Collecting Data and Making Data-Driven Decisions From Day One

*This is part of an ongoing series from Rezilion titled Enlightened Engineering: Reflections From Rezilion’s Tech Team

By: Shahar Bahat, Product Manager, Rezilion

Defining a product is one of the most essential missions of a company. As a product manager in a startup, this is the hardest and most valuable task. In this post, I want to highlight the importance of having data as your best friend from the start, and how it can be collected in the early days of a startup.

Data Challenges of An Early-Stage Startup

One of the main reasons startups fail these days is because they haven’t built the right product.

When building a new product as part of a startup, it is crucial to design the product based on validated knowledge rather than speculation.

This is a difficult task. When you’re an early-stage startup you have almost no data. So how can you make decisions based on data? No customers have joined yet, and most of your information is based on the internet and rumors. At best, you might have some back-in-the-day experience, but this isn’t enough.

Making Data-Driven Decisions Is The Holy Grail

For a product manager, data is a superpower. Today, most of the world is driven by data, and with good reason – it’s proved itself over and over again. When you use statistics to make decisions, you’re basing them on real events, on real outcomes, and most importantly – on knowledge. The more info you collect & analyze, the more accurately focused you are on customers’ day-to-day actions, problems, and reactions.

From data you can understand the necessary next steps, your product’s weaknesses and even predict trends that are happening or have happened in the past, so you can prepare for an unknown future. By using data, you listen to what actions and information have to teach you and use it to reduce mistakes and determine the next best step. Knowing what information to collect is necessary, but knowing how to use it is even more crucial.

How to Start Collecting Data In A Startup?

So, how do you use data when you don’t have any? Where to start? What to consider? 

The overall flow of collecting data goes like this:

1. Identify Your Sources

One of your main responsibilities as a product manager is to know. But how? You ask questions. But who and what should we ask? This is a huge question!

First it’s necessary to understand what questions we’re trying to solve and where we can find those answers.

In a startup with no data, every action you take is a source that you have to use smartly.

Your sources can be in the form of:

• A person who holds specific knowledge, or a specific profession we’re interested in.
• A platform or company that holds information you need or datasets you need to acquire. For example, a company that holds data you think will be of value to you. Even if it isn’t intended for sale, they might be willing to negotiate a deal with you.
• Friends or acquaintances whose expertise you appreciate.
• Social network insights (gathered from social networks like Facebook, LinkedIn, Glassdoor, etc.)
• Even watching people out on the street.

As long as it relates to your product needs, it can really be anything you think about.

Once you’ve considered all the sources, prioritize them based on trustworthiness, practicality, and cost-effectiveness. Then, write them down so they’ll be saved for later. I’m sure you’ll find them useful again and again.

2. Collect

It’s pretty straight forward. Ask your questions. Gather your data.

The more sources and types of sources you have, the more reliable your information is. It might be a frustrating process, but the more knowledge you have to begin with, the better prepared you will be.

3. Organize and Document

In my opinion, this is the most important part. Collecting data, conducting research or asking questions is beneficial. But if you don’t document it in a way that you can later use it for a variety of purposes, you’re wasting your time.

Defining your leading questions and data points before collecting is the first step.

Then, make sure you have a structured way of documenting everything you collect. My preference is Queryable data points, but Visual graphs are also an option. In documenting, it’s vital to specify the type and source of the data, so that you can determine how reliable each data point is.

For instance, take an interview and understand how to structure the answers into fields in a table you can use to ask multiple types of questions. Using this method, you can query this interview in the future and benefit from it, or even better, your co-workers can use it!

As part of this process you might lose some of the less essential details, but you should preserve the most vital information.

4. Store

Store the data in a central location suitable for any type of information. Establish a “data center” that will be the gateway to all information from this type. I personally like Splunk, or a local SQL database. As a result, you’ll use it more and everyone in the company will invest in it. Most importantly, you will minimize data loss. Furthermore, you are preparing the ground for integrating data sources and creating dashboards that can be presented in real-time.

5. Enrich

Some questions are more complicated than others. Combining different data points or sources gives you the best answers in these cases.

For example, taking information related to users and combining it with stats on the market can help anticipate future trends for our users.

Also, always identify what type of data points you might be missing. I’m sure that as you go through this process or even in your everyday routine and work, you’ll always say “I wish I had some data on…”. Act on it. Don’t wish – collect!

As long as you identify what is missing, you’ll always improve and learn more if you start collecting as soon as possible. If you stick to the same questions, sources, or advisors, the results and opinions will be the same. Utilize them, but always look for more directions and information to gain a broader perspective and understanding.

6. Analyze Using Your Questions

This is a fundamental part as well. Data can be very confusing and overwhelming.

Before we start analyzing the data, we need to come up with questions we want to answer and a plan on how we want to research the information to address those questions. The questions could be phrased in a variety of ways, such as:

• What platform does my client use? If so, how do they use it?
• Describe my client’s daily routine. What are X persona’s biggest problems?
• What is frustrating X persona in their day-to-day operations?
• What are the most common interview questions?

And more…

You can use the answers to define new features for your product, improve your interviews, discover pain points you hadn’t considered, create a better priority list, and so much more.

Additionally, you should share your conclusions! To make the insights useful to the company, you shouldn’t keep them to yourself. Talk about them.

When Is the Right Time to Collect Data?

The collection of data should have begun yesterday. As I’ve explained in this post – data is your power. You have to begin collecting it from the day your company starts. Each action you take gives you valuable information, and you should consider more actions that can give you insights.

Even though you won’t see results right away, in a startup’s life it is necessary  to collect information and document it so that it has a good knowledge base later on. 

Time and coverage matter a lot in this area, and as soon as you start it changes the game.

Furthermore, it’s necessary to get your colleagues and managers on board with understanding the importance of data collection and prioritizing it from the start. It’s a collective assignment – and when everyone is thinking about it, it will be built into company culture.

Continually Move Forward

At every stage of the product life cycle, data collection and analysis are ongoing processes that contribute to product data-driven decisions. Do not stop, the day you stop is the day your product loses its power.

There will always be new areas of challenge to be considered as you move forward in this journey, here are some I’ll discuss in my next blog post:

• How can I convince everyone to invest in collecting information?
• Data over memory and money
• How can I master the volume of information without getting lost in it?
• The different levels of evidence to trust

It’s time to take the first step on your journey. What do you want to know? What methods are you using today? What are potential sources?

Besides being an influential journey, it’s also a lot of fun!