We’ve talked about how important data is in many of our articles, and it’s not surprising why. Data is one of the most important things businesses rely on in many aspects. One of these aspects is product development.
Product managers have so much data at their disposal, including customer feedback, satisfaction rates, and behavioral data. In this article, we’ll discuss what data you must focus on when developing products, we’ll look at some examples from the real world, and explain how to collect the necessary data for the most effective data-driven product development.
Why is Data-Driven Product Development Important?
Without looking at the data about your customers, what they do with your product or service, or what they like and dislike about it, you would be just guessing in the dark in the development process. That is definitely not something you want to do in your business. If you look at the numbers, it’s clear that data-driven decisions can enhance your products tremendously:
- It is 23 times more likely that you will be able to acquire more customers if you take data-driven analytics into account.
- You can decrease your profits by 8% by using Big Data.
- 62% of organizations think that if they take into consideration information and analytics, they can gain a competitive advantage.
- One-third of professionals believe that using the right technology for data analytics is the way to better understand customers.
From these statistics, it is evident that data is definitely something you must consider in your product development, as it will drive more success and a better understanding of the needs of your customers.
What Kind of Data Should You Look Out For?
In product management, there are many types of data you must analyze to be able to determine the specific steps you need to take in development. An article by Product School explains that it requires data from several channels: user data, product data collection, and market research. As for the user data, here are some specific information to inspect:
- NPS (Net Promoter Score) for seeing satisfaction rates
- Retention Rate
- Customer Acquisition Cost
- Lifetime Value
- Monthly Recurring Revenue (MRR)
- User flows for identifying how your customers interact with your product, where they might get stuck, etc.
- Bounce rates to see why customers leave the business without any activity
- And heatmaps for determining areas of interest and improvement opportunities.
Now, let’s look at what the experts have to say about the data types when asked about their experience.
In my conversation with Arthur Augusto Barreto Monteiro, Product Manager at ClearSale, when asked about what type of data they look at in the product development process, he listed the following: “Interaction data and surveys are the most important: frontend insights about user behavior, like using funnels or cohorts to understand our user. It gives us insights into new features/platform development.”
Gaurav Srivastava, Product Development Manager at Zycus, answered: “Customer data before product development has to do with the bird's eye view. Specific data points include the target audience, geographic location, and user roadmap. Also if we follow the TDD approach, producing an MVP for the customer, getting feedback on the expectation, and reiterating the development process play a very crucial time-saving effort.”
Among many other things, these types of information can help you determine the different stages, features, and next steps you want to take when developing your product.
Real-Life Examples of Companies Using Data-Driven Decisions
Amazon stands out in making sure their customers have a very personalized experience. And how do they do that? Of course, with data-driven decision-making. They have a vast information collection in their system, making sure they know everything about their customers and what they like and dislike. They look at customer feedback, reviews, and browsing history to make sure their improvements and innovations are all serving the needs of their users.
Uber has transformed the transportation industry without owning a single vehicle. How? By using data science and big data to improve their operations and create a service that offers a solution for exact customer pain points. They use data for surge pricing, enhancing vehicle quality, and investigating fraudulent activities, such as fake rides, cards, and feedback. Data-driven decision-making enables users to match with the most suitable drivers in 15 seconds.
Netflix is known for its complex and very personalized algorithm that offers specific suggestions for users based on their preferences and previous behaviors. On their website, they explain that “Our portfolio of work involves diving into large, complex data to answer ambiguous business questions. We work cross-functionally across business domains to discover and assess new opportunities, create new business metrics to measure success and inform prioritization. We also strive to make analytic tools self-service to make data and insights even more accessible.”
Airbnb uses data analysis and algorithms to ensure that its users receive location relevance when searching for a place to stay. They implement smart pricing by predictive analytics and geospatial factors. In addition, they use risk assessment, background checks, and reviews to create a safe space for the people who travel and for those who host.
How to Collect Customer Data Effectively
In the statistics, at the beginning of our article, you could read that one-third of industry professionals believe that to understand your customers deeply and effectively, you need to use great technology.
At SAAS First, we offer you a platform where you can collect data on your customers easily and without limitation. But what do we mean by that? We offer you the chance to collect people’s static data, any information in relation to their businesses, and also the different events that might be happening while using your product or service. What is more, you can store an unlimited number of event types, and within that, unlimited amounts of data for each type.
With us, you can ensure you have all the data you need to make data-driven decisions in your development process, as well as in other areas of your business.
In conclusion, harnessing customer data for product development is essential for modern businesses aiming for success. Focus on the right data sets, such as user behavior, satisfaction metrics, and market trends to make informed decisions that resonate with your customers' needs and preferences. Plus, invest in a technology like SAAS First that enables you to collect and analyze data effectively to create profitable product development strategies.