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Sentiment Analysis - Build It Yourself or Use an API?

Sentiment analysis technology comprises many machine learning techniques that come together to automatically mine emotion from data so you can understand audience opinions. It can be used in a variety of fields including employee satisfaction, understanding customer behavior, or knowing the level of market reception of a new venture.

Organizations know the impact of sentiment analysis insights on business performance. So the question is do you build a sentiment analysis tool from scratch or is it better to employ a ready-made sentiment analysis platform available in the market.

Building A Sentiment Analysis Tool By Yourself

If you have the time and resources, you can choose to leverage machine learning-driven sentiment analysis technology and build your own emotion mining tool. But if you want to dive straight away into supercharging your marketing strategies through in-depth customer experience analysis or invigorate your brand experience and save time and costs, it is smart to choose from the many sentiment analysis tools that are available to purchase.

However, if you do intend to build a sentiment analysis API of your own, there are certain pros and cons that you need to keep in mind. Let’s consider some of them.

Pros:

  • You know exactly what your requirements are and therefore the API can be built exactly per your needs.
  • There are no third-party expenses in terms of subscription fees or technical support
  • You can keep upgrading the model by training and enriching it by adding new metadata

Cons:

  • Building an API from scratch can be a time-consuming endeavor
  • A sentiment analysis technology platform can also be a very expensive task
  • It is crucial to have experienced data scientists on board
  • The tool must be able to analyze sentiment in BOTH text and videos
  • The API must have native natural language processing (NLP) ability to avoid machine translations to analyze multiple languages as it can lead to inefficiency.
  • It must have a robust named entity recognition (NER) capability, which is a feat tough to accomplish in a short time.

What Should You Consider When Choosing A Sentiment Analysis Tool?

Should you choose to use a sentiment analysis platform from a service provider, there are certain top criteria that you should consider.

1. Customizable

There are many high-performance sentiment analysis tools on the market. What you need to do is choose one that is exactly customized to your requirements. Not having a machine learning model that is built to fit your custom needs can give you inaccurate insights, which ultimately defeats the purpose of having the platform in the first place.

2. Speed & Scalability

The reason companies choose a sentiment analysis API is because it allows them a quick analysis of large volumes of data for voice of the customer analysis. Therefore, speed and agility are of important consideration. So is scalability, for you should choose a tool that can scale with you as your business and requirements grow.

3. Real-time analysis

Sentiment analysis technology can help you analyze customer opinions in real-time. You can automate social media video content analysis for TikTok, YouTube, or any other platform, and at the same time analyze customer support tickets based on aspects like topics or issues. You can also analyze all the insights on a customer experience dashboard for tangible action-based results you can use in a timely manner for your branding and marketing campaigns.

4. Minimal coding

The very reason you are choosing to purchase a subscription-based sentiment analysis model instead of developing one from scratch yourself is so you don’t have to go through the nitty-gritty of coding and data architecture. Whether it is to add new metadata or customize topics and themes in your aspect model, the sentiment analysis API you choose should require minimal to no coding. This is also strategically helpful as you won’t be dependent on a third-party vendor for any underlying technology support.

5. Speed to market

Wasting thousands of hours on analyzing social media or customer complaints can be detrimental if you are in a space where speed to market is a necessity to manage a competitive environment This holds especially true if you are a marketing agency. A read-to-use sentiment analysis API extracts consumer insights from all relevant data sources at speed so you don’t lag in your response to market demands.

6. Flexible environment

It’s a great advantage if the sentiment analysis technology you use is built for virtual infrastructure but also for an on-premise installation. This gives you the flexibility to choose between having a platform behind your firewall for data security and one that is friendly to a Cloud environment, which is necessary if you have data spread across scattered data warehouses.

Conclusion

Sorting humongous amounts of data such as surveys, social media conversations, product reviews, or even news articles can take hundreds of man-hours. Not to mention, be inefficient due to human errors and biases because tagging text with sentiment is highly subjective as it can be influenced by personal experiences. Sentiment analysis technology powered customer insights model automates this process by analyzing such big data efficiently and cost-effectively from a neutral point of view and exactly as it is trained.

Read about the benefits of a sentiment analysis API.

Therefore, it’s a no-brainer that an API is your best bet for high-precision business intelligence. If you are able to choose an API that fulfills all your criteria, you do not have to go through the hassle of developing your own sentiment analysis tool. Thus, benefiting from cost-efficiency and savings on time and human resources.

Repustate’s sentiment analysis API gives you critical business insights from customer/user and employee data quickly and accurately. It scans social media platforms like TikTok, YouTube, Instagram, and others, surveys, online news and article, customer support emails and tickets, and various other sentiment analysis data sources seamlessly, analyzing both text and video content and offering capabilities like search inside video.

Highly customizable to fit your business needs and available in 23 different languages, each supported by its own native speech tagger, Repustte’s sentiment analysis technology is available as a standalone model as well as a platform with its own intelligent dashboard.