Deciding the optimal sample size, data collection, data analysis, before coming up with a final result is an iterative process which can be exhausting. But what if the enterprise doesn’t have enough resources but still wants to predict the impact of a message on the audience? The question then that begs asking: Is there a way to predict the success of a message without conducting any surveys or without having to go through the iterative market research process? 

The answer to the million-dollar question is a resounding “YES”! Thanks to technology, there is a product that makes use of artificial intelligence, machine learning, and deep natural language, to study the impact of a message on the users without the need to conduct primary market research. The message development research product can predict message effectiveness with 80% accuracy by using data from past studies and has been trained on millions of past research studies.

Some research products now specialize in using advanced algorithms and high-quality inputs that can provide better results, in less time, that too in cost-effective prices.

There are many reasons for an enterprise to choose to use such a product instead of lining up for a traditional market research study. Some of these are:

1. Lack of time
   Enterprises do not always have the required time to spend on conducting detailed market research. This might result in haphazard surveys, which may or may not provide correct predictions. Newer products that utilize AI and machine learning can help enterprises can cut down the time spent on surveys. This will lead to faster market releases and additional opportunities to grow.
2. Not Enough Budget 
   Market surveys are expensive. Even though there are websites that offer free sample surveys, to get a detailed prediction, a business needs to have a budget for it. What if the brand can get better and accurate predictions for just one-third of the price paid for market surveys?
3. Get To-the-Point Answers
   A detailed market research study does not yield one-page results. The study will be a thick file of data that has to be read, understood, and analyzed to get down to the crux of the survey. Wouldn’t it be easy for enterprises if the research product could simply gave a list of suggestions from the analysis?
4. Not Enough Customers for Research
   Inadequate sample sizes can mess up any survey. Whether it is choosing a wrong sample size or a wrong target audience for the survey, the end result could be faulty. Why worry about not finding enough users to for a survey when there is no need? Message predictor relies on machine learning algorithms rather than users to conduct predictive analysis. 
5. Customization of the Message Predictor
   Message development research cannot follow the same pattern or formula for every enterprise. Most survey forms are based on standard templates, which are given minor tweaks, if required. But the message predictor can be customized based on the industry and the category of product/ service. The algorithms are trained to identify and predict responses for specific questions instead of general questions.