Principles of Product Intelligence

1.  It is not possible to isolate customer data management, behavioral targeting, analytics, and experimentation from one another and optimize the product experience.

You might have the best analysis, charts, and data tools but in the absence of the right data, a business will struggle. The three components of product intelligence are as follows:

·       Product Analysis

It’s a real-time analysis for monitoring and exploring the consumer behavior along with a cross-platform digital journey. It helps understand the effect of product bets.

·       Customer Data Management

It is all about data pipelines with tools to monitor data and accessibility. It helps in creating accurate windows into the behavioral data.

·       Behavioral Targeting

It is all about integration into other platforms and connecting data to other tools for powering personalized experiences and analyzing results immediately. It helps in keeping up with regular releases and enables the teams to understand how the releases can improve experiences to enhance consumer lifetime value.

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2.  Platforms and integrations don’t offer a great product experience but teams do! Businesses need to help them collaborate in an effective manner.

Modern product teams are cross-functional as well as collaborative. The back-and-forth process is fast and fluid. Collaboration is a whole model and not simply offering access to the notebooks and dashboards. The business needs to push the teams around the learning loop.

The process begins with a handful of employees or teams. Other teams witness what’s happening. They observe the impact and wish to be a part of the same. With product intelligence, an advanced version of the learning loop can be applied.

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