According to McKinsey Global Institute, retailers using big data to its full potential could increase their operating margins by over 60%. That said, companies have been searching for a solution to three major issues:
There’s a need for a solution, especially for small and medium-sized businesses and personal users. These users require economically-efficient infrastructure for sentiment data and may want to analyze and apply crowd wisdom to make proper decisions.
Now, these users do not have to worry about whether they could afford to use big data for sentiment analysis.
Senno is a decentralized, blockchain-based sentiment analysis platform using distributed hardware. Additionally, it has an open software development kit (SDK). The platform allows third parties to integrate crowd wisdom, as well as data conclusion tools into their own platforms. For example, with this platform, digital assistants, such as Alexa, would be able to answer a variety of new questions with high precision. This is all based on real-time user-generated content such as how the crowd feels towards a subject or product.
There are several benefits when using this platform. The blockchain-based sentiment analysis platform could identify both opportunities and threats, and users could respond almost instantaneously. They could also monitor the impact of changes made to marketing campaigns, products and performance within a specific geographic location or time frame.
Take this as an example use case:
If there is an increasing number of mentions in a company, it indicates that something is going on. That in mind, if the company is on Senno’s platform, employees may want to look at these indications and analyze the meaning and strength.
Senno’s engineers and developers have come up with a ground-breaking solution, delivering precise, real-time, in-depth and extensive analysis of sentiment data to all the members of its community. Consequently, there is full-transparency. Moreover, Senno is more cost-effective than traditional solutions and has higher accuracy as well.