Competition can be fierce in the business world. While creating goods and services that consumers need, love, and keep coming back to is crucial your success, it is also important to keep tabs on the competition — so that you know who the key players within your industry are, what they’re doing in-market, and how customers are responding to them.
For any business, the cost of market research and competitor analysis can be daunting. This is compounded because at face-value, business intelligence gathering and analysis only has an indirect influence on your business’s ability to generate value and revenue.
Given the costs of labour for competitor analysis and the time involved in manually collecting and analysing data, many small businesses decide to skip the tedious process of manually evaluating their competitors altogether. This means that these businesses approach the market with a weakened knowledge of its conditions — a position no company wants to be in when it is time to make important decisions.
The solution to this problem can come in the form of artificial intelligence (AI) tools. Below, we examine how AI tools like otso can be used to evaluate competitors and market conditions, and how this style of analysis can then be used to benefit your business.
There are many processes that AI can use to help a business gauge their competition.
otso offers a powerful natural language machine learning tool, leveraging several methods for analysis and categorisation of data, including Named Entity Recognition, Sentiment Analysis, and Emotion Analysis. So, what do these methods involve, and how can they help businesses to evaluate competition?
Named Entity Recognition works similarly to an intelligent, keyword recognition feature, except it also has the learning capabilities of our bespoke AI modelling behind it. Named Entity Recognition allows otso to learn from contextual linguistic patterns, which can lead to deeper discoveries within your data. On this basis, otso can deliver insights around new products, services, or your competitors, based on how they appear in the context of naturally expressed language.
Sentiment Analysis is the process by which otso evaluates and identifies the tone used within an area of text. This method can help businesses survey general customer sentiment towards their own company, or a competitor. Aspect-specific sentiment analysis also allows for fine-grained distinctions about the directionality of sentiment — who or what has attracted the ire of the public.
Emotion Analysis is similar to Sentiment Analysis, but with the potential for more nuance in its distinctions between observable emotions. Rather than categorising the feelings customers have expressed into positive, negative, or neutral labels, Emotion Analysis breaks the feelings down into a handful of more specific emotions, including; joy, anger, sadness, fear and disgust. These can be useful measures to prompt deeper reflection and analysis of why people have engaged with a product or company in an emotive way.
otso allows businesses to step back from manually analysing gathered data, and let the power of machine learning work for them.