on these insights.
What is your value proposition?
Make sure that you have a clear and specific value proposition. In other words, what problems are you solving for your customers, what benefits are you offering, how are you different from your competitors, etc.? A clear, concise, and compelling value proposition helps build an effective monetisation strategy. Analytics helps to test and validate your value proposition by measuring how well your products/services resonate with your audience.
Which social media channel to use?
You can monetise any social media channel that your audience prefers to use. Analytics provides all the information about who your audience is, what channels they use, when they use the channel, etc. You can create monetisation strategies aligned with those channels.
What revenue model to use?
You can monetise your content, skill, expertise, etc., through different revenue models such as:
- Subscriptions
- Memberships
- Ads
- Sponsorships
- Commissions
- Merchandising
- And more!
The choice of the revenue model will depend on your niche, audience, goals, and costs. Analytics can help businesses compare and evaluate different revenue models by tracking key metrics such as revenue, profitability, conversion rate, retention rate, etc.
Are you able to connect with your audience?
As you formulate your monetisation strategy, it’s crucial to verify that you are effectively targeting the appropriate audience, conveying the right message, providing valuable offerings, and crafting an elevated customer experience. Analytics plays a pivotal role in quantifying and enhancing various metrics, including but not limited to website traffic, click-through rates, lead generation, upselling, cross-selling, and more.
Furthermore, analytics can be harnessed for monitoring and actively engaging with your digital assets such as social media platforms, email lists, and websites. These analytical tools offer invaluable insights into metrics such as reach, engagement, sentiment analysis, and feedback, allowing for informed decision-making and strategic improvements.
Are you using technology to your advantage?
While you may ask the right questions and have the right answers, you may still find it difficult to be heard through all the noise of social media! This is where technology can help you!
Big data analytics can be used in tandem with Artificial Intelligence (AI) to help create effective social media monetisation strategies. AI can analyse both structured and unstructured data from multiple sources and provide valuable insights to marketers. These insights help in creating personalised posts.
Machine Learning (ML) learns from the existing datasets and makes accurate forecasts. This helps optimise social media monetisation strategies for better outcomes. ML predicts content popularity. This helps you develop an effective social media monetisation strategy.
AI also automates content scheduling based on these predictions to engage the audience. AI can also provide specific information like how much money a customer will spend on a channel. This data helps determine customer behaviour and build strategies to encourage them to spend more.
Unlocking success with social media monetisation strategies
Social media monetisation strategies help a business build an income stream. However, the success of the strategy depends on multiple factors such as:
- Robust and accurate data analytics framework – Data analytics is the cornerstone for building effective social media monetisation strategies. AI-based data analytics helps businesses understand their target audience and build strategies tailored to their needs. Businesses that invest in data analytics are better equipped to achieve their monetisation goals and build long-term relationships with their clients.
- Periodic monitoring and fine-tuning of AI/ML-based analytical models – Keeping a close eye and reviewing your analytical models regularly will help to track the performance of the model. It ensures quality as constant scrutiny highlights the bugs or issues which can then be overcome to deliver the best results.
- Formalise an efficient team structure – A team structure will directly impact the effectiveness of a model which in turn enhances social media monetization opportunities. Hence, it should comprise the right mix of members with specific expertise from various functions that can be utilised for perfecting each process. This can include domain expertise, AI/ML, data management, tool administration, new technologies such as generative AI, etc.
Developing an effective social media monetisation strategy with the help of data analytics requires in-depth analysis and keen foresight. Businesses can greatly benefit by using this medium to their full potential and maximising their income.
