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Product development has long been a high science with frameworks, rules and significant research conducted to ensure that the product in question is fit for the market and valued for its price.
But not all companies use 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 too important to get wrong or approach without sufficient intelligence. While most organizations adopting a product engineering mindset approach their product development cycles with a structured framework, they may fail to analyze and integrate deep insights from billions of product conversations online. , companies and trends.
Like McKinsey wisely declared, digital product managers “are increasingly the ‘mini-CEOs’ of the product”, responsible for many different facets and held accountable for success, whether or not a failure had something to do with the creation of the product itself. -same. The sad reality is, in many ways, 80% to 95% of all products fail.
At every stage of the product development lifecycle, AI-powered product information platforms contribute significantly to creating, optimizing, and better bringing products to market.
Here are the five recognized stages of the product development cycle and some specific ways product information platform can give organizations the best chance to maximize their return on investment.
The ideation phase includes assessing trends and opportunities, studying the competitive landscape, and identifying white space opportunities. While many companies rely on simple social listening and human evaluation, AI-powered product intelligence is another level of guidance.
Instead of latent indicators caused by reading reviews today, product intelligence platforms can analyze entire conversations to understand where customer preferences are heading. The end result is the creation of a product that appeals to today’s market and prepares the organization for the future.
Once the ideation process is complete and a product is conceptualized, product teams must get to work, producing features and establishing product leadership attributes to become a winner. This is where good ideas can die if they fail to get the details right.
A product insights platform ensures that this definition phase focuses on the product attributes that customers will want and need, while also understanding the attributes of your competitors’ products that customers love or hate. . This is not easily achieved by generic text analysis or customer experience tools who can analyze surface-level meanings on public comments. By focusing on a simple aggregation of public feedback without a measure of scale or influence or deeper context, companies can make the wrong decision, rendering a product undesirable or obsolete within a year. Given that 45% of product launches are delayed, tapping into real-time feedback is a huge opportunity to move the process forward while always staying on top of changing consumer preferences.
Now the “real work” begins via the development cycle. Companies that don’t have the right intelligence tool at this stage go headlong and develop a product over months or years, confident that their pre-development knowledge remains valid.
This is where product intelligence helps manufacturers of physical products behave more like their digital counterparts, who use the Minimally Viable Product (MVP) methodology to launch foundational products and iterate as developments occur. additional are required. While physical products don’t allow for as many iterative builds, they can still use Intel to course correct. Companies that are constantly monitoring product intelligence can keep tabs on the billions of daily conversations to ensure the development roadmap is correct and start identifying new features for future releases.
Once your company has imagined, defined, developed and optimized your product, comes the moment of launch. Many amazing products never had a chance to change consumers’ lives because the launch failed, either due to bad messaging, bad timing, or go-to-market strategy. Prior to launch, brands identify target personalities and define launch strategy and positioning. After the launch, they monitor the successes and compare them to previous product launches or those of their competitors.
Although the product was built at the time and therefore cannot be changed, how a product is positioned can often have as much of an effect on success as how it was built. Good intelligence platforms can leverage existing conversations to understand existing customer perception on both anticipation of this launch and ongoing consumer opinions about product category and competition – which can also help. identify product problems and crises early on. It allows you to benchmark your product against all of the competition, as well as identify channels that could help you introduce your product to a much larger audience.
Companies monitor product issues, address safety or liability issues, and test product performance during the optimization phase. Again, this all happens within the organization and is specific to the product being developed.
The right insights platform absorbs conversations about customers’ first impressions of your product and validates or challenges your marketing strategy. By keeping information in an always-on approach, you can fix attributes that will be poorly received and add additional features that could mean the difference between a failed launch and a one-time success.
Putting it all together: product management and development
Companies that integrate AI-powered product insights from online conversations are more likely to make smarter decisions at every stage of the product development cycle, likely leading to fewer delays and greater chance of being in the minority of successful products. When the cost of failure is so high, it’s an obvious step every organization should take to protect their investments and maximize their chances of success.
Rodrigo Pantigas is co-founder and CPO of Birdie.
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