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👀 Things Worth Checking Out
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💡 Opportunity #1 - AI Web Analytics
🗂 Overview:
For the longest time, Google Analytics was the standard analytics tool for most websites, pretty much everyone used it. But over time, as privacy has become a bigger concern and changes to GA have alienated some of its user base, new options are emerging.
Now that AI is abundantly available it has become relatively simple to combine website analytics tools with AI capabilities not only for tracking but also for spotting & predicting trends, performance commentary, custom reports and so on.
Creating a tool specifically for certain areas (for example Ecom, Paid Ads Analysis, SEO, Agencies, etc) would add immense value to a lot of brands.
This report by Gartner reckons that by 2025, context-enriched analysis and AI will revolutionize data analytics by replacing over 60% of traditional models.
The web analytics market was valued at approximately $3.01 billion in 2020, with projections to reach around $7.05 billion by 2027.
⭐️ Examples:
PaveAI is an AI tool that transforms Google Analytics data into actionable insights.
Glassbox markets itself as a “digital experience tool” that uses AI for analytics and for a feature called “Voice of the Silent” which uses AI to get customer feedback without surveys.
Simple Analytics are a popular alternative to GA and has a Chat with AI feature that helps simplify your data.
Optimizely uses AI for A/B testing and personalization to enhance user experiences.
Motion is a creative analytics tool for people running paid ads on Meta, TikTok and so on. They don’t currently utilise AI but if you could build AI on top of this it could crush.
👎 Problems:
Data Overload: Too much raw data with insufficient insights, making it hard to focus on what's important. AI can automate the analysis process, highlighting important insights without human intervention, thus handling data overload efficiently.
Lack of Real-Time Data: Delayed data updates hinder timely decision-making. AI enables real-time data processing, offering up-to-the-minute insights for timely decision-making.
Complexity in Data Integration: Challenges in integrating data from various sources for a unified view. AI techniques can integrate and analyze data from multiple sources, providing a comprehensive view.
Accuracy Issues: Potential inaccuracies in data collection and analysis. AI algorithms improve over time, learning to filter out noise and reduce inaccuracies in data analysis.
Limited Predictive Capabilities: Traditional analytics tools focus more on historical data, with limited predictive functions. AI can identify patterns and predict future trends, moving beyond historical data analysis.
Poor Personalization: Struggle to use data effectively for personalized user experiences. I use behaviour data to tailor experiences to individual user preferences, enhancing personalization.
User Privacy Concerns: Increasing regulations and user concerns about privacy complicate data collection. AI models can be designed to respect user privacy, using techniques like federated learning to analyze data without compromising privacy.
Dependency on Expert Analysis: Requires specialized skills to interpret data, creating a bottleneck. AI tools can present data in more accessible ways, reducing the need for expert analysis.
Static Reporting: Reports are often static and not interactive, limiting deeper exploration of data. AI enables the creation of interactive, real-time dashboards for deeper data exploration.
🧐 Opportunities:
SEO: Answer the Public meets SEMRush meets Hypotenuse meets Search Console. You wouldn’t need to take all the features, just some core features that work together to improve workflow.
Paid Social: Like Motion for paid creative analysis but also recommends creative based on trends and competition spying (like Foreplay but automatically) and helps with conversion tracking like Triple Whale.
Google Analytics Add-Ons: Similar to PaveAI but for specific solutions or sectors. You could also try creating add-ons for Adobe Analytics, Google Sheets or Supermetrics.
White-Label Analytics: Create a tool that agencies can pay to license and brand as their own to upsell to clients. Altum code has 66Analytics which is a basic white-label website analytics tool. You could create one with AI features.
🛠 How to Build:
Market research: Analyze the current landscape of website analytics to identify gaps and opportunities where AI can add value.
Determine your niche: (see above or find your own).
Determine features and benefits: How is your tool different from existing tools and how does it improve your customer’s workflow?
Develop an MVP: Build an MVP (Minimum Viable Product) to demonstrate your solution’s capabilities. You can use white-label tools like 66Analytics and basic Chatgpt API functions.
Refine your product: Use feedback from early adopters to refine your product and add features that meet market needs.
Compliance and Privacy: Ensure your product complies with data protection regulations like GDPR and CCPA.
🚀 How to Grow:
Content Marketing: Create valuable content related to website analytics and AI to attract and educate your target audience.
SEO and SEM: Optimize your website for search engines to increase visibility for those searching for AI analytics solutions.
Social Media Marketing: Leverage platforms like LinkedIn, Twitter, and Reddit to engage with the tech and marketing communities.
Influencer Partnerships: Collaborate with influencers and thought leaders in the tech and digital marketing spaces to gain credibility and exposure.
Webinars and Workshops: Host educational webinars and workshops to demonstrate the value of your AI analytics tool and attract potential customers.
Referral Programs: Encourage users to refer others by offering incentives, enhancing organic growth.
Email Marketing: Use targeted email campaigns to nurture leads and keep your audience engaged with updates and insights.
Networking and Events: Attend tech meetups, conferences, and industry events to network with potential clients and partners.
Customer Success Stories: Showcase success stories and case studies from early users to illustrate the impact of your solution.
Free Trials or Demos: Offer free trials or demos to allow potential customers to experience the benefits of your AI analytics tool firsthand.
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🔒 Opportunity #2 - No Code SaaS Services
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🗂 Overview:
⭐️ Examples:
👎 Problems:
🧐 Opportunities:
🛠 How to Build
🚀 How to Grow:
👍 Tips:
🔒 Opportunity #3 - Helping ADHD Symptoms
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