Should I Build It Should I Build It
06 Aug 2025
Artificial Intelligence Delivery E-Commerce

An AI powered shipping application, which auto-selects the cheapest ...

...shipper based on time/date you need the package to be recieved by, this saves the user significant time in checking multiple shippers but also overpaying for shipping which can cost a business thousands per year. The app would then purchase the shipping/provide a shipping print out the can attach to the parcel to then be sent or collected by the shipper. The app would contain rich reporting as well as tracking information on every parcel being sent, this would help find lost packages.

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 AI-powered shipping application falls into a crowded space where many have tried to streamline the shipping process, but few have truly broken through. Our analysis suggests your idea sits in the 'Swamp' category, meaning there are several existing solutions, but none are particularly loved. With only 3 similar products found, the confidence in this categorization is medium, suggesting there's room for differentiation, but the low engagement (average of 1 comment per product) indicates lukewarm interest. The lack of clear 'use' or 'buy' signals further underscores this uncertainty. To succeed, you'll need a truly disruptive approach or a highly targeted niche to avoid getting lost in the shuffle.

Recommendations

  1. First, deeply research why current shipping solutions aren't resonating with users. Identify their pain points and unmet needs. What are people complaining about? Where are the bottlenecks? Do thorough competitor analysis to really understand the landscape.
  2. Given the existing options, consider focusing on a specific niche or industry underserved by current solutions. For example, perishable goods, oversized items, or specific geographical regions. Specializing allows you to tailor your AI and reporting features to their unique requirements, giving you a competitive edge.
  3. Before building a standalone app, explore the possibility of creating tools or integrations for existing shipping providers or e-commerce platforms. This allows you to validate your core technology and features without investing in a full-fledged application and user acquisition.
  4. Analyze adjacent problems in the shipping and logistics space. Could you focus on optimizing warehouse management, improving last-mile delivery, or reducing shipping-related fraud? There might be more promising and less crowded opportunities nearby.
  5. Explore the potential of leveraging blockchain technology for increased transparency and security in shipping. This could differentiate your solution and build trust with users concerned about lost or damaged packages.
  6. As 'Bigship' had positive user feedback, analyze their specific features and target market. Identify areas where you can offer a superior or more comprehensive solution. Study their approach to customer acquisition and retention.
  7. Given the absence of strong 'buy' signals in similar products, focus on demonstrating clear ROI for businesses. Quantify the potential savings in shipping costs and time, and showcase how your reporting features can help them optimize their supply chain.
  8. Prioritize building a strong MVP with core features and gather user feedback early and often. Iterate based on their needs and pain points. Continuous improvement is key to overcoming the challenges in this space.

Questions

  1. What specific, measurable pain points are businesses experiencing with current shipping solutions that your AI can uniquely address, and how can you validate these pain points before building the entire application?
  2. Considering the 'Swamp' category and lukewarm engagement, what innovative features or unique value proposition can you offer that will truly differentiate your solution and attract users away from existing options?
  3. How will you acquire initial users and build a sustainable customer base in a competitive market, and what marketing strategies will you employ to showcase the ROI of your AI-powered shipping solution?

Your are here

Your AI-powered shipping application falls into a crowded space where many have tried to streamline the shipping process, but few have truly broken through. Our analysis suggests your idea sits in the 'Swamp' category, meaning there are several existing solutions, but none are particularly loved. With only 3 similar products found, the confidence in this categorization is medium, suggesting there's room for differentiation, but the low engagement (average of 1 comment per product) indicates lukewarm interest. The lack of clear 'use' or 'buy' signals further underscores this uncertainty. To succeed, you'll need a truly disruptive approach or a highly targeted niche to avoid getting lost in the shuffle.

Recommendations

  1. First, deeply research why current shipping solutions aren't resonating with users. Identify their pain points and unmet needs. What are people complaining about? Where are the bottlenecks? Do thorough competitor analysis to really understand the landscape.
  2. Given the existing options, consider focusing on a specific niche or industry underserved by current solutions. For example, perishable goods, oversized items, or specific geographical regions. Specializing allows you to tailor your AI and reporting features to their unique requirements, giving you a competitive edge.
  3. Before building a standalone app, explore the possibility of creating tools or integrations for existing shipping providers or e-commerce platforms. This allows you to validate your core technology and features without investing in a full-fledged application and user acquisition.
  4. Analyze adjacent problems in the shipping and logistics space. Could you focus on optimizing warehouse management, improving last-mile delivery, or reducing shipping-related fraud? There might be more promising and less crowded opportunities nearby.
  5. Explore the potential of leveraging blockchain technology for increased transparency and security in shipping. This could differentiate your solution and build trust with users concerned about lost or damaged packages.
  6. As 'Bigship' had positive user feedback, analyze their specific features and target market. Identify areas where you can offer a superior or more comprehensive solution. Study their approach to customer acquisition and retention.
  7. Given the absence of strong 'buy' signals in similar products, focus on demonstrating clear ROI for businesses. Quantify the potential savings in shipping costs and time, and showcase how your reporting features can help them optimize their supply chain.
  8. Prioritize building a strong MVP with core features and gather user feedback early and often. Iterate based on their needs and pain points. Continuous improvement is key to overcoming the challenges in this space.

Questions

  1. What specific, measurable pain points are businesses experiencing with current shipping solutions that your AI can uniquely address, and how can you validate these pain points before building the entire application?
  2. Considering the 'Swamp' category and lukewarm engagement, what innovative features or unique value proposition can you offer that will truly differentiate your solution and attract users away from existing options?
  3. How will you acquire initial users and build a sustainable customer base in a competitive market, and what marketing strategies will you employ to showcase the ROI of your AI-powered shipping solution?

  • Confidence: Medium
    • Number of similar products: 3
  • Engagement: Low
    • Average number of comments: 1
  • 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

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