Should I Build It Should I Build It
12 Apr 2025
SaaS Analytics Developer Tools

A tool to track user behavior in SaaS apps and provide actionable ...

...insights, including user health scores and feature adoption.

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

Your idea for a tool to track user behavior in SaaS apps and provide actionable insights, including user health scores and feature adoption, falls into a crowded category. Our analysis identifies it as a "Swamp"-type idea, meaning several similar solutions already exist, but haven't found widespread success. With 8 similar products already identified, competition is significant. Unfortunately, engagement with these existing products is low, suggesting that users are not particularly excited about the current offerings. Given this context, entering this market directly would be challenging without a truly disruptive approach. The current landscape suggests that you should proceed with caution or consider alternative strategies.

Recommendations

  1. First, dive deep into why existing SaaS user behavior tracking solutions haven't achieved substantial traction. Understand their shortcomings, user complaints, and areas where they fail to meet user needs. This research will be critical in identifying potential gaps in the market that your tool could uniquely address. The fact that similar products have low engagement shows that there might be something fundamentally wrong with the approach, so try to see it from a different angle and identify the core problem that needs solving, not just the symptoms.
  2. If you remain committed to this idea, identify a narrowly defined niche or specific group of SaaS users whose needs are not adequately met by existing solutions. Focus on a vertical or a particular user persona with unique requirements. This targeted approach will allow you to tailor your product and marketing efforts, increasing your chances of standing out in a crowded market.
  3. Instead of directly competing with established SaaS analytics tools, explore the possibility of building complementary tools or integrations for these existing providers. This approach could involve developing plugins, extensions, or add-ons that enhance the functionality of existing platforms, offering value without directly challenging them.
  4. Given the challenges and competition in the existing market, be prepared to pivot or abandon this idea if your initial research and testing do not yield positive results. It's crucial to remain objective and avoid falling into the sunk cost fallacy. Saving your energy for a better opportunity may be the most prudent course of action.

Questions

  1. What are the top 3 reasons why existing SaaS user behavior tracking tools have failed to gain widespread adoption, and how can your solution address these shortcomings in a fundamentally different way?
  2. What specific niche or vertical within the SaaS market is most underserved by current analytics solutions, and what unique value proposition can you offer to this target audience?
  3. How can you leverage the insights gained from user behavior tracking to provide proactive recommendations or automated interventions that directly improve user outcomes and drive greater SaaS adoption?

Your are here

Your idea for a tool to track user behavior in SaaS apps and provide actionable insights, including user health scores and feature adoption, falls into a crowded category. Our analysis identifies it as a "Swamp"-type idea, meaning several similar solutions already exist, but haven't found widespread success. With 8 similar products already identified, competition is significant. Unfortunately, engagement with these existing products is low, suggesting that users are not particularly excited about the current offerings. Given this context, entering this market directly would be challenging without a truly disruptive approach. The current landscape suggests that you should proceed with caution or consider alternative strategies.

Recommendations

  1. First, dive deep into why existing SaaS user behavior tracking solutions haven't achieved substantial traction. Understand their shortcomings, user complaints, and areas where they fail to meet user needs. This research will be critical in identifying potential gaps in the market that your tool could uniquely address. The fact that similar products have low engagement shows that there might be something fundamentally wrong with the approach, so try to see it from a different angle and identify the core problem that needs solving, not just the symptoms.
  2. If you remain committed to this idea, identify a narrowly defined niche or specific group of SaaS users whose needs are not adequately met by existing solutions. Focus on a vertical or a particular user persona with unique requirements. This targeted approach will allow you to tailor your product and marketing efforts, increasing your chances of standing out in a crowded market.
  3. Instead of directly competing with established SaaS analytics tools, explore the possibility of building complementary tools or integrations for these existing providers. This approach could involve developing plugins, extensions, or add-ons that enhance the functionality of existing platforms, offering value without directly challenging them.
  4. Given the challenges and competition in the existing market, be prepared to pivot or abandon this idea if your initial research and testing do not yield positive results. It's crucial to remain objective and avoid falling into the sunk cost fallacy. Saving your energy for a better opportunity may be the most prudent course of action.

Questions

  1. What are the top 3 reasons why existing SaaS user behavior tracking tools have failed to gain widespread adoption, and how can your solution address these shortcomings in a fundamentally different way?
  2. What specific niche or vertical within the SaaS market is most underserved by current analytics solutions, and what unique value proposition can you offer to this target audience?
  3. How can you leverage the insights gained from user behavior tracking to provide proactive recommendations or automated interventions that directly improve user outcomes and drive greater SaaS adoption?

  • Confidence: High
    • Number of similar products: 8
  • 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.

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