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How to Use WhatsApp Broadcasts and AI for Better ROI.
In the digital marketing landscape, WhatsApp Broadcasts have emerged as a modern-day equivalent of flyers, combining efficiency with precision targeting. The integration of Artificial Intelligence (AI) further amplifies its potential, offering smarter ways to connect with and engage audiences. With a staggering 98% open rates and 35% click rates, leveraging WhatsApp Broadcasts with AI can significantly boost your Return on Investment (ROI). This guide delves into strategies for building a robust broadcast list and utilizing AI to maximize the impact of your WhatsApp marketing campaign.
Building a WhatsApp Broadcast List with AI
In the world of digital marketing, WhatsApp Broadcasts are like the modern-day equivalent of flyers. They offer a combination of efficiency and precision targeting that can help businesses reach their audiences in a whole new way. But what if I told you that you could take your WhatsApp Broadcasts to the next level with the power of Artificial Intelligence (AI)? By leveraging AI, you can unlock even more potential and significantly boost your Return on Investment (ROI).
WhatsApp Broadcasts already boast impressive statistics, with a staggering 98% open rate and 35% click rate. But imagine what you could achieve by integrating AI into your WhatsApp marketing campaigns.
Let’s start by exploring how AI can help you build a WhatsApp Broadcast list. WhatsApp offers several built-in features that can be enhanced with AI. For example, with the WhatsApp Business API, AI can analyze customer interactions and create personalized opt-in invitations. This way, you can leverage AI to attract more subscribers to your broadcast list.
Another feature you can use is the WhatsApp Click-to-Chat Link. By using AI algorithms to analyze user engagement data, you can determine the most effective platforms to place these links. This will help drive more users to engage with your WhatsApp Broadcasts.
QR codes have become increasingly popular in marketing, and WhatsApp offers its own QR code feature. By using AI algorithms to track QR code scans and optimize their placements, you can make sure that your QR codes are working to their full potential.
If you have a website, you can also utilize the WhatsApp Chat Widget. AI can personalize the interactions on the chat widget, improving user engagement and encouraging visitors to join your broadcast list.
Let’s move on to how you can utilize AI in the content and engagement strategies of your WhatsApp marketing campaigns.
AI can help you create personalized newsletters by analyzing subscriber preferences. By tailoring your newsletter content to match what your subscribers are interested in, you can encourage them to provide their WhatsApp details and join your broadcast list.
When it comes to content strategy, AI can be a powerful tool. You can use AI tools to analyze trending topics and user interests for your blogs and glossaries, ensuring that your content remains relevant and engaging. Additionally, AI can help you segment your audience and offer personalized eBooks, reports, and whitepapers to different user groups.
Product demos and samples are a great way to engage potential leads, but AI can take it a step further. By deploying AI to identify leads that are most likely to respond positively to product demos and samples, you can focus your efforts on those who are most likely to convert.
Workshops and webinars are another effective way to engage with your audience. With AI tools, you can identify trending topics and personalize invitations, increasing registration rates and ensuring that you are reaching the right people.
Social media is a valuable platform for marketing, and AI can help you make the most of it. AI algorithms can analyze social media behavior to identify potential leads and optimize your content, ensuring that you are reaching the right audience at the right time.
When it comes to social media ads, AI can help you fine-tune your targeting. By leveraging AI to analyze user behavior and preferences, you can ensure that your ads are being shown to the people who are most likely to be interested in your products or services.
Chatbots have become increasingly popular in customer service, and for a good reason. By integrating AI-powered chatbots into your social media platforms, you can handle complex queries and provide personalized interactions. This can greatly improve customer satisfaction and engagement.
Customer referral programs are a valuable tool for growing your business, and AI can help you make them even more effective. By using AI analytics, you can identify customers who are most likely to refer others and tailor your referral programs accordingly.
Now let’s focus on how you can maximize your ROI with WhatsApp Broadcasts and AI.
First and foremost, AI-driven personalization is key. By using AI to segment your audience, you can send highly personalized and relevant broadcasts. This will ensure that your messages resonate with your audience, increasing engagement and conversion rates.
Timing is everything, and AI can help you with that too. By leveraging AI, you can determine the best times to send follow-up messages and analyze customer responses for future interactions. This will help you build a strong relationship with your audience.
Continuous AI analytics are crucial for optimizing your WhatsApp Broadcasts. By employing AI tools to analyze the performance of your broadcasts, you can adapt your strategies accordingly. This will help you stay ahead of the game and ensure that you are delivering the most effective messages to your audience.
It’s important to remember that while AI is a powerful tool, it should be used in adherence to best practices and compliance policies. This will ensure that your communication is respectful and effective, building a positive reputation for your business.
Finally, integrating WhatsApp and AI into a broader digital marketing strategy is essential. While WhatsApp Broadcasts and AI are powerful on their own, incorporating them into a comprehensive strategy will result in synergistic effects. This means that you should integrate WhatsApp and AI with other marketing channels and tactics to create a unified and effective approach.
In conclusion, combining WhatsApp Broadcasts with AI offers a powerful opportunity to enhance your digital marketing efforts. By strategically building a broadcast list and employing AI for personalized, data-driven communication, businesses can achieve a significantly improved ROI.
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AI-Driven Personalization: Use AI to segment your audience and send highly personalized and relevant broadcasts.
Timely AI-Enhanced Follow-Ups: Leverage AI to determine the best times for follow-up messages and to analyze customer responses for future interactions.
Continuous AI Analytics: Employ AI tools to continuously analyze the performance of your broadcasts and adapt strategies accordingly.
Adherence to Best Practices: Combine AI insights with WhatsApp’s compliance policies to ensure respectful and effective communication.
Integrating WhatsApp and AI into a Broader Strategy: Don’t rely solely on WhatsApp and AI. Integrate them into a comprehensive digital marketing strategy for synergistic effects.
If you are not comfortable with AI, you can still leverage WhatsApp broadcast for a good ROI.
1. WhatsApp’s Built-In Features
WhatsApp Business API: Utilizes an opt-in policy encouraging new users to connect with your business.
WhatsApp Click-to-Chat Link: This feature allows you to create a clickable link for your WhatsApp business number, making it easier for customers to reach out directly.
WhatsApp QR Code: Similar to Click-to-Chat but in a scannable QR format. Ideal for offline and online platforms.
WhatsApp Chat Widget: Integrates a chat feature on your website, directly linking to your WhatsApp business account.
2. Create a Newsletter
Offer subscriptions for updates about your business and industry, encouraging users to register with their email and WhatsApp details.
3. Content Strategy
Free Content: Blogs and glossaries to increase awareness and credibility.
Gated Content: eBooks, reports, and whitepapers for detailed insights, in exchange for contact details.
4. Product Demos and Samples
Entice potential leads with a ‘free taste’ of your product or service in exchange for contact information.
5. Engaging Workshops and Webinars
Host informative sessions in exchange for registration, thus acquiring leads.
6. Social Media Utilization
Leverage the extensive reach of platforms like Facebook and Instagram to gather leads.
7. Paid Social Media Ads
Target specific demographics with sponsored ads to attract a relevant audience.
8. Chatbot Integration
Use automated chatbots to engage users on social media, covering FAQs and product details.
9. Customer Referral Programs
Encourage current customers to refer friends in exchange for exclusive offers.
Maximizing Returns with WhatsApp Broadcasts
Once you’ve built a robust list, it’s crucial to maximize the potential of WhatsApp Broadcasts. Here’s how:
Targeted Content: Ensure that your broadcasts are relevant and engaging. Personalize messages based on user behavior and preferences.
Timely Follow-Ups: Use the high open rates to your advantage. Send follow-up messages to keep the conversation going.
Measure and Adapt: Track the success of your broadcasts. Use insights to refine your strategy continually.
Compliance and Consent: Always adhere to WhatsApp’s policies and respect user consent for message receipts.
Integrated Marketing Strategy: Don’t rely solely on WhatsApp. Integrate it into a broader digital marketing strategy for maximum impact.
Conclusion
Combining WhatsApp Broadcasts with AI presents a powerful opportunity to enhance your digital marketing efforts. By smartly building a broadcast list and employing AI for personalized, data-driven communication, businesses can achieve a significantly improved ROI. Remember, the key lies in the strategic, innovative, and ethical use of these technologies to create meaningful connections with your audience.
Are you eager to expand your understanding of artificial intelligence? Look no further than the essential book “AI Unraveled: Master GPT-4, Gemini, Generative AI & LLMs – Simplified Guide for Everyday Users: Demystifying Artificial Intelligence – OpenAI, ChatGPT, Google Bard, AI ML Quiz, AI Certifications Prep, Prompt Engineering,” available at Etsy, Shopify, Apple, Google, or Amazon
I recently started actually checking them out, and submitting topics. It’s entertaining for sure. I know they have to be spending money to run them, don’t they? And I know there’s Patreon’s. These are 24/7 streams too. There are features that cost money (I’ve only submitted topics through Discord for free, but there are people paying for the paid features, like making the characters sing a YouTube video, throwing objects at characters (often references from the show). One of my biggest questions is about the copyright legality of this, but there’s AI Family Guy l, AI SpongeBob, and AI South Park (there was AI Seinfeld, but they got shut down by Twitch for offensive submissions not being filtered, and then came back but renamed the characters to be even less similar to the Seinfeld characters), and probably others I don’t know of, but also guarantee there will be more to come. This could be potentially great passive income, I can’t imagine these people are actually SPENDING money to run these, without any way of making any money from it. submitted by /u/AImoneyhowto [link] [comments]
I can use ChatGPT effectively to ramp up quickly on open-source project source code. Here is a very simple example of understanding cockroachDB code repo. I work as a lead in a small tech company with about 80 tech employees. How would I set up something similar locally (in-house) for our private code repos? The purpose would be twofold: 1. Help new employees ramp up more easily, and 2. Help people on the team who are not well versed with a particular area of the code that they haven’t worked on before. I feel this approach will help the person learning (especially juniors) to ask 'better' questions instead of basic ones, and want to test this theory. How would I go about it? submitted by /u/eRajsh [link] [comments]
I want to build an AI assistant, something like Siri or Alexa from scratch. Also it needs to connect to my corpus of knowledge & intelligently answer questions. ie both chatbot plus knowledge bot. What do I need to learn ? I'm willing to put in the effort right from the math. Recommend me: The Math concepts involved ML concepts I need to learn Neural network concepts Recommend the python libraries (from simple experimental frameworks to production grade frameworks) What are some good free video courses submitted by /u/throwawayanontroll [link] [comments]
I want to know if some tool which I can give it my liked songs playlist (which has more than a thousand songs) and then the ai will (to itself) categorize each song in terms of many parameters (higher/lower tempo, energy, language, length, mood/vibe, and many more) and then I would be able to ask it to create, for example, out of my liked songs build a playlist that's all about high energy/high tempo for workouts, and the tool would do just that, will add all the songs it considered "high energy" to a new Spotify playlist. submitted by /u/Marvellover13 [link] [comments]
The ones where they change the names of different people to sound like Fortnite terms. I’m curious if anyone knows the AI used to make the images and voiceovers submitted by /u/donqon [link] [comments]
Recently, Alibaba group released Qwen2.5 72B instruct model which is giving a stiff competition to the paid claude3.5 sonnet that too ooen-sourced. Checkout the demo here : https://youtu.be/GRP5qlF4BDc?si=vnGd7WZ7ACbrfNGk submitted by /u/mehul_gupta1997 [link] [comments]
Wanting to build a chatbot with documentation library that is publicly available on our website allowing a customer to ask questions about any info. Any recommendations? submitted by /u/dkoepke [link] [comments]
Foxconn chairman says AI investment boom ‘still has some time to go’ as language models evolve.[1] Samsung Electronics apologises for disappointing profit as it struggles in AI chips.[2] Google DeepMind exec says AI will increase efficiency so much it’s expected to handle 50% of info requests in its legal department.[3] Fairfax Co. to use AI for screening nonemergency 911 calls.[4] Sources included at: https://bushaicave.com/2024/10/07/10-7-2024/ submitted by /u/Excellent-Target-847 [link] [comments]
Inflection (the creators of Pi) just released the Pi API: https://developers.inflection.ai/playground This API allows developers to build a clone of Pi, which is great news because a bunch of people in this subreddit have mentioned that Pi has been degrading since Inflection was acquired by Microsoft. I’m creating my own website that’ll basically be a clone of Pi with improved memory and no rate limit. I’m a community member of Pi, so I’ll listen to people’s feedback 🙂 If you’re interested in being one of the first to use it, join the waitlist: https://yk1m5yevl9j.typeform.com/to/SnveAlMQ Also, feel free to share your feature wishlist or other thoughts in this thread! submitted by /u/shopifyIsOvervalued [link] [comments]
I've been experimenting with AI music and video for about a month now, so I decided to throw my hat in the ring with these AI movie trailers. I really like Star Wars and Blaxploitation movies, so I combined the two with this video. I used Hailuo to make most of the video clips (with a couple being made with Runway). The narration was done with ElevenLabs. The music was generated with Suno. All of the sound effects I edited in myself. I also did things like add lasers and some other post effects to try to make it as polished as possible. I edited this with Davinci Resolve and did some audio effects in Reaper. This took me about a week to finish and I learned a lot about editing. Would love to get any feedback or thoughts on this as I gave this everything I've got. https://youtu.be/zyqyNXUkfLs THANKS FOR WATCHING! submitted by /u/justdandycandy [link] [comments]
Hi all, I'm deep into AI in the healthcare setting in Australia, policy landscape and futures. I want to do some additional study that is more technical than the free fundamentals courses but I don't need to train to program a LLM or relearn calculus. Any suggestions or communities that are worth getting involved in? Ta! submitted by /u/annabelita24 [link] [comments]
My friends and I had a debate about how long would it take for a model to take in a script from any writer and produce a whole new episode for a show like friends lets say. The episode would have to be of quality where you could just insert the episode into a season, and it would not be noticeable that it was made by Ai. My friends think it is possible in 3-5 years im thinking more like 10-15 want all of your opinions submitted by /u/Ok-Somewhere5685 [link] [comments]
What factors do you consider most important when choosing AI tools to improve your business effectiveness? Is it automation, data analysis, customer service, or something else? How do you balance finding the right tool while making sure it integrates smoothly with your existing systems? submitted by /u/OddReplacement5567 [link] [comments]
I'm finding and summarising interesting AI research papers every day so you don't have to trawl through them all. Today's paper is titled "CounterQuill: Investigating the Potential of Human-AI Collaboration in Online Counterspeech Writing" by Xiaohan Ding, Kaike Ping, Uma Sushmitha Gunturi, Buse Carik, Sophia Stil, Lance T Wilhelm, Taufiq Daryanto, James Hawdon, Sang Won Lee, Eugenia H Rho. This paper explores the novel CounterQuill system designed to support human-AI collaboration in writing counterspeech, an emerging approach to countering online hate speech. It provides a structured methodology to aid users in composing empathetic and effective counterspeech. Here are some key findings: Enhanced Sense of Ownership: Users working with CounterQuill reported a stronger sense of ownership over their co-authored counterspeech. This feeling was attributed to the system’s interactive process that facilitates personal involvement in the writing. Increased User Confidence: The study found that CounterQuill increased users' confidence and perceived ability to create empathetic and impactful counterspeech, surpassing the outputs generated by systems like ChatGPT. Improved Identification of Hate Speech Components: The system's design encouraged users to better identify hate speech components, such as targeted identities and dehumanizing actions, through an interactive highlighting process. Greater Empathy in Communication: CounterQuill's structured learning and brainstorming sessions enhanced users' understanding of empathy-based strategies, promoting a more constructive approach to counterspeech. User-Centric Customization: Participants appreciated the system's ability to align AI suggestions with their personal experiences and ideas, offering nuanced guidance that improved writing outcomes. You can catch the full breakdown here: Here You can catch the full and original research paper here: Original Paper submitted by /u/steves1189 [link] [comments]
Interesting article with deep dive into efforts at the Broad Institute etc. https://www.newyorker.com/magazine/2024/09/09/how-machines-learned-to-discover-drugs submitted by /u/gabreading [link] [comments]
I often see people discussing AI progress as if it's directly tied to Moore's Law, but this can be misleading. Moore's Law only tells us how compute power (transistor count) increases over time, not how model performance (e.g., error rate) improves over time. What we really need is the scaling law, which describes how model performance scales with compute. Here's the key point: the scaling law shows that you need more and more compute to achieve the same increase in performance. Because the exponent of and exponential is still exponential, model performance still scales exponentially over time, but, exponentially slower than Moore's Law. The Bigger Picture: Moore's Law: Describes how compute increases with time (Time → Compute). Scaling Law: Describes how AI model performance increases with compute (Compute → Performance). When you connect the two, you get the real relationship: Time → Compute → Performance. This adjusted model is a lower bound for AI progress, meaning it gives a conservative estimate of how fast AI can improve over time. Why Does This Matter? This has huge practical implications. For example, while Moore's Law might lead to 16x compute growth over 10 years, AI performance only grows 2x due to alpha from the Scaling Law (approx 0.28). If AI can currently automate 10% of human tasks, reaching 99% automation would take 8.2 years under Moore's Law. Factoring in the scaling law, it actually takes 29.2 years! Note: I'm talking about a LOWER BOUND: this means that according to (relatively) stable laws (Moore's and Scaling Law), we can predict that AI performance should atleast grow as quickly as this lower bound. This means AI progress can still be A LOT higher than this bound, due to higher investments, better algorithms, self-improvement etc. But we refrain from using these for a bound since they are hard to predict as opposed to our laws. submitted by /u/PianistWinter8293 [link] [comments]
Customize the GPT-4o Mini model to classify posts from Reddit into "stressful" and "non-stressful" labels. In this tutorial, we will fine-tune the GPT-4o Mini model to classify text into "stress" and "non-stress" labels. Subsequently, we will access the fine-tuned model using the OpenAI API and the OpenAI playground. Finally, we will evaluate the fine-tuned model by comparing its performance before and after tuning it using various classification metrics. https://www.datacamp.com/tutorial/fine-tuning-gpt-4o-mini submitted by /u/kingabzpro [link] [comments]
So I'm an artificial intelligence student and I'll be making a project as my End of study project , maybe apps or websites in condition we integrate AI please if someone has any ideas (I would prefer unusual innovative ideas please ) I'm open to learn things so don't limit your ideas doesn't matter what skills I already have . submitted by /u/bigangrywatermelon [link] [comments]
Has the idea been proposed before to specifically limit models to areas of expertise on purpose and most importantly give them COMPETING GOALS, and have them “talk” to other similarly powerful models for answers/authority they need to operate and proceed? Like we’d still give them all highest level goals of not ending humanity and whatnot, but each models highest level goal like this is worded differently and is more of a backstop. They then have some kind of lower level goal that is more specific and can be coded to be a bit in conflict with other models goals. I’m thinking essentially a digital version of check and balances. Like we all know that we are probably not smart enough to properly think of every way an ASI could get out of control, but if we made a flurry of AGI-level+ models and made them all have to get some kind of consensus with specific strengths/weaknesses and most importantly competing goals could that work as a way to have them police each other instead of us trying to do it perfectly? Granted not working well in current democracies but perhaps without the emotion and money stuff to corrupt, and realllllllly well thought out checks/balances/interdependencies this could be an architecture for lowering risk of life ending ASI? If this isn’t a new idea could someone point me to where I could read more discussion on this? submitted by /u/crispy88 [link] [comments]
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