AI & RoboticsNews

How AI powers modern product lifecycle management

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 – 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Register today!


Product development has long been an elevated science with frameworks, rules and significant research work conducted to ensure the product in question is fit-for-market and valued for its price. 

But not every company is using 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 incorporate deep insights from the billions of online conversations about products, companies, and trends. 

As McKinsey wisely stated, digital product managers “are increasingly the ‘mini-CEO’ of the product,” responsible for many different facets and held accountable for success, regardless of whether a failure had to do anything with the actual product creation. The sad reality is, 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 create, optimize, and market products better.

Here are the five recognized stages of the product development cycle and some specific ways the right product insights platform can give organizations the best chance to maximize their return on investment.

Ideation

The ideation phase incorporates assessing trends and opportunities, surveying the competitive landscape, and identifying white space opportunities. While many companies rely on simple social listening and human assessment, AI-driven product intelligence is another level of guidance.

Instead of latent indicators caused by surfacing reading of comments today, product intelligence platforms can crunch the totality of conversations to understand where customer preferences are going. The end result is creating a product that appeals to today’s market and future-prepares the organization.

Definition

Once the ideation process finishes and a product is conceptualized, the product teams must get down to brass tacks and productize features and establish product leadership attributes to become a winner. This is where good ideas can die if they fail to get the specifics right. 

A product insights platform ensures this definitional phase focuses on product attributes customers will want and need while also understanding which attributes your competitors’ products have that customers love or hate. This is not easily achieved by generic text analytics or customer experience tools that can parse surface-level meanings on public feedback. By focusing on a simple aggregation of public comments with no measure for scale or influence or deeper context, companies can make the wrong decision, rendering a product unwanted or obsolete within a year. Considering that 45% of product launches are delayed, tapping into real-time feedback is a huge opportunity to keep the process moving while always staying on top of how consumer preferences are changing. 

Product development

Now the “real work” begins via the development cycle. Companies without the right intelligence tool at this point go heads down and build out a product over several months or years, confident that their pre-development insights remain valid.

Here is where product intelligence helps physical product manufacturers behave more like their digital counterparts, which use the minimally viable product (MVP) methodology to release foundational products and iterate as additional development is needed. While physical products do not allow as many iterative releases, they can still use intel to course correct. Companies continuously monitoring product intelligence can keep an eye on the billions of daily conversations to ensure the development roadmap is correct and begin identifying new functionality to incorporate in future releases. 

Launch

Once your company has ideated, defined, developed, and optimized your product, the time comes for launch. Many amazing products never had a chance to change consumers’ lives because the launch failed, either due to poor messaging, timing, or go-to-market strategy. Pre-launch, brands identify target personas and define launch strategy and positioning. Post-launch, they monitor successes and compare them to previous product launches or the ones from their competitors.

While the product has been built by this time and therefore cannot be altered, how a product is positioned can often have as much effect on success on how it was built. The right intelligence platforms can tap into existing conversations to understand existing customer perception both about the anticipation of this launch and consumers’ ongoing opinions about the product category and competition – which can also help to identify product issues & crises early on. It allows you to contrast your product against the competitive set, as well as identify channels that could help get your product in front of a much wider audience.  

Optimize

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

The right insights platform absorbs conversations about customers’ initial impressions of your product and validates or calls into question your marketing strategy. By keeping insights in an always-on approach, you can course-correct any attributes that will be poorly received and add additional features that could make the difference between a failed launch and a once-in-a-lifetime success. 

Putting it all together: Product management and development

Companies that incorporate 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 a higher chance of being in the minority of products that succeed. 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 cofounder and CPO of Birdie.

DataDecisionMakers

Welcome to the VentureBeat community!

DataDecisionMakers is where experts, including the technical people doing data work, can share data-related insights and innovation.

If you want to read about cutting-edge ideas and up-to-date information, best practices, and the future of data and data tech, join us at DataDecisionMakers.

You might even consider contributing an article of your own!

Read More From DataDecisionMakers


Author: Rodrigo Pantigas, Birdie
Source: Venturebeat

Related posts
Cleantech & EV'sNews

Einride deploys first daily commercial operations of autonomous trucks in Europe

Cleantech & EV'sNews

ChargePoint collaborates with GM Energy to deploy up to 500 EV fast chargers with Omni Ports

Cleantech & EV'sNews

How Ukraine assassinated a Russian general with an electric scooter

CryptoNews

Day-1 Crypto Executive Orders? Bitcoin Bulls Brace for Trump's Big Move

Sign up for our Newsletter and
stay informed!