Data-driven decision making is one of the most important skills for startup founders to learn. As you begin to scale your startup, you will be forced to make decisions about your product, customers, and team. By learning and applying data-driven decision making, you can increase trust within your organization and grow a strong, scalable business.
Data inspires the best decisions. That’s why data scientists and analysts are worth their weight in gold. For us mere mortals however, it can be almost impossible to make data-driven decisions every day. Data is power, but it’s a power we don’t often use. The solution to becoming a data-driven startup? This guide!
1. Decide What You Want to Measure
Deciding what you want to measure is the first step of the data collection process, and probably the most important. If you’re not looking at the right metrics, you won’t collect the data you need to make informed, data-driven decisions.
At the end of the day, there are lots of metrics you can track. It’s essential that the data points you are measuring are perfectly aligned with your business goals, given your unique value proposition, target audience, and other idiosyncrasies of your startup.
So when deciding what you want to measure, ask yourself these questions:
- What is the purpose of my business, really?
- What very specific type of person am I targeting?
- What demographic and behavioral variables are likely to predict interest in my startup’s product (or service) offering?
Once you’ve asked yourself these questions, develop robust survey questions that will help you monitor this over time. It’s important that the way you ask these questions doesn’t change over time, either, so that you’re able to measure the impact of even tiny changes to your messaging on just how much interested your audience shows in your offer.
2. Collect Data
Collecting data is the next step here. It can be done in different ways. Some of the most common methods include surveys, interviews, focus groups, and field experiments. In some cases, companies can also use secondary data that has already been collected.
There are numerous benefits to collecting your own data with a survey. You can customize your questions to get extremely specific answers, you have the freedom to make changes as needed during the collection process, and you have total control over who is participating in the study. However, there are also some disadvantages to collecting your own data as well. It may take longer to collect the data depending on your method and it can be quite expensive. But with a tool like MR4S, you don’t have to worry too much about getting all of this right — we use time-tested methodologies to make sure you’re getting high-quality respondents to your survey, and fast!
3. Interpret the Data
Interpreting data is the process of assigning meaning to the data you collected. It is simply a matter of knowing how to read charts and graphs, and making sure that the proper conclusions are being drawn from them.
What’s important is to think about possible cuts and segmentations to make on your survey questions. Could it be that males and females answered your questions differently? If so, you want to know that — it may impact your marketing and go-to-market strategy.
Consider possible data cuts that might be relevant to your particular startup.
Data interpretation is also important in determining whether something was done correctly in the deciding what to measure phase. For example, if the results of a survey don’t help you understand the market better or understand the success of your business, then you didn’t choose the right things to measure. You can only know this once you’ve analyzed and interpreted your data.
4. Make Decisions
Making decisions is the fourth step of the data-driven startup decision making process. Once you’ve chosen your measurements, collected your data, and analyzed and interpreted it, you then need to decide what to do with that information. In order to truly make the most of your analytics, you should consider who you want to share the data with and how much influence they will have in the decision making process moving forward.
The three main approaches for making decisions include:
- Decision by authority: This is when one person makes all of the decisions based on the data, combined with their knowledge and experience in a certain area.
- Decision by consensus: This is when everyone involved in a specific decision gets together, discusses their conclusions about the data and comes up with a solution together as a group.
- Decision by consultant: This is when a consultant is brought in to interpret the data and see where its results can be most beneficial. This is a good option if your company feels stuck and you need a fresh pair of eyes. Data-driven decisions aren’t always easy! It can sometimes take a professional to know exactly how to interpret
5. Measure Success by Repeating the Process
Measure your success by repeating the data collection process. A second round of data should show whether your new approach is working. If it isn’t, you’ve learned something valuable, and can course correct to try again.
When you gather data to inform your decision making process, you should test it as often as you can to learn whether to make adjustments. If a second, third, or fourth round of testing shows more promising results, keep doing that. In the end, you’ll have mastered the same resourcefulness and grit needed to scale your business.
You’re well on your way to becoming a truly data-driven startup!
Once you’ve completed a survey, check out our guide on how to present your findings to investors.