Speicher elektrisiert / Electrified Speicher
This series analyses electric mobility not from a marketing or pure technology angle, but as a real-world product system: How trust is built. How decisions are actually made. How long-term adoption emerges beyond specifications and branding.
The analytical basis is the experience of building one of Europe’s largest independent Škoda EV communities.
The customer-centric, business-oriented view of my product ‚Speicher elektrisiert‘
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Start with Why: How and why Speicher elektrisiert came about
This article explains the origin, purpose and rationale behind Speicher elektrisiert. It describes the market situation at the beginning of the 2020s, the role of the MEB platform and the functional gap that the project…
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How the Speicher elektrisiert business model is designed
This article describes how Speicher elektrisiert works today. It shows how the project functions as a knowledge system and how the individual components of the Business Model Canvas and Lean Canvas interlock.
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The two central customer segments of Speicher are electrified
This article describes the two user profiles or customer segments for which Speicher electrifies its content: Technical Analysts and Joyful Explorers. The Value Proposition Canvas serves as a tool to precisely capture their jobs, pains,…
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Why the e-guide was created and how it works
I will show you how I use the Value Proposition Canvas to design my content, using my e-guide as an example.
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Success Story: E-Guide for ENYAQ and ELROQ
The success story demonstrates the measurable impact of the eight-part e-guide, with over 650,000 views, an exceptionally high like ratio and strong algorithmic relevance.
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Operating in a Niche: Strengths, Limits, Dependencies
This article explains why the niche made the project strong, but also what structural constraints and dependencies limited its further development.
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Innovation Excursus: Desirable, Feasible, Viable
This section places Speicher elektrisiert within a well-established innovation framework. The analysis explains why the model worked, where it reached structural limits, and why further development was not only reasonable but necessary.
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Ending at the Peak
Ending a model while it is performing well may seem counterintuitive. Yet this is precisely where the difference lies between something that fades out and something that evolves.