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Conversational user surveys powered by AI. Automatically ask deep follow-up questions based on user's feedback. Stop settling for shallow insights, sign up for free.

How RhetorAI can help you:

Automatically conducts in-depth customer interviews using AI.
Generates valuable insights from customer feedback effortlessly.
Offers multilingual support to cater to global audiences.
Provides flexibility in conversation lengths to match user preferences.
Allows for easy website integration for seamless user experience.
Sends instant email notifications for new user responses.

Why choose RhetorAI: Key features

24/7 AI-powered product researcher at your service.
Multilingual capabilities for diverse user engagement.
Customizable AI to suit your brand's voice.
Efficient insights generation for informed decision-making.
Email alerts to keep you updated on customer feedback.

Who should choose RhetorAI:

Startups and small businesses seeking to understand their customers better.
Research teams looking for in-depth user feedback.
Product managers aiming for enhanced product development.
Marketers interested in genuine customer insights for strategy refinement.

About RhetorAI

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November 2023

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Build Your Own AI Chatbot in Minutes: A Step-by-Step Guide

Providing instant and personalized customer support is crucial for businesses to stay competitive. Creating an AI chatbot for your website is an effective way to enhance customer engagement, improve lead generation, and streamline support processes. With Denser AI, you can set up a custom chatbot in minutes, even without extensive technical expertise. The video below from AI Andy will walk you through the process of setting up, customizing, and integrating a chatbot to transform customer support and lead generation on your website. One of the standout features of Denser AI is its user-friendly interface, designed to make chatbot creation a breeze. The intuitive setup process allows you to create a fully functional chatbot quickly, without the need for complex coding or technical skills. This means that businesses of all sizes can leverage the power of AI chatbots, regardless of their technical background. To get started, simply sign up on the Denser AI platform using your preferred method, such as a username and password or your social media accounts. Once you've created an account, you can immediately begin building your chatbot by inputting your website URL or uploading relevant files to train the AI. Denser AI's intelligent algorithms will analyze the provided data and generate a chatbot tailored to your website's content and user needs. Denser AI understands that every business is unique, which is why it offers a wide range of customization options to ensure your chatbot seamlessly integrates with your brand identity and website design. You have the flexibility to: Denser AI prioritizes ease of integration, ensuring that you can effortlessly incorporate the chatbot into your existing website, regardless of the platform you use. Whether you have a WordPress site, a Shopify store, or a custom-built website, Denser AI provides straightforward integration options. For WordPress users, the process is as simple as installing the WP Headers and Footers plugin and adding the provided code snippet. Shopify store owners can easily embed the chatbot using the platform's built-in features. If you have a custom website, Denser AI offers clear instructions and code snippets to seamlessly integrate the chatbot into your site's structure. One of the key benefits of implementing an AI chatbot is its ability to capture leads directly through user interactions. Denser AI's chatbot comes equipped with powerful lead generation features, allowing you to gather valuable information from your website visitors. By setting up fields for name, email, and additional custom fields relevant to your business, you can collect targeted data that helps you better understand your audience and nurture potential customers. The chatbot's intelligent algorithms analyze user inputs and provide personalized responses, guiding visitors through the lead capture process in a natural and engaging manner. This approach not only enhances the user experience but also increases the likelihood of visitors providing their information, ultimately boosting your lead generation efforts. To ensure your chatbot delivers an exceptional user experience and achieves your desired outcomes, thorough testing is essential. Denser AI provides a comprehensive testing environment where you can verify the chatbot's functionality, responsiveness, and accuracy. During the testing phase, you can engage with the chatbot as a user would, asking questions and evaluating its responses. This allows you to assess whether the chatbot effectively answers queries based on the provided data and captures leads accurately. Additionally, testing enables you to identify any potential improvements or adjustments needed to optimize the chatbot's performance. By dedicating time to thorough testing, you can confidently deploy your chatbot, knowing that it will deliver a seamless and valuable experience to your website visitors. Creating an AI chatbot for your website is no longer a daunting task, thanks to the user-friendly and powerful capabilities of Denser AI. By following the simple steps outlined in this guide, you can have a fully functional chatbot up and running on your website in minutes, without the need for extensive technical expertise. With Denser AI's extensive customization options, seamless integration across platforms, and robust lead generation features, you can transform customer support and lead generation on your website. By leveraging the power of AI chatbots, you can provide instant, personalized assistance to your visitors, gather valuable data, and streamline your business processes. Don't miss out on the opportunity to enhance your website's user experience and drive business growth. Sign up for Denser AI today and unlock the potential of AI chatbots for your business.

Geeky Gadgets

Wed, 3 Jul, 10:05 AM UTC

How to use Perplexity AI for research and data analysis

If you would like to improve your research and data analytical skills, you might be interested in learning more about Perplexity AI. An artificial intelligent (AI) research tool that offers an alternative to traditional search engines like Google and chat-based editors like OpenAI's ChatGPT. It aggregates information from various sources across the web to provide comprehensive answers to user queries. This tool is particularly useful for detailed research, academic writing, and problem-solving, offering features such as source verification, language model selection, and the ability to generate and organize content. Ever found yourself drowning in a sea of tabs, each one a different source of information for your research project? It's a common problem that many of us face. But what if there was a tool that could aggregate all that information and present it in a comprehensive, easy-to-digest format? Meet Perplexity AI, your new best friend in the world of research. One of the key strengths of Perplexity AI is its ability to pull information from multiple sources, including the web, YouTube, and Reddit, when you input a query. This allows the tool to deliver detailed, well-sourced answers that go beyond the capabilities of traditional search engines. Additionally, Perplexity AI allows you to ask follow-up questions, allowing you to dive deeper into a topic and obtain more nuanced insights. Perplexity AI offers a range of features that set it apart from other research tools: Here are a selection of other articles from our extensive library of content you may find of interest on the subject of Perplexity and alternative to Google Search : Perplexity AI is particularly beneficial for academic research, as it can search reliable academic sources for papers and studies, providing you with credible information to support your work. It is also valuable for problem-solving, offering step-by-step solutions to technical issues, making it a useful resource for both students and professionals. In terms of content creation, Perplexity AI can help you generate structured content and pages that you can easily share with others. This is especially useful for bloggers, writers, and content creators who need to organize their work efficiently and effectively. Perplexity AI offers several advanced tools that further enhance its capabilities: Perplexity AI offers a user-friendly interface that simplifies the research process by summarizing information and allowing you to ask questions and receive detailed answers quickly. This makes it easier to gather and understand complex information, enhancing your productivity and efficiency. However, it is important to note that while Perplexity AI offers many advanced features, its image generation capabilities are pretty much non-existent when compared to OpenAI's DallE 3 and Midjourney. Additionally, some features, such as advanced image generation, may require a Pro version, which could be a limitation for some users who are short on cash. Perplexity AI is a robust and versatile tool for research and content creation, offering comprehensive answers, source verification, and a range of advanced features. Its ability to aggregate information from diverse sources and provide well-sourced, detailed responses makes it particularly useful for students, researchers, and content creators looking for a streamlined way to gather and organize information. With its user-friendly interface and array of capabilities, Perplexity AI is a valuable resource for anyone navigating the complexities of the digital age.

Geeky Gadgets

Sat, 13 Jul, 6:00 AM UTC

Council Post: The Evolving Role Of Technology In Market Research

Recent advancements in generative AI and machine learning are changing the ways data analytics and market research are conducted. Practitioners and consumers of market insights can leverage new algorithms to develop deeper insights faster than ever. But these technologies are not immediate problem-solvers. Firms must understand the best marketing applications of generative AI to harness their full potential -- responsibly freeing practitioners from repetitive tasks and enabling them to focus on higher level tasks. How is AI affecting market research? Traditional analytics has historically been used to perform statistical analysis on large collections of data. While helpful, it is primarily retrospective in nature. These data points -- which rely on static models -- lack the capability to generate new insights or help predict future changes. In a dynamic economy, focusing on past performance may be a disadvantage. Generative AI models such as ChatGPT are trained on massive databases of information but those databases are not infinite, so chat models aren't always responsive to the context you want them to work in. This leads to "hallucinations," which produce errors. The best way to secure the benefits of AI while eliminating risks is to work with experts who maintain your system. Humans are still best at identifying bias, ethics and privacy issues. For teams that put too much trust in tools built on external data, their successes are at constant risk of mistakes due to lack of human oversight. Instead of trusting their sensitive data to public databases, many teams opt to build their own AI for research purposes. An internal chatbot can be specifically trained on your data, eliminating bias and most hallucinations from the system. Plus, training on internal data enables you to ask questions like, "What was the competition like between these two major soda brands between 1990 and 1995, and which marketing campaigns affected the results the most?" These types of questions provide powerful insights that could not be derived from a public AI. Most businesses know they want to invest in AI for some of their data analysis. A more productive question is whether they want to build their own product or partner with an AI company. To understand the best decision for your firm, consider how these traditional challenges in market research will change with new technology developments. One of the most important tasks in market research is data cleaning. As analysts, we must ensure our data is based on valid responses. This has always been the case with data analytics -- you get out what you put in -- but is even more critical in the age of artificial intelligence. If your firm creates and interprets data from a large number of surveys, you already know this is an arduous task when performed manually. As a result, many firms are tempted to outsource all of their data cleaning to an AI solution. While this is a great application of AI, excessive trust in algorithms risks missing mistakes in data which can result in exponentially worse errors. Many firms prefer working with companies that emphasize high quality data collection to mitigate this risk. They seek partnerships with companies that specialize in using AI to identify large blocks of text for efficient human screening. This saves a lot of time in the process of data cleaning while upholding the importance of human insights. An ideal partner will have a deep understanding of how generative models should (and should not) be used for data cleaning. If you are approaching the development of your own AI product, this should be considered with your internal team. Do you have the capacity to maintain a significant level of focus on data cleaning? If not, a partnership with the right firm may be in your best interest. Survey insights have traditionally been limited by quantitative analysis. For example, in a standard survey for a banking service, you may ask participants to rate the service on a scale of one through 10. But what do these data points tell you about your business? More often than not, firms must arrange follow-up qualitative interviews. This deeper dive with respondents yields meaningful insights at a steep cost, both of time and money. Instead, with a properly trained AI model, you can design your survey to include interactive elements that prompt qualitative responses. For example, if a respondent gives a score of 90%, which we know falls at the high end of the Net Promoter Score, a properly trained chat feature can ask a follow-up question and probe further if needed, diving deeper into what an individual customer likes and dislikes about your service. You may find that loyal customers have problems with your company, allowing you to revisit your strategy in a more proactive manner. To set this up properly, you need to either partner with a company who has expertise in training AI models or have the capability to hire experts for your team as required. Data cleaning is even more important when using surveys with qualitative elements. This further emphasizes the importance of your dedication to maintaining data quality. If you plan to include qualitative chat elements in your otherwise quantitative survey, it is important to work with experts that understand how to use machine learning with very large data sets. This skillset extends far beyond expertise in chatbot functionality. If you want AI to perform both data cleaning and qualitative functionality in your customer surveys, you may want to partner with a market research company with expertise in artificial intelligence. The specialized knowledge required is often too much for an internal team to assume. Plus, working with a trusted provider helps mitigate risks -- and liabilities -- of working with these new and powerful technologies. Forbes Business Council is the foremost growth and networking organization for business owners and leaders. Do I qualify?

Forbes

Wed, 17 Jul, 8:04 PM UTC

How entrepreneurs can use AI - Fast Company

Within the specific prompts, Friend says you can ask it to emulate a persona, ask it to cite valid sources and tell it to keep evolving with the new inputs you enter. For her, leaning on AI frees up time for her to then commit to client work. The whole process "still requires my brain," says Friend, as she still needs to work with the output and add her human touch, but it helps her run her business more efficiently. Tomer Pensenzon, the Head of Marketing at Unleash is based in Tel Aviv, Israel and says "AI will take my job -- just when I'm trying to sleep!" For him, instead of trying to keep impossible hours across time zones, he has created and trained a Slack chatbot that answers questions solely based on his documents and company's data named 'Mini-Tomer.' Using the company's software he says "it answers 80% of the questions in my 'Ask-Tomer' channel while I'm sleeping." He says the main value would be "not in creating information, it will be making it accessible," and it's important that each company customize it. What does that look like for someone else? Tomer offered that this would apply to a marketer like me with my weekly podcast called The Exit Interview with Kim Rittberg. The podcast helps self-employed folks succeed in work and life, offering tips on business building, marketing and work-life balance, and I have a blog post about the benefits of the show. Timer says if someone asked me a question about my podcast, I could configure the AI to answer that. Specifically, it could review blog posts and generate the answer based on my content. Dave Anderson, Head of Product Marketing at Contentsquare, a digital experience analytics platform, uses AI to inform him "of market trends, and positioning" he should consider to market their analytical program. So basically he uses AI to understand what customers want out of AI. But under the 'non-obvious' ways he uses AI, he says that during his keynote presentations, he often makes comical parody songs about the analytics industry. He uses ChatGPT to get ideas, recommending a song by someone like Taylor Swift or Sting. "It never gets the lyrics perfectly, but it provides inspiration." Whether you're looking to become the next Weird Al at your company, speed up your operations, and whether you're ready to dip your toe in or jump off the high diving board,

Fast Company

Thu, 1 Aug, 2:15 PM UTC

Yellow.ai Launches Analyze To Help Enterprises Close Gaps In Customer Service Strategies

Analyze provides comprehensive metrics that enhance containment opportunities and drive more effective automation: Yellow.ai cofounder Customer service automation startup yellow.ai has rolled out a solution to improve bot interactions with in-depth conversational insights and advanced self-learning capabilities. Built on an in-house LLM model, Analyze reduces ticket volume by 30% and boosts containment rates by 10, the company said in a statement. Traditional automation platforms provide limited insights, focusing only on basic metrics like user numbers or session times. This gap leaves businesses lacking a comprehensive understanding of chatbot interaction quality. According to a recent Yellow.ai survey, 54.5% of customer service professionals seek to enhance their data analysis capabilities through AI adoption. They are turning to AI-first solutions to gain comprehensive insights into bot effectiveness, user satisfaction, conversation topics, and opportunities for improvement in bot interactions. Addressing this demand, Yellow.ai's Analyze not only delivers detailed insights but also uses this information to continuously improve the bot's ability to handle a broader range of customer queries without human intervention, the statement added. "With the launch of Analyze, we aim to help enterprises close gaps in their customer service strategies. Analyze provides comprehensive metrics that enhance containment opportunities and drive more effective automation," Raghu Ravinutala, CEO & cofounder of Yellow.ai, said. Analyze enhances customer support through four key features. Its self-learning loopback technology automates and improves bot performance by feeding escalated customer queries back into the system, generating knowledge base articles for future use. It provides strategic insights for topic clustering, allowing customer service teams to explore AI-generated clusters with insights into customer sentiments, knowledge base improvements, and conversation opportunities. In addition, conversation analysis offers detailed reports on resolution quality, enabling teams to assess various metrics like containment rate and conversation share instantly. Finally, sentiment analysis uses deep learning to categorise conversations, providing reliable insights into user satisfaction and resolution quality, surpassing traditional feedback methods. Founded in 2016, Yellow.ai serves 1,100+ enterprises in 85 countries, including Pelago (part of Singapore Airlines), Waste Connections, Sony, Domino's, Hyundai, Volkswagen, Decathlon, Randstad and the Lulu Group International, among others. It offers products across 35 channels (text and voice platforms like mobile, social media, messaging, web, voicebots and more) and supports 135 languages. It also claims to automate 16 Bn+ platform conversations annually. Yellow.ai claims to have achieved 5x rise in global revenue in the past three years and built a team of 650+, Inc42 reported earlier. It claimed $30-40 Mn in annual recurring revenue (ARR) in FY24 (February 1, 2023-January 31, 2024), with India accounting for 30-40% of its business. The global conversational AI market, widely adopted by enterprises for its efficiency and cost-saving benefits, is growing rapidly, expanding from $10.7 Bn in 2023 to a projected $29.8 Bn by 2028, with a compound annual growth rate (CAGR) of 22.6%.

Inc42 Media

Tue, 13 Aug, 8:00 AM UTC

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