Data analytics in instagram
- 2. INTRODUCTION – Instagram is an American photo and video sharing social networking service. – It was created by Kevin Systrom and Mike Krieger and was launched in 2010. – Today, Instagram is owned by Facebook and there are around 800 million users. – People interact through posting pictures, liking posts, commenting, using hastags which creates enormous data. – This data through artificial intelligence algorithms can provide business insights.
- 3. HOW DOES INSTAGRAM USE BIG DATA? – Explore page and Search Function: With the help of hastags and trending information, users are able to find a particular activity, event, and places. The search tools allows Instagram users to doscover things of interest among million uploaded content. – Target Advertising: Instagram collects customer insights by extracting data. By assessing search preferences and engagement insights, Instagram can sell advertising to companies who want to target the particular customer profile who might be interested in receiving a marketed message.
- 4. – Enhance User Experience: To ensure that users find value in the platform, it is important for Instagram to show users what they like. As amount of content grows, finding content that each user will find relevant becomes challenging. So, Instagram uses machine learning algorithms that will help in sorting information according to the users likes and shares. With time the user will have a personalised feed. – Eliminating Spam: Instagram detects fake messages and gets rid of them from accounts. The technology works on nine languages such as English, Chinese, Arabic and Russian. Spam detection is possible through Al and Deep text that read texts and determines its context and relevance.
- 5. – Offensive and Inappropriate Content: Studies show that 42% of bullying instances happen on Instagram. Instagram to deal with this problem, were the first to use machine learning which automatically removes offensive posts, whereas Facebook and Twitter rely on users to report abusive language. If the algorithm finds something offensive, it is immediately removed. There is still the risk of misclassifying something as offensive when it’s not or that offensive comments will make it through. – Studying Human Condition: When it comes to Instagram, it makes your audience feel like a part of a global community. Machine learning helps in extracting insights when studying humans and social, economic and cultural factors around the world. It means that you need to work with loads of data and interpret them correctly to take the right actionable insights to improve your content and posts targeted to your audience.
- 6. INSTAGRAM ANALYTICS TOOLS – Instagram is a great platform to market and influence people. There are Instagram analytics tools that can help with influencer strategy. – Instagram Insight is a built-in analytics that is provided by Instagram. From within the app you can learn more about your audience demographics, when they’re online, what they’re clicking on, and what they like. – Sprout Social: In addition to Instagram scheduling and publishing features, as well as supporting engagement through real-time monitoring, Sprout enables quick analyses at both the post and profile level. You can examine hashtag trends to inform future content or evaluating team performance to optimize operations, you can do it at scale by measuring everything from follower growth to engagement across different products, brands or locations simultaneously.
- 7. – Phlanx: Phlanx’s engagement calculator analyzes the engagement rate of any given Instagram account. Although the tool is marketed as being for influencers, any personal or business account can be plugged in. Engagement rate is calculated by dividing the number of likes and comments a post receives versus an account’s follower count. – TapInfluence: TapInfluence’s platform analyzes a database of over 50,000 influencers to help brands find the right fit for their influencer campaigns. Businesses can search by industry or specific tags based on what they’re looking for. – Similarily there are many other tools like Curalate, Union Metrics, Bitly, Keyhole, Iconosquare etc.
- 8. CONCLUSION – Big data, AI, and machine learning play a crucial role in social media marketing, including Instagram. They introduced new standards of user experience so that brands can create content that grabs consumer attention.
- 9. THANK YOU