Growth Hacking, Retention, Acquisition, Conversion: Growthmint

Day 3: Data

Using data is a foundational principle of growth. Data points you in the right direction and tells you whether your hard work is paying off or not.

Over the last several years, there has been an explosion in ways to collect data and analyze it. This is both a good and a bad thing.

It's great to see more and more powerful tools coming out to allow wider collection and deeper analysis of data. At the same time, it means there's a lot more data to dig through to find insights.

There are two types of data, quantitative and qualitative, and both are extremely important to growth.

Quantitative data

Quantitative data is what people typically think of when they hear the words data and growth in the same sentence. It's the type of data you see used in "the percentage of people who ..." type statements.

This is the kind of data that's collected when you visit a website or use a SaaS app. This data is collected and then analyzed with analytics software, which I go into in Day 5.

Qualitative data

Qualitative data is the type of data you get in focus groups and surveys. It typically involves extended and detailed answers to questions. It can't be measuered like quantitative data can.

It's not as common for people doing growth to involve this type of data as it is with quantitative data. This is a big missed opportunity because while quantitative data tells you what your customers and potential customers are doing, it doesn't tell you why.

Collecting qualitative data

Surveys are the most common way to collect qualitative data. This type of data collection is about getting to know concerns and goals of your market.

Ways to collect data:

  • Survey people in your target market with a tool like Google Consumer Surveys.
  • Survey visitors on your public facing website with a tool like Qualaroo.
  • Survey your customers with in-app (Qualaroo is also good for this), email, web (try Survey.io or SurveyMonkey), and phone surveys.
  • Put together focus groups.

Example

For a client, I created a survey and sent out an email from one of the founders of the company asking customers to fill it out. We got back a ton of insights, including important things we had never thought about.

Ask the right questions

The questions you ask should be clear and, if they’re not open ended, the answer choices shouldn't be either. Here are the six most common question mistakes made in research:

  • Using leading words and/or questions - An example is: “How difficult is it to use [insert a competitor]’s app?” This suggests that it’s difficult to use and leads the person responding to answer in that direction. A better question would be: “Do you think [insert a competitor]’s is difficult to use?”
  • Not asking direct questions - You want to be specific about what you’re asking. This reduces confusion among the people responding.
  • Forgetting to add a “prefer not to answer” option - This is especially an issue if you are collecting sensitive information that the person responding might not want to share.
  • Failing to cover all possible answer choices - You’ve been there before. You’re taking a test and you carefully consider each of the possible four answers. Yet there is a fifth possibility. How are you supposed to answer this? If you are unsure if you’ve covered all possible answers (and it can be hard), just include an “other” field that can be written in. Carefully consider the other reasons to see if any are worth adding.
  • Asking more than one question at a time - This is called a double barreled question. It’s confusing because you’re being asked to answer two questions with one answer. For example, if you asked “What email SaaS solution is easiest to use and has the most features?” Different products could be the easiest to use and have the most features.
  • Not providing mutually exclusive answers - For example, if you asked “how far do you live from your workplace” and gave the following possible answers to choose from: a) 0-5km, b) 5-10km, c) 10-15km. What answer would you select if you lived exactly 5km away from where you work? There are two possible options that you could choose from (both of which are correct). To make the answers mutually exclusive, b) should be 6-10km and c) should be 11-15km.

Pro Tip

Don’t ask too many questions at once, especially if they’re open ended. The sweet spot is 1-3 open ended questions and up to 10 multiple choice.

Pro Tip

Keep your surveys as simple as possible to get the most results.