Product development is an intense and expensive endeavor. From researching a market need to conjuring up a product concept to developing the final product. All this while taking into account the competitive landscape, overhead costs et cetera. The traditional way to test out a product is to develop it and send people some samples and ask for feedback. In the digital era, however, social listening has revolutionized product development. Capturing consumer intelligence in real-time allows developers to know the exact needs of the market. Here’s how to make use of social listening for product development.
How is Social Listening suited for the Product Development Process?
A lot of pressure rides on the back of a product manager when it comes to the success or failure of a product. It is therefore crucial for any project manager to look at the entire process from a strategic standpoint. The typical process involves activities like:
- Identifying a problem
- Research, designing, and development
- Marketing and sales
- Measuring post-launch success
There is typically an entire team deployed behind each of these activities. And the success of each department is a key step towards the overall success of the product.
And while most product managers might be losing their night’s sleep thinking of the Herculean task, we are here to suggest social media listening as a solution. Social media information is a gold mine, especially for consumer-facing brands. This is because people love to talk and when many of them are connected over social media, they do talk about products and services they enjoy or the ones they don’t. Tapping into this resource brings you more information from a larger specimen group than any traditional method of research.
Social Listening refines the Product Development Process
Monitoring social data and analyzing it can help at multiple stages of the product development wireframe. Advances in artificial intelligence tools like social listening and sentiment analysis allow brands to map customer preference and how they influence others or are influenced by others.
Social listening also tackles the problem of unclean data. When companies buy consumer data from vendors, there are a few posts that come from the consumer, the rest are manufactured by the agency and robots. This can lead to distorted results. Social listening sources data in real-time right from the consumers themselves.
Deeper Consumer Insights
Traditionally, for research and development, methods like focus group discussions have been used by companies. While these worked well in the past, the major issue is that these processes are costly and time-consuming. When you are conducting a focus group discussion or survey for an existing product, you get answers to the questions you have already thought about and asked. On the other hand, monitoring social data can bring up issues about the product that you might not have thought about asking.
Moreover, with tools such as Auris, the analysis develops and gets accurate over time as more and more historical data accumulates. This isn’t quite possible with physical surveys and focus groups.
You will be amazed at the detail at which consumers discuss their interactions and experiences with brands and products. Consumers do not stop at that. They might like your product but they will point out how bad the delivery or packaging was if any of those things are found lacking. Natural language processing and social listening help marketers deduce the precise pain points of consumers, be it a product feature or post-sales customer support.
For instance, you may see a lot of comments regarding the poor plastic packaging of your product. In such a case you know you need to consider different packing materials. Similarly, if you see people commenting on how they love your product, you can deduce which feature they like the most. Use this information to build on your future advertisements.
With the advances in social listening technology, product development and research get easier. You do not have to go over every comment and mention manually. The data is collected, sorted, analyzed, and presented. Manufacturers simply need to pick up what consumers want and implement that in the design and functionality of their product.