3 Major Product Management Trends for 2023
Product management in 2022 was all about product-led growth. With the way things are going, we can safely say that 2023 will be all about AI.
From streamlining the product development process to validating product ideas, product managers do everything they can to outperform the competition. As we enter into 2023, product managers will continue to use a customer-centric approach to building products, and product-led growth strategies will continue to prevail.
In addition to these continuing trends, AI will play a larger role in all major aspects of product management, product operations roles will continue to gain in popularity, and product managers will rely on customer feedback like never before. Here’s how those three product management trends will play out in 2023.
1. Increased Use of AI to Support Iteration
Product managers are increasingly relying on AI technology to help them improve internal processes, as well as build customer-facing features. According to IBM, 21% of product managers use AI, putting them in the top 10 AI user groups across the world. The same report shows that the global adoption rate of AI grew four points in 2022 and is currently at 35%. In addition to that, 42% of organizations are in the process of embedding AI in their processes. We expect this trend to continue in 2023, especially as AI plays a more significant role in product management.
How Will Product Managers Use AI in 2023?
Product managers will use AI to gather and analyze data and add AI-based features to their products. Products using AI require product management approaches that ensure features fulfill customer demand and are technologically feasible—AI product management combines these two overarching objectives into one discipline. Developing an AI product strategy will help your team identify market needs, validate product hypotheses, and create AI models to fulfill the product’s function.
Gathering Competitive Intelligence (CI)
Product managers gather data about their industry, competitors, and customers from multiple sources. That data needs to be prepared for analysis with the help of data professionals and then analyzed with the help of business analytics tools. As companies gather more first-party data, PMs will need tools that can analyze that data faster.
AI tools such as Kompyte and Crayon help product managers create their own CI programs that automate manual processes, process large quantities of data easily, and gain accurate insights. As data sets grow and more products flood the market, product managers will tap into the latest AI tools to create AI-assisted CI programs.
Introducing AI-Enabled Features
Customer-facing features such as AI chatbots (like Drift) and AI-powered learning management systems (LMSs) (such as Docebo) have been on the market for years. In fact, “AI-powered” has been an industry buzzword since before 2017. But as more organizations adopt AI technology, that technology will power more and more customer-facing features for software products across industries.
For example, UserVoice uses OpenAI to distill large amounts of data and customize GPT-3—a natural language processor (NLP)—to create AI-powered features. One such feature is UserVoice's Merge Matches technology which automatically scans feedback data for duplicate product suggestions and requests. The feature minimizes the time product managers have to otherwise spend combing through data and manually sorting and combining similar ideas.
Netflix’s use of machine learning and AI to recommend content to each user based on their viewing habits is another example of AI-enabled features in a product.
2. Rise of the Product Operations Role
As your company grows, you’ll likely launch new products, add features, collect more data, and need to manage user feedback. Those demands may eventually cause a strain on your systems and processes since it’s a lot for one product manager to handle.
Product operations is an emerging role in the product management world meant to address the demands of growing companies and product lines by supporting the product team through a smooth development, launch, or update. The product operations manager focuses on the operational aspects of development, like streamlining processes, workflows, and cross-functional alignment with other departments. This frees up the Product Manager’s time to focus on what they do best: building amazing products. The role has been around for a while, but has recently become more popular with companies that offer software products, such as Adobe, TikTok, and Uber.
Data is integral in product management, and a product operations manager is meant to help the team understand data and prioritize what actions to take based on the data. Product ops managers are generally data literate and can save a team a lot of time figuring out what their next move should be. Product ops collects, organizes, and analyzes internal and external data, such as:
- Customer feedback, support tickets, and feature requests put in by customers and the support team
- Data from experiments set up by the product team
- General product usage data, such as active monthly users, session length, user churn, etc.
- Data from finance about quarterly growth and expense reports for product upkeep
- Data from sales about user acquisition, as well as qualitative data related to feedback from prospects (who have yet to turn into customers)
- Marketing data about the target market’s response to the latest campaigns and messaging
Product ops managers are also responsible for product research to help your team understand what consumers want and for process refinement to help your team be more efficient in product development, and they are usually responsible for managing the team’s tech stack.
Product ops managers serve as a bridge between your product team and the rest of the company. They may be responsible for presenting product changes to the rest of the company or sharing product-specific data that may influence product development.
Overall, the product operations manager role is one that will drive collaboration in the coming years while helping teams make data-driven decisions.
3. Feature and Product Changes Based on Customer Feedback
While AI tools can predict user needs with increasing accuracy, customer feedback will continue to play a central role in shaping products.
Product feedback software (such as UserVoice) can help your product team differentiate from competitors by staying ahead of trends related to customer needs. Knowing what customers really want and building your product based on their needs will help you stand out in an increasingly saturated market.
Let’s say you are consistently receiving feedback about your task management software that says users would prefer to filter tasks by client or project, not just by the due date. If the current filtering system is standard in the project management industry, you could be the first one to launch a unique solution if you pay attention and leverage that feedback. If you don’t listen to your customers and give them what they need, someone else will beat you to it, which will lead to customer churn.
If you didn’t have feedback management software, you wouldn’t even know that a substantial number of customers want more filtering options!
You spend a significant amount of time doing market research and analyzing customer data, so you can learn more about your customers and their needs. A feedback management tool that centralizes your data can help you spot emerging trends to stay ahead of the market.
UserVoice Discovery Offers a Data-Driven Response to Product Management Trends
If a focus on solutions to customer feedback is a priority for your team in 2023, consider UserVoice Discovery. We are a platform designed to help you collect and organize customer feedback, making it easy for you to synthesize data that informs product innovation and updates. To find out how UserVoice can help you get ahead of the competition, check out our free trial.