Should I Build It Should I Build It
10 May 2025
Career

website to tell you if a particular college and major are worth the ...

...investment long term and tells you expected jobs and salary ranges

Confidence
Engagement
Net use signal
Net buy signal

Idea type: Swamp

The market has seen several mediocre solutions that nobody loves. Unless you can offer something fundamentally different, you’ll likely struggle to stand out or make money.

Should You Build It?

Don't build it.

Your are here

You're entering a "Swamp" category, meaning there are existing solutions, but none are particularly loved or successful. With 5 similar products already identified, you'll face competition. The engagement on those similar products is low (engagement = low, n_comments = 0), indicating a lack of enthusiasm or unmet needs in the market. Since there were no positive or negative signals of use/buy, it means that no one explicitly expressed interest in using or buying similar products. Considering this, you need to REALLY figure out what will make your solution stand out and why current solutions aren't cutting it. Don't just build another mediocre product; dig deep and find a genuine unmet need or a fundamentally better approach.

Recommendations

  1. Before diving into development, invest significant time in researching why existing college/major ROI calculators haven't resonated with users. What are their pain points? What information are they missing? Understanding these shortcomings is crucial to building a truly valuable product.
  2. Instead of targeting all college students, focus on a specific demographic or field of study. For example, you could specialize in trade schools, vocational programs, or specific STEM fields. Niche focus allows you to tailor the data and provide more relevant insights.
  3. Consider building tools or APIs for existing college planning websites or guidance counselors instead of building a standalone website. Integrating your ROI data into established platforms could be a more effective distribution strategy and let them be the "face" of the platform to the students.
  4. Explore adjacent problems related to career planning, such as skill gap analysis, personalized learning paths, or mentorship matching. These areas might offer more promising opportunities for innovation and differentiation.
  5. Since similar products received very little engagement, focus your efforts on creating a very high quality data set that might stand out from alternatives. If you are able to collect real world data that others don't have, that might be a good start. As one of the similar products struggled with the location input clarity, consider that as well.
  6. Given the risks of a "Swamp" category, carefully evaluate whether this idea is the best use of your time and resources. There might be other opportunities with a higher potential for success. Think hard and be honest with yourself.

Questions

  1. What specific data points and analytical methods will you use to differentiate your ROI calculations from existing solutions, and how will you ensure the accuracy and reliability of this data?
  2. Given the low engagement with similar products, what innovative strategies will you employ to attract and retain users, and how will you measure the effectiveness of these strategies?
  3. How can you implement user feedback into the data and overall experience in a way that builds trust, value, and helps users with their decisions?

Your are here

You're entering a "Swamp" category, meaning there are existing solutions, but none are particularly loved or successful. With 5 similar products already identified, you'll face competition. The engagement on those similar products is low (engagement = low, n_comments = 0), indicating a lack of enthusiasm or unmet needs in the market. Since there were no positive or negative signals of use/buy, it means that no one explicitly expressed interest in using or buying similar products. Considering this, you need to REALLY figure out what will make your solution stand out and why current solutions aren't cutting it. Don't just build another mediocre product; dig deep and find a genuine unmet need or a fundamentally better approach.

Recommendations

  1. Before diving into development, invest significant time in researching why existing college/major ROI calculators haven't resonated with users. What are their pain points? What information are they missing? Understanding these shortcomings is crucial to building a truly valuable product.
  2. Instead of targeting all college students, focus on a specific demographic or field of study. For example, you could specialize in trade schools, vocational programs, or specific STEM fields. Niche focus allows you to tailor the data and provide more relevant insights.
  3. Consider building tools or APIs for existing college planning websites or guidance counselors instead of building a standalone website. Integrating your ROI data into established platforms could be a more effective distribution strategy and let them be the "face" of the platform to the students.
  4. Explore adjacent problems related to career planning, such as skill gap analysis, personalized learning paths, or mentorship matching. These areas might offer more promising opportunities for innovation and differentiation.
  5. Since similar products received very little engagement, focus your efforts on creating a very high quality data set that might stand out from alternatives. If you are able to collect real world data that others don't have, that might be a good start. As one of the similar products struggled with the location input clarity, consider that as well.
  6. Given the risks of a "Swamp" category, carefully evaluate whether this idea is the best use of your time and resources. There might be other opportunities with a higher potential for success. Think hard and be honest with yourself.

Questions

  1. What specific data points and analytical methods will you use to differentiate your ROI calculations from existing solutions, and how will you ensure the accuracy and reliability of this data?
  2. Given the low engagement with similar products, what innovative strategies will you employ to attract and retain users, and how will you measure the effectiveness of these strategies?
  3. How can you implement user feedback into the data and overall experience in a way that builds trust, value, and helps users with their decisions?

  • Confidence: Medium
    • Number of similar products: 5
  • Engagement: Low
    • Average number of comments: 0
  • Net use signal: 0.0%
    • Positive use signal: 0.0%
    • Negative use signal: 0.0%
  • Net buy signal: 0.0%
    • Positive buy signal: 0.0%
    • Negative buy signal: 0.0%

This chart summarizes all the similar products we found for your idea in a single plot.

The x-axis represents the overall feedback each product received. This is calculated from the net use and buy signals that were expressed in the comments. The maximum is +1, which means all comments (across all similar products) were positive, expressed a willingness to use & buy said product. The minimum is -1 and it means the exact opposite.

The y-axis captures the strength of the signal, i.e. how many people commented and how does this rank against other products in this category. The maximum is +1, which means these products were the most liked, upvoted and talked about launches recently. The minimum is 0, meaning zero engagement or feedback was received.

The sizes of the product dots are determined by the relevance to your idea, where 10 is the maximum.

Your idea is the big blueish dot, which should lie somewhere in the polygon defined by these products. It can be off-center because we use custom weighting to summarize these metrics.

Similar products

Relevance

No BS site to view government salary data

09 Oct 2024 Hiring

I built a simple site that uses public data from the U.S. Bureau of Labor Statistics to better visualize the salary data. The only bad thing is that some states dont have data for specific occupations, and some salary data is just marked as being >$229,000 instead of the exact number.

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