Creating a great product is a combination of intuition and science. Product decisions must balance inputs from feedback and customer information, data, and insights from product and engineering teams.

To resolve these tasks, you should create a data-driven strategy, and my goal today is to share with you three following techniques:

1. Identify Customer Needs – become Customer Obsessed:
Gathering data about your customers or end-users and their workflows – actually speaking to them, helps you to uncover what they need, what their pain points are, and how you can improve your product to address those needs and pain points. The key to a data-driven strategy is precisely identifying your customer’s problems.

You should Integrate and analyze a combination of data sets. This is the only way to gain insights into your customer’s behavior and form a 360-degree view of your customer as an individual.

“The product teams need to focus on adjusting their development priorities to enhance the customer experience, improve customer satisfaction, increase analytics adoption rates, and most importantly – solve the customer pain. ”

2. Infuse Insights into your Product Development Process:
A deep understanding of customer needs and behaviors is a cornerstone of startup success. Successful startups build their products and services around solving real customer problems, constantly seeking feedback, and adapting to meet their evolving needs.

Use data and insights to understand your customers and how you will evolve your product and their experience, and infuse your product with insights that provide value to them. Using big data, for example, can infuse insights from data into your product development process. Let me explain:

Using data to fuel real-time and machine-learning efforts can give you a personal customer vision: Your edge will come from self-sustaining cycles of real-time, two-way, insights-driven interactions that are actionable and delivered precisely where your users need them.

For example, Uber’s new features are not created because a customer requested them but because the team using data realizes they can provide a new feature to solve a problem we didn’t even know we had.

3. Prepare your Team:
Using data to create a product strategy begins with handling the data, but for this to be effective, your team has to be cross-departmental and cross-disciplinary

Your team needs individuals willing to go beyond their areas of knowledge. Data scientists must be willing to learn about marketing, salespeople must be willing to learn about IT, and engineers must know about product fundamentals.

A good approach, for example, is to assemble your data scientist team with individuals from different specialty areas or hire an executive to oversee data and analytics. It would be best to prioritize collaboration between these people, having frequent informal meetings where everyone shares ideas and information.

This is also an effective way for everyone to start thinking about and better understanding the customer’s needs.

Remember, the faster you implement those items, the quicker you’ll be on your way to growing your business. Cr