Solicited data
1. Solicited data
In the last lesson, we learned about data that your company can collect through the web or financial transactions. Now, we'll cover data you can obtain by asking your customers for their opinions, which we'll call solicited data.2. Why do we solicit data?
Solicited data can be used to create marketing collateral, such as a post about what percent of our customers are satisfied with our product. It can also be used to de-risk a decision making process, such as when we survey users to gauge interest in a new product. Finally, it can be used to monitor quality, such as when DataCamp asks users to rate each course.3. Types of solicited data
Common types of solicited data include surveys, customer reviews, in-app questionnaires, and focus groups. This image shows a very common type of solicited feedback: the Net Promoter Score, or NPS, which asks how likely a user is to recommend a product to a friend or colleague.4. Types of solicited data
Solicited data can be qualitative, such as conversations and open-ended questions, or quantitative, such as multiple choice questions or rating scales. Qualitative data is very subjective and requires a lot of analysis. Quantitative data can be easily summarized in a graph or chart. In general, collection of small-scale qualitative data is good for generating hypotheses. For example, a focus group might provide some ideas about what features we might want to build. Larger scale quantitative collection is needed to validate these hypotheses. For example, we can ask users to rank a list of features from most desirable to least desirable.5. Revealed and stated preferences
It's important to remember that solicited data generally tells us our users' stated preference. A stated preference is what someone tells us they want or believe, and is somewhat hypothetical. When a user actually takes an action, such as purchasing a product, we learn their revealed preference. We hope that our users' stated preferences are good indicators of their revealed preference, but this isn't always the case. Many people have a stated preference to go to the gym frequently. However, many of the same people's revealed preference is only to go occasionally. Some gyms have an entire business model based off of the expected difference between people's stated and revealed preference for exercise.6. Best practices
Now that we know some types of solicited data, and are aware of the pitfalls of revealed versus stated preference, let's go over some best practices. First, we should try to be as specific as possible when asking questions. This specificity should apply to both the wording of the question and the potential answer choices that we give.7. Best practices
Next, we should avoid loaded language, especially if it might bias respondents toward a particular choice. For example, avoid using adjectives to describe possible choices and try to be objective.8. Best practices
Whenever possible, calibrate your survey by comparing to known quantities. For example, rather than asking a respondent if they are interested in a new product, ask them to compare their interest in that product to their interest in one of your current offerings or the offerings of a known competitor.9. Best practices
Finally, it can be tempting to ask as many questions as possible. Fight that instinct and instead ensure that every question you ask will help you take a decisive action. For example, if customers indicated a preference for Feature A over Feature B, you should commit to building Feature A first.10. Let's practice!
You've learned about uses for solicited data, types of solicited data and the dangers of revealed versus stated preference, and some best practices for designing questions. Let's practice!Create Your Free Account
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.