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Instagram Scraping

Data can primarily be of three different formats- structured, semi structured and unstructured. Structured data refers to tabular data that we see on Google sheets, Excel files and tables. Semi structured data can be lists, flow diagrams, charts, JSON files, XML data, and more. Unstructured data refers to everything else– all data formats that do not follow a pattern, that can be learnt and deciphered by a machine.  

Unstructured Data and Social Media

One of the biggest sources of unstructured data today is data scraped from different social media websites. These could be textual data from Facebook or Reddit, Images from Instagram or Pinterest, job reviews and posts from Linkedin or Glassdoor, or even videos and audio recordings from tens of different platforms. 

While working with unstructured data is difficult, NLP or Natural Language Processing has come a long way in the last decade. This has enabled businesses as well as researchers to use machines on social media content to extract information. Alternative data sources like Social Media allow companies to directly consume and build on raw data generated by customers on the ground.

Social Media Data can Help you Achieve your Business Goals

Social Media Data, when harvested correctly, can turn into a goldmine for companies who want to understand their user base better and use their feedback to work on new features and products. While it may seem like a challenging road to take, leaving the data on the table is not an option. Hence, let’s look at the 5 step approach that you can take to use social media data optimally and boost your business.

  1. Finding the platforms most relevant to your business: Tapping into all social media platforms would only increase the noise and remove your focus from the main task. Instead you need to shortlist the platforms most likely to contain data relevant to you. If you create consumer products, instagram reels and posts may be a good source of information, if you provide professional services, Linkedin may be more up your sleeve, for those wanting to take a dig at marketing patterns for B2C products, Facebook may work wonders, and so on.
  2. Set the Goal: Unless you set a target and work towards it, you will just be sitting on a mountain of data scraped from social media without knowing what to do with it. Instead of deciding what you need answers to, you can come up with problem statements like, why some of your products are more popular than others, what type of products or services you should work on next, why you have a lesser number of return customers, etc. Only when you have your question ready, can you go on to find the data that has the answers hidden.
  3. Decide on data scraping tools: Once you have finalized the problem statement and decided on which sources you will need to fetch data from, you have to decide on the tools you will be using to get your job done. You can choose between DIY coding, screen grabbing semi automated software solutions and DaaS offerings. However, if you need to get things done quickly and “on-demand”, without having to worry about the technical and legal aspects of web scraping, it’s best to go for a DaaS provider like PromptCloud.
  4. Keep track of trends and changes: A new trend comes out and everyone wants a piece of the pie. In order to ensure that you don’t miss out, once you have the live data feed, you will need to monitor trends and changes every hour or day, or week. If you review the data more frequently, you will be able to act faster and make the most of opportunities. One example of this would be businesses who consumed data on Covid pandemic first and realized the impact of it.  These companies most likely changed the course of their businesses and saved them in time. Changing course here could mean taking their business online or moving from a restaurant business to a cloud kitchen setup. You would also need to keep track of changes and trends in your competitors’ social media engagement.
  5. Customer Sentiment Analysis: The most common usage of social media data is for analyzing comments and remarks left by customers to find out where companies are going right and where their efforts are leaving much to be desired. If you have a B2C business, you are likely to find a horde of data that you can give your product team to work on, once you have consumed the data and performed a Natural Language Processing based sentiment analysis on it.

Influencers and Instagram Scraping

In recent years, Instagram has grown to the biggest platform for influencers. This is where famous individuals as well as fresh faces advertise products and services in a completely new fashion. Their posts contain data in many forms– videos, images as well as textual content added as description. 

These content provide insights into the latest trends in the market, top products that are being advertised currently, the top influencers whom brands are hiring and more. With Instagram scraping, you would not only have content and data but also information regarding which individuals you could contact in case you want to promote your own products or services.

Given that instagram or any other social media website contains data that is not well-formatted, scraping it, cleaning it and then consuming it is a complicated process. Unless the service provider that you are using has prior experience with social media data, you may end up with unclean data which in turn would affect all the insights that you extract and the data backed decisions that you make. Instagram scaping brings wide opportunities for influencers these days.

Our team at PromptCloud has helped customers:

  1. Build different products on top of raw social media data.
  2. Use social media data to improve customer experience based on feedback and comments. 
  3. Get a better understanding of their competitors through their social media presence and accordingly make business decisions.

As new alternative sources of data are added, they may be difficult to consume but ones who adapt quickly will end up having an advantage in the long run.

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