🤖 AI Problem Identifier

Spotting the right opportunities in a sea of options can be tough. But what if there was a tool to make it easier? Feedough's AI opportunity identifier does just that. It helps you identify real problems in your industry and convert them into a new opportunity for innovation. Instead of getting lost in endless possibilities, you can focus on the opportunities that matter most. Whether you're leading a business or seeking personal growth, this tool makes spotting your next move much easier.

What Is an AI Problem Identifier?

AI Problem Identifier is a tool that helps businesses spot challenges their target audience is facing. It uses data analysis and machine learning to help you find pain points of your target audience that you can address. By highlighting these problems, businesses can create more focused strategies—whether it’s for product development, improving services, or fine-tuning marketing. In short, a Problem Identifier helps companies understand their customers’ pain points, opening the door to growth and new opportunities.

How Does an AI Problem Identifier Work?

AI problem identifier is designed to help you pinpoint challenges or opportunities specific to your business by analysing the information you provide. Whether you're working in e-commerce, marketing, or any other field, it simplifies the process of understanding your audience's needs and the industry trends. By using AI, you can save time and get relevant insights that help you make smarter decisions. The generator works through three main stages: input, processing, and output. Let’s break it down.

Input

This is the first step where you provide the AI with the essential details it needs to start working. The quality of the output depends heavily on the accuracy and relevance of the input you provide.

Here’s what happens at the input stage:

• Industry Information: You begin by entering your industry, like “E-commerce” in this case. The AI needs to understand the specific market or field you're working in. By doing so, it narrows down the analysis to industry-specific challenges and trends. For instance, in e-commerce, the AI might focus on problems like customer experience, conversion rates, or mobile shopping trends.
• Target Audience: The next step involves defining your target audience. In the example you provided, the target audience is “mobile shoppers aged 18-35.” This helps the AI tailor its analysis to the behaviour, preferences, and needs of your audience. For example, it might look into how this age group prefers fast, mobile-friendly websites, or values quick checkout processes. The more precise you are with your audience description, the better the AI can generate relevant insights.

By giving these inputs, you are essentially guiding the AI to focus on specific areas that matter most to your business.

Processing

Once the input is provided, the AI begins the processing stage. This is where it analyses the data you entered to come up with insights or problems related to your business. The AI uses advanced algorithms to process the information and find connections between the industry, the target audience, and potential challenges.

Here’s how the AI processes the data:

• Contextual Understanding
  The AI takes the input and looks at the bigger picture. For example, if your input mentions e-commerce and mobile shoppers, it will use its vast knowledge to understand what mobile shoppers are likely to struggle with in the e-commerce space. It can analyse patterns from millions of similar cases, such as slow website load times leading to cart abandonment.
• Pattern Recognition
  AI is great at identifying patterns. It will look for common issues mobile shoppers face, such as difficulties navigating on smaller screens or slow app performance. Based on these patterns, it will start highlighting problem areas for you to focus on.
• Trend Analysis
  The AI may also pull from current trends in the e-commerce industry or mobile shopping. For example, it might detect that younger shoppers are increasingly relying on social media for shopping decisions or are more likely to make purchases via mobile apps rather than websites.

At the end of the processing stage, the AI has created a roadmap of potential issues and opportunities by connecting industry specifics with audience behaviour.

Output

Finally, the AI presents its findings in the output stage. Based on the input and processing, the output will include insights or suggestions that you can use to address specific problems or make improvements.

Here’s what the AI delivers in the output:

• Problem Identification: The AI highlights key problems that your business might face based on the information you provided. For example, if you’re in e-commerce and targeting mobile shoppers, it might identify that a slow mobile experience is a common issue for your audience, leading to higher bounce rates and lower conversions.
• Suggestions for Improvement: Along with the problems, the AI will likely offer suggestions for improvement. For instance, it may recommend optimising your website for mobile use, simplifying the checkout process, or integrating faster payment options to cater to the younger demographic who value speed and convenience.
• Tailored Insights: The output can also include insights based on your industry and audience trends. In the case of mobile shoppers, the AI might point out that offering features like Apple Pay or Google Wallet could lead to higher conversions. These insights help you understand what your audience values most and where your focus should be.

With the output in hand, you now have actionable insights that are specifically designed for your business needs. This allows you to make informed decisions on where to improve or adjust your strategies.

How to Find Your Customer's Pain Points Using AI Problem Identifier ?

Finding your customer's pain points is crucial for improving your product or service, and using an AI problem identifier can make the process easier and more efficient. By using AI, you can uncover hidden issues or challenges that your customers are facing, which might not be immediately obvious.

The AI works through a systematic process of collecting information, analysing patterns, and delivering insights that help you pinpoint exactly where your customers are struggling. Let’s break down the steps:

Step 1: Specify Your Industry or Field

The first thing you need to do is input the specific industry or field you're focusing on. This helps the AI tool understand the context in which your customers operate and the kind of problems they might be facing.

For example, if you're working in the E-commerce space, the tool will look for issues commonly faced in online shopping experiences. If you were in the fitness industry, the AI might instead focus on challenges related to customer motivation or ease of use for apps or workout programs.

Each industry has its own unique set of challenges. By specifying your field, you give the AI a direction, helping it focus on common pain points that are likely to resonate with your customer base. A general approach would miss out on these nuanced issues.

Step 2: Define Your Target Audience

Next, you’ll enter details about your target audience. This could be as specific as "Mobile shoppers aged 18-35," or "New moms in their 30s," depending on who your customers are.

Let’s say your audience is young mobile shoppers. The tool will search for issues specific to their online shopping habits, like slow mobile experiences or the lack of popular payment options like digital wallets (Apple Pay, Google Pay, etc.).

Every customer segment faces different issues. A senior shopping online may struggle with too-small text or complicated forms, while a younger audience might get frustrated by slow apps or inconvenient payment methods. The AI helps zero in on problems that your specific group of customers might actually care about, so you're not wasting time fixing issues that aren't relevant to them.

Step 3: Generate Customer Pain Points

Once you've input your industry and audience, hit the "Generate" button. The AI will analyse patterns and common issues based on the data available for your particular audience in your industry.

For example, for e-commerce mobile shoppers aged 18-35, you might get pain points like:

• Slow mobile website load times: Young shoppers, especially on mobile, expect websites to load within a few seconds. If your site takes too long, they’ll leave before making a purchase.
• Limited payment options: Gen Z and Millennials often prefer to use mobile wallets or services like PayPal. If your checkout only allows credit cards, you could be losing customers.
• Poor mobile app experience: Mobile shoppers often get frustrated if the navigation on an app is confusing or if they have to click through too many screens to find what they want.

The AI quickly identifies specific pain points based on actual user behaviour patterns and market data, saving you the time and effort of manually identifying them. It also helps you focus on problems that will actually move the needle for your business.

Step 4: Analyse the Generated Problems

Once you’ve got a list of customer pain points, it’s important to take a closer look at each one. Start by asking yourself a few key questions:

• Is this a common complaint among my customers?
• How significant is this issue? Could it be losing me customers or preventing conversions?
• How easy or difficult would it be to solve this problem?

For example, if one of the pain points is that your mobile site is slow, you can use tools like Google’s PageSpeed Insights to see just how bad the issue is and how it might be affecting your customers.

This analysis helps you prioritise which pain points need fixing urgently and which ones might be less critical.

Step 5: Prioritise the Pain Points

Not all problems are created equal. Some may require immediate action, while others can be put on the back burner. Start by ranking the pain points based on two criteria:

1. Severity: How big of an issue is this for your customers? Are people abandoning carts or leaving your site because of it?
2. Impact on your business: If you fix this problem, will it have a significant effect on your sales or customer satisfaction?

Let’s say slow mobile website load times was a pain point. Studies show that even a one-second delay can cause conversions to drop by 7%. In this case, it’s clear that fixing the issue should be a top priority because it’s costing you revenue.

On the other hand, a pain point like limited payment options might be less urgent if only a small percentage of customers have complained about it.

Step 6: Plan Solutions for Each Problem

Once you’ve prioritised the pain points, it’s time to plan out how you’re going to address them. Let’s go over a couple of common solutions that could apply to typical e-commerce problems:

• For slow load times: You might need to optimise your website by compressing images, using faster hosting, or implementing a content delivery network (CDN) to speed up the experience for mobile users.
• For limited payment options: Consider adding more payment methods like PayPal, Apple Pay, or even options for buy-now-pay-later services like Afterpay or Klarna, which are popular with younger audiences.

Each solution should have a clear action plan. Who’s responsible for implementing it? What’s the timeline? Make sure you’re realistic about what you can accomplish.

Step 7: Test and Iterate

Once you've made changes, don't assume the problem is fixed for good. It’s important to keep testing your solutions to see if they’re having the desired effect. For example, after speeding up your mobile site, you can monitor your bounce rate and conversion rate to see if they improve.

For payment options, you can track the number of transactions completed using new methods like Apple Pay or PayPal. Keep checking in on these metrics to make sure the fixes are working as expected.

Step 8: Collect Feedback

Finally, go back to your customers. Use surveys, reviews, or even direct outreach to find out if their experience has improved. Ask questions like:

• "How easy was it to shop on your mobile device?"
• "Were you satisfied with the payment options available?"

This will help you understand whether you've fully addressed their pain points or if there's still work to be done.