How AI powers modern product lifecycle management

We’re excited to bring Transform 2022 back to life on July 19th and virtually July 20-28. Join AI and data leaders for sensible conversations and exciting networking opportunities. Register today!

Product development has long been a high science with a framework, rules and considerable research work that ensures that the product in question is appropriate for the market and valued for its value.

But not every company uses the full suite of tools available to tap into the collective wisdom of the consumer base. Developing a product that can make or break your organization is very important to take the wrong approach or approach without sufficient intelligence. While most organizations adopt a product engineering mindset that adapts their product development cycle to a structured framework, they may fail to analyze and incorporate deep insights from billions of online conversations about products, companies, and trends.

As McKinsey wisely puts it, digital product managers are “increasingly the ‘mini-CEOs’ of product, responsible for many different aspects and are responsible for success, regardless of the failure to create the actual product.” The sad reality is that, by many measures, 80% -95% of all products fail.

At every step of the product development cycle, there are meaningful contributions from AI-powered product insights platforms to better create, optimize and market products.

Here are five valid stages of the product development cycle and some specific ways that the right product insights platform can give organizations the best opportunity to get the maximum return on their investment.


The thinking phase involves evaluating trends and opportunities, surveying the competitive landscape, and identifying opportunities in the white space. While many companies rely on simple social listening and human evaluation, AI-powered product intelligence is another level of guidance.

Instead of latent indicators due to reading comments today, product intelligence platforms can crunch the integrity of a conversation to understand where customer preferences are going. The end result is creating a product that appeals to today’s market and prepares the organization for the future.


Once the thought process is complete and the product is conceived, the production teams should land on the brass tax and build the production facilities and establish the product leadership features to be the winners. This is where good ideas can die if they fail to get the specifications right.

The Product Insights Platform ensures that this defining phase focuses on the features of products that consumers want and want while also understanding what features of your competitors’ products customers love or hate. This is not easily achieved by general text analytics or customer experience tools that can analyze surface-level meanings on public feedback. By focusing on simple aggregation of public comments without any criteria for scale or performance or deep context, companies can make the wrong decision, which can make the product undesirable or obsolete within a year. Given the 45% delay in product launches, tapping into real-time feedback is a great opportunity to move the process forward while always keeping abreast of how customer preferences are changing.

Product development

Now the “real work” begins with the development cycle. At this point companies without proper intelligence tools go down and build products in many months or years, with the confidence that their pre-development insights remain valid.

Here Product Intelligence helps physical product manufacturers behave more like their digital counterparts, using the Minimal Practical Product (MVP) method to release basic products and replicate them as additional development is needed. While physical products do not allow many repetitive releases, they can still use Intel to do the course right. Companies constantly monitoring product intelligence can monitor billions of daily conversations to make sure the development roadmap is correct and begin to identify new functionality for inclusion in future releases.


Once your company has thought, defined, developed, and optimized your product, it’s time to launch. Many awesome products never had a chance to change the lives of consumers because the launch failed, either because of poor messaging, time, or market strategy. Pre-launch, brands identify target individuals and define launch strategy and position. After the launch, they monitor successes and compare their previous product launches or those of their competitors.

While a product has been made by this time and therefore cannot be replaced, how the product is located can often have as much of an impact on the success of how it was made. Appropriate intelligence platforms can tap into current conversations to understand current consumer perceptions about both launch expectations and current customer perceptions about the product category and the competition – which can also help identify product issues and crises early on. It allows you to contrast your product with a competitive audience, as well as identify channels that can help bring your product to a wider audience.


Companies monitor product issues, address safety or liability concerns, and test product performance in the optimization phase. Again, all of this is happening within the organization and is specific to the product developed.

The right insights platform absorbs conversations from customers about the initial impression of your product and validates or calls your marketing strategy. With insights into an always-on approach, you can course-improve any poorly acquired features and add additional features that can make the difference between a failed launch and a one-time success in life.

Putting it all together: product management and development

Companies that incorporate AI-driven product insights from online conversations are more likely to make smarter decisions at each stage of the product development cycle, resulting in fewer delays and more chances to be in the minority of successful products. When the cost of failure is so high, it is a clear step for every organization to secure their investments and increase their chances of success.

Rodrigo is the co-founder and CPO of Pentigas Birdie,


Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including tech people working on data, can share data-related insights and innovations.

If you would like to read about the latest ideas and latest information, best practices and the future of data and data tech, join us at DataDecisionMakers.

You might even consider contributing to your own article!

Read more from DataDecisionMakers

Similar Posts

Leave a Reply

Your email address will not be published.