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Product-led Growth and Product Analytics, Can There Be One Without The Other?

What is Product-Led Growth for Embedded Devices?

Product-led growth puts the product experience, both from a software and a hardware perspective, into the focus of the go-to-market strategy. Instead of planning sales and marketing operations around high-touch customer engagements and marketing campaigns, the digital and physical experience of the embedded device is such that customers proactively engage in the purchase process.

Easy product onboarding, quick time to value, and a superior understanding of which features provide continuous value to end users are key to a successful product-led go-to-market execution. Can a Product Manager achieve these three success criteria without product analytics?

Learning the Customer Objectively

The concept of customer-centricity has been a driving force for us Product Managers already for more than a decade. Product-led growth is - as a go-to-market strategy - complementing product strategies evolving around customer-centricity. However, the new laser focus on product experience allows us, or even mandates, to adjust how we manage our product. Let me explain.

We all know that understanding the customer and the value-add is crucial for the success of our product strategy. This has stayed the same with the concept of product-led growth. For more than 15 years as a Product Manager, I've gained a good understanding of what customers want and value through focus groups, individual key user interviews, community forums, and survey monkeys. Nevertheless, these methods have two major flaws:

  1. These methods don't scale well. Even for the more scalable approaches, such as online surveys and community forum feature rankings, the outcome depends on how proactive and available participants are. A study sample of proactive, extrovert folks is not necessarily representative of most end users.
  2. Any of these methods rely on the subjective opinion of those end users. The views of what is valuable might be influenced by trends, competitors' features, and things they need right at the time of giving feedback. Usually, these methods do not provide an objective view of which features represent 80% of the everyday interactions with the product and, therefore, are of the most value.

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If we want to learn about the end user’s onboarding journey, time to value, and continuous value, then the traditional research means are insufficient. The lacking scope, not extending to the daily use of the digital product, and the subjectivity of the feedback limit their value for a product-led go-to-market strategy. Only product analytics, a technique to measure the end user's interactions with the product during different phases of the product lifecycle, enables Product Managers to create a winning go-to-market strategy. The ability of product analytics to indicate which features are adopted how often and when in the product lifecycle, to visualize the UI navigation paths different user cohorts take, and to measure the retention of users over time provide crucial insights to Product Managers, R&D Leaders, Marketing Managers, Customer Success Managers, and Sales Executives.

Customer Centricity and Data-Driven Product Management


Product analytics is not only an essential enabler for a product-led strategy, but it also allows Product Managers to take customer-centricity to the next level. The objective data from product analytics enhances the understanding of the customer’s needs dramatically. Nevertheless, product analytics doesn't replace the need for focus groups or end-user interviews because of the need to learn the customer's opinion on the product's physical aspects, such as the industrial design. However, product analytics takes the guesswork out of end-user research of the digital experience and is the foundation for objective data-driven product management.

We have introduced Qt Insight, a product analytics solution for embedded device makers, recently and are inviting enterprises to the beta release pilot. Check out more here.


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