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Product management: Using social media for requirements gathering

In this tip, requirements expert Scott Sehlhorst explores the many uses of social media and social networks for improving product management.

Social media is the most recent "next new thing" to cross the chasm into mainstream product management. Product management is, in a nutshell, the discipline of understanding which problems your customers are willing to pay to solve, and driving the creation of products that solve them. Social media tools allow you to connect with people – actively and passively; listening, conversing and collaborating. How do you use social media to improve the requirements gathering process? 

Gaining market insights

Getting insights into your market is an open-ended exploration process, and you can accelerate this knowledge collection process by connecting with the people that already have an understanding of the space. The fastest way to develop an understanding of your target market is to find people who already understand your market and learn from them. You can ask your network for pointers to people with domain expertise in a particular market. The two social networks with the most activity in the United States are Facebook and Twitter. Which one should you use? A great distinction I heard once is that Facebook is best suited to reconnecting with people you used to know, and Twitter is best suited for making connections with people you don't know yet. Google plus is emerging as a new social network – with 40 million users in November 2011, it is 5% of the size of Facebook and less than 1/5th the number of people using Twitter. Google plus doesn't know who it wants to be yet – it may be a great place to research for your product, or it may be an empty auditorium, but time will tell.

You can use search to discover important articles, conversations and authors; is particularly effective. Twitter users use hashtags – an Octothorpe (#) followed by a word or collection of characters – to "label" a tweet with a term that (a) provides context when you're reading it, and (b) provides a convenient way to search for information about a particular topic. For example, "#prodmgmt" is the hashtag that people use when talking about product management topics or sharing articles of interest to product managers. Once you uncover keywords and hashtags that people use to discuss your market, or the problems you are focusing on, you can use Twitter's search to find those conversations. Your competitors may already have a social network presence, and you can find what they are saying and who they are conversing publicly with, and insert yourself in those conversations. When you take the approach of contributing to these conversations and sharing what you learn, you can form relationships with these people and participate in the community.

When you do find hashtags that people regularly use, you can also use a site called WeFollow to see who the most-influential and most-followed people that talk about that hashtag are – is the page where you are introduced to the folks who are most engaged (and most listened-to), on Twitter, talking about product management.

Your goal at this point is to discover problems that might be worth solving, discover products that people use to solve those problems, understand trends about the market (past, present and future) and make connections with people that will help you gain more understanding.  

Quantifying Market Problems

You can get qualitative data by forming relationships and talking directly with individuals. You can use that qualitative data to drive the creation of surveys that help you quantitatively characterize what you learn. With high levels of engagement, you can get statistically significant insights. Even without significance, you can collect data that informs your hypotheses. Once you've done qualitative research, you are ready to quantify your insights – you form a hypothesis – this problem is more important than that problem, for example. You prove or disprove that hypothesis with quantitative data.  

"Prove" is actually too strong of a word; you can't prove anything about market problems, from a scientific point of view. You can, however, use data to validate or refute the premise that a particular problem is one that it is (already) important to people to solve. I don't believe that you can gain much insight into discovering problems people don't realize they have, however. Think of the time before the first mp3 players – how many people were talking about how unhappy they were that they couldn't carry their entire music library with them everywhere they went?

Creating good surveys, and motivating people to respond honestly to them is a tough problem, but not one I'll address in this tip. Once you have a good survey, if you've earned the attention of the people you've connected with through social media tools, you can get data to support your decision making. I've had success in using surveys to understand the frequency with which people perform activities (that were relevant to products I was managing at the time), profiling and characterizing aspects of the problems people were solving, and gaining feedback about the effectiveness of the products people were using to solve those problems.

There are also companies that do data mining of social media chatter, to perform sentiment analysis and gain other "more generic" insights, by monitoring what people say. This data is usually less specific, which makes sense, since those companies are not engaging in conversations, but rather eavesdropping on other conversations that are already happening. This type of data can be used both to help with your qualitative research (gaining insight), and in some cases, quantitative research.

Validating Your Solutions

With an established network of people that trust you (or at least like you), you can utilize your connections with people who are representative of your target personas to get feedback on prototypes, alpha (or beta) releases, design mockups, etc. You can even formalize this into a community of people who are willing to invest their time – providing feedback – in exchange for getting access to early versions of your product, or because they want an opportunity to participate in the creation of your product or in the community that you've formed around your product. In a recent interview, Eric Reis, author of The Lean Startup, talks about testing hypotheses as a key driver of iterative development and decision making. When quantifying market problems, you are testing hypotheses as well, but the data you get requires you to take a leap of faith in connecting that data with future successes. Getting feedback on a prototype requires a smaller imaginative jump on the part of users. Getting real usage data from volunteer users of an early release of your product gets you the best data – your only leap of faith is in believing that there are other people out there who will use your product the same way (and value its capabilities similarly) to solve their problems.

Seth Godin made a great point about social networks in an interview from a couple years ago; he said social networking tools have no intrinsic value. Relationships have value, and social networking tools can be used to form relationships. Use social media tools to form the relationships, but don't focus on the tools (or the networks) directly. The tools are great accelerants to forming relationships, but you have to contribute to create the relationships. Find something that Gary Vaynerchuck has said or written, and see how he forms relationships. If you can engage half as effectively as Gary, you'll get far more out of the relationships you form through social media than you try and "use" the people you find in those networks.  

For a comprehensive resource on social media, see Social media: A guide to enhancing ALM with collaborative tools.

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