We asked Mr. Hackathon, the creator of the application Market Master AI, to explain how he managed to build a beta version of an AI-powered market research platform in a day.
Benefits of automating your market research project with AI
Market research is a complex and multi-faceted process that requires a significant investment of time to be done effectively. Manually gathering and analyzing data from multiple sources, such as industry reports, government statistics, customer surveys, and competitor analysis, can be time-consuming.
Artificial intelligence (AI) can help streamline many of the tasks involved in market research, extract more meaningful insights, and make more accurate predictions in a shorter amount of time. Here are a few examples:
- Data collection and analysis: AI can automate the process of collecting and analyzing data from various sources, such as social media, industry reports, and customer surveys, which can save time and reduce human error.
- Natural language processing: NLP can help to quickly process and analyze large amounts of unstructured data, such as survey responses and customer support inquiries, which can be difficult to process manually.
- Sentiment analysis: AI can be used to analyze customer sentiment from social media, customer feedback, and other sources, to gain insight into customer attitudes and perceptions.
- Predictive modeling: AI can be used to analyze data and make predictions about future market trends, customer behavior, and the potential success of new products or marketing strategies.
- A/B testing: AI can automate the process of A/B testing, which can help to quickly identify the most effective marketing strategies and design elements.
Why should you build AI with No Code? –Interview with Market Master AI creator
Dominic Norton, known professionally as Mr. Hackaton, is a no-code expert who teaches at universities worldwide and through social media. One of his goals is to bring No-code to rural and underprivileged areas that lack access to education or internet facilities.
By using Eden AI, his students can have an easier learning experience as his course mainly focuses on theory.
Where does your interest in No-Code and AI come from?
In many countries where Dominic works, AI is not as prevalent as it is in the western world. Places like Nigeria, Ghana, and even rural parts of the UK lack the same level of technology adoption as more developed regions, which is why he mainly works through his education technology platform, Prolithink, an entrepreneurship and digital skills education platform.
Inside rural communities, you might not even know AI tools like Eden AI. And what we've seen over the last year or so is an uptick in artificial intelligence and student interest in artificial intelligence. No-code has been democratized and students are actually building AI applications. Eden AI has been a big part of that in conjunction with Make.
Eden AI is great for beginners and for no-coders getting their feet wet. And for the developers who are in a Machine Learning or AI program, and are doing a research-focused Master’s degree or PhD, that’s where Eden AI may balance it all out. It allows them to actually build alongside their theory, which helps their exponential learning.
Why did you choose to integrate AI with No Code?
No-Code is great to monitor and test the potential of your app. Your customers can test it, which is a great way to build a relationship and find a way to get early buyers.
Dominic says it can also help you enhance your app:
I could have a list of questions that people have asked before. I could use enough AI generation tools to generate ideas for questions. And this is what Eden AI, Softer, and No-code are good for. And the first version of your app allows you to build in the right direction. This was done in no time, like in a weekend.
How does your app “Market Master AI” work?
Market Master AI was built with the help of Softer (front-end), Airtable (back-end), Make (to automate everything), and Eden AI (to connect the application and AI technology). The app was primarily designed as a tool for Market Analysts to conduct market research from 2022 to 2023. Dominic explains:
You have all these big banks and all these big institutions that bring out all these Market reports, and often as an analyst, you have to go through them. You have to remember them, and it's a very difficult and time-consuming process. And one thing that AI allows you to do well is query information and so this is how it works: you can select your report (ex: Global Economics Analyst Macro Outlook 2023).
You can type the question you want and it's going to bring back the most relevant answer. So it’s saving analysts time:
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Market Master AI application
What’s the role of Eden AI in this whole ecosystem?
Eden AI is really interesting for business customers to maximize artificial intelligence in their operations, especially where they want to do something custom. Companies don't have a no-code developer, and if they want to do text-to-speech for some reason, they don't have to be technical –they just have to know how to use Eden AI. For instance, if you’re in marketing and you want to analyze feedback, you could use sentiment analysis, and as a marketer, you don't have to bring that engineering in to do so.
This is the whole point of no-code that actually democratizes AI, especially for “citizen developers”, to allow them to be able to use AI. As AI technology increases, I'm sure Eden AI is going to increase its AI capabilities, which will allow marketers or sales teams or just different teams to be able to use artificial intelligence without the cost of an engineering team or using the capacity of their engineering team.
How to build an AI-powered market research app in a day?
As mentioned earlier, you can use natural language processing to easily explore data and find what you are looking for. Q&A and Search APIs are a good start in that respect.
What are Search and Q&A APIs?
Search API lets you conduct a semantic search across a collection of documents by using a query, such as a natural language question or statement. The documents will be ranked based on their semantic relevance to the input query and returned with a score.
Meanwhile, Question Answering API allows users to input a natural language question and receive an answer based on the information present in a specific set of documents or a knowledge base.
Question Answering API response - Eden AI
If you wish to learn more about integrating those features into your application, our team of AI experts will be pleased to help you get started with it. Book a call or simply start chatting with us on Discord😎
Quick tutorial on how to build a Q&A and Search-powered app
To achieve optimal performance, Dominic used Eden AI single API which allows him to fully leverage AI capabilities and gain access to the top AI engines through a single API.
He showcased his work by building a semantic search-based application and a Q&A-based application using No-Code and various tools such as Glide, Airtable, Make and Eden AI:
Part 1 (Semantic Search) - https://t.co/F80pFFKJ11
Part 2 (Q&A) - https://www.loom.com/share/8b7b93201f6744889001f5c7815a066c.
He also shared the details of the process on his Twitter feed:
Get started with Eden AI API
To use Q&A and Search technologies, you'll need to create an account on Eden AI for free. Then, you'll be able to get your API 🔑 directly from the homepage with free credits offered by Eden AI:
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Get your API key for FREE on Eden AI platform
Benefits of using Eden AI
Eden AI is the future of AI usage in companies: our app allows you to call multiple AI APIs.
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Multiple AI engines through a unique API
Save time and cost
We offer a unified API for all providers: simple and standard to use, with a quick switch between providers and an access to the specific features of each provider.
Easy to integrate
The JSON output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.
Customization
With Eden AI you have the possibility to integrate a third party platform: we can quickly develop connectors. To go further and customize your Semantic Search request with specific parameters, check out our documentation.
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