Today we explore RAD AI, an exciting company whose innovative platform brings the power of AI to marketing. We took a tour of their platform, spoke with RAD AI’s CEO, and looked at how one could invest in this company using crowdsourcing
We are all bombarded with advertisements and marketing by companies vying for our attention. Digital advertisers flood us with unwanted and irrelevant messages, spam and junk advertising. Marketers want to connect with us, but they’re trying to do so using language and messaging that does not resonate with us and turn us off to their products or services, even for things we are the right target market for. They might have the right target market but are wasting billions through ineffective and insincere messaging to that market.
Audiences everywhere demand authenticity in marketing and all forms of messaging, and these must always feel real and genuine. As consumers we want to feel that as we’re the right target market or prospect we’re being spoken to in a way that feels genuine and sincere. Simultaneously, this consumer need for authenticity in messaging must still also be capable of producing commercial success.
An AI-powered marketing platform holds great promise for marketers. Businesses everywhere want to make sure their messaging and campaigns are effective over an increasingly diverse range of media and outlets. They also want to learn what messaging produces the best effect and adapt that based on insights of previous messaging to their target audience.
Marketers want to create more effective marketing campaigns and messaging, and optimize their messaging, spending, and campaign reach. The speed with which marketing messaging can be seen by a targeted audience is unprecedented. Being able to optimize that messaging to use the correct tone and feel for the target audience is essential. AI offers the ability to create unprecedented tools to analyze responses to messaging, and the tone and feeling to create the messaging that best resonates with the target audience.
At face value, consumers can seem wary about the idea of AI. This perception is largely due to how AI has been used in sci-fi movies and from press reports of how AI has been used in isolated cases in the past; any type of science can be put to good use or misused.
But people have used AI for many years to good effect. One of the most recognizable ways that a technology-driven platform can help to benefit many is Amazon.com’s recommendation engine and features such as “Customers Also Bought” and “Recommendations & Popular Items. These features are successful both for Amazon.com and for consumers who want relevant recommendations to help them make informed choices.
RAD AI’s platform brings the power of AI marketing campaigns and business communications, allowing marketers to;
- Create authentic-feeling marketing programs for every marketing channel and platform.
- See which type of language, tone, messaging, even specific words, works best for their campaigns across different channels.
- Analyze the internet with the push of a button, allowing them to create authentic influencer content for their customer personas.
- Create thoughtful narratives that engage customers in ways that RAD AI can measure and improve. In real-time, AI measures behavior of hundreds of thousands of online consumer touchpoints, and recommends or generates new content based on these engagement metrics.
- Connect RAD AI to existing business analytical platforms such as Google Analytics to recommend and make measurable improvements, often leading to significant core marketing performance improvements compared to not using RAD AI.
RAD AI’s platform offers to work across;
- Blogs & articles
- Organic SEO
- Paid media & digital ads
- Email sequences and campaigns
- Product descriptions
- Topics and titles
- Influencer marketing across all social platforms
- Company communications
- Anywhere language is used, with additional advancements in no-written communication such as video
Technical Facets of RAD AI
The technology behind AI lies at the heart of the overall platform so we dove into what it offers.
Testing methods such as split testing, A/B testing, multivariate testing, and fractional testing are not new to marketing. Serious marketers have for many years used split testing to arrive at incrementally better methods in their marketing. RAD AI’s platform improves upon that because it is able to analyze a massive amount of data and see the patterns in it to produce the best recommendations to create the most effective results.
RAD AI’s platform uses non-linear regression analysis methods to undertake its analyses and tests. The platform is rated for the highest language accuracy, with a 92% accuracy. RAD’s AI even beats Bert, Google’s language AI, by 30%. This is the most accurate content AI for text-based content, phrases, and language.
RAD AI can analyze campaigns for specific marketing campaigns, or it can analyze existing platforms on the Internet to give specific insights to trends within these platforms.
RAD AI’s CEO, Jeremy Barnett, explained, “We average 35,000 machine learning hours on a campaign, which is the equivalent of analyzing 550 million web pages of data. We’re also connected with Reddit, and we look at every active subreddit. There are about 190,000 active subreddits, and around two million sub Reddits that are on the platform.”
Impressive. But it’s not just RAD AI’s ability to look at a massive amount of data. The AI is not so much smarter than humans are, it’s simply able to apply intelligence and observe patterns around the information that it has access to. It’s able to understand and see what language and words and tone a particular target audience responds to for any given platform or channel.
RAD AI is definitely accurate, but one unique element of the strength of the platform is how the team has built in methods to challenge its own assumptions. This is important. In traditional testing methods such as the A/B testing many companies commonly use, companies often test to prove assumptions and confirm their existing beliefs, but they don’t also attempt to disprove or challenge their own assumptions.
But RAD AI already built that into the analyses and recommendations within its platform. By building in an “adversarial environment” it automatically eliminates assumptions and decisions it makes about something that can’t be true in addition to understanding things that could be true. And based on those two elements working as a team, you’re able to come up with a much better quality of prediction. It’s like harnessing a team of skilled copywriters, marketers, and data scientists together the moment you put RAD AI to a task.
No matter how good any platform is, if it only substantiates the assumptions and insights it makes without challenging them, you end up perpetuating any biases in the system. We know from trading and investing (and life in general!) that humans are incredibly prone to confirmation bias. You don’t want that in many areas though because you’re simply confirming what you already know, including all the errors and biases and assumptions you already have.
In this way RAD AI is always looking at ways to disprove its assumptions as well as to validate them. This results in extremely quick, accurate, highly perceptive, and reliable insights into your communications. Each business has discreet audience segments and groups of target customers, and each of those segments needs to be communicated with in a respectful and inclusive manner.
RAD AI’s platform is continually being improved and is built on $20M of R&D by Atomic Reach, a marketing technology company RAD acquired to scale their AI capabilities.
Although this is an AI platform, not a human, its output is difficult to tell apart from human-created copy. We’d agree with RAD AI’s stated promise that it “blends the magic of storytelling with a mastery of AI” to create more authentic marketing programs. It’s uncanny that a machine can make recommendations (make changes automatically if you want it to) that feel more authentic than the actual human-created original copywriting. This is not some “AI article spinning” commonplace tool that is widely available these days but actually feels more human than the original copy.
RAD AI can understand an infinite number of these personas and measure, understand, and recommend what type of communication, words, and emotions work to produce results across all these customer groups.
RAD AI takes this data about how real people react, behave, and feel and test it against third-party data sources to confirm the data. It can scan hundreds of millions of data points on the Internet from sites like Reddit, Pinterest, search, and social.
Our AI isn’t so much smarter than a human. But it can read and understand patterns much faster, and understand behavioral patterns across hundreds of millions of pages of data. By comparison, RAD AI can read as many books in about three seconds as you or I could read in approximately 14 years but with near-perfect comprehension.
Improving Marketing With RAD AI
The theory of RAD AI is clear and the numbers are impressive but how does it actually work?
RAD AI analyzes data and then comes back with recommendations that adapt and adjust the language and the actual words to use in your communications. It can do that by allowing you to make the changes yourself right there on screen with RAD AI’s editor, or you can just let RAD AI free to rewrite your content for you according to its recommendations.
We’ve seen RAD AI’s platform in use and it’s impressive… very! And yes, it can even feel a little unnerving at times. Were this a skilled human copywriter making these recommendations we’d be grateful for their celearly perceptive insights. The copywriting suggestions it makes are really spot on and we could see how the target audiences would feel that the changes it makes are more genuine and “felt better” than the original.
It’s quite uncanny watching RAD AI rewrite a piece of content to use specific words and copywriting that it has analyzed your target audience specifically responds to.This is no automated “article spinning” than the copy you created yourself to create a more effective result according to your defined audience and metrics.
It’s easy for a computer to perform rote calculations better than a human can, although if you’ve seen the movie Hidden Figures you’ll remember how this was at the time when machines first started to do many of the complex computations that humans had initially done with pencil and paper.
But it can be difficult for humans to accept that a machine could do something better than a human which involves feelings or conveying emotions in a genuine way. Can a machine convey emotional intelligence in how it communicates? But that’s exactly what RAD AI seems to do very well. By analyzing a marketing campaign it can come up with clear recommendations of which language, tone, emotions, and words used within that campaign which attract and produce the desired outcome with the target audience. RAD AI can make these recommendations and then allow a human to apply the recommendations or you could just let RAD AI automatically change all the words in the campaign according to its recommendations.
It would take years per marketing campaign for any human to analyze the amount of data RAD AI is capable of, but its ability to then interpret these data to such a high degree of accuracy and then come up with clear recommendations would not be possible for a human, at least to any degree of accuracy.
Subjectively, we like what we see. But who is adopting it? And what is the proof that any of this works, though?
RAD AI’s Business Model
We see a lot of great technology fail to make great businesses because a great invention alone isn’t enough to make a viable business. There has to be a clear benefit to a business in using that technology and there has to be a clear revenue model the company has behind their invention.
RAD AI has both a strong revenue model and a growing group of projects and clients benefiting from their technology. The average customer currently spends $250,000 a year with RAD AI. These are companies that are usually spending above $15 million a year on things like paid advertising.
Their clients are also highly committed to email sequencing, blog marketing, communication, social media, and the entire marketing mix. For these types of customers, it’s quite easy for RAD AI to create and build a long-term business offering and value proposition.
RAD AI’s CEO, Jeremy Barnett, describes their revenue model as akin to an “early stage Salesforce”. The company has a software as a service (or SaaS) pricing model but in addition has a consulting model that allows them to work with clients to implement the software and provide consulting, creative services, training, and value-add services around the software.
For RAD AI, it runs the SAAS side of its offerings with a very healthy 85% margin; this is a highly scalable offering.
RAD AI have strong projections for the future and a 158% average annual growth rate forecasted out to 2026.
RAD AI Projects & Clients
RAD AI already have a long list of successful projects and clients across a diversity of campaigns, including work for;
PFS Brands, Apruve, Golf Town, A Top 5 Enterprise Healthcare brand, Fisker, Spin, Salt Life Beer, Crush/Canelo, Think Royln, Prepdeck, Lil Buddies, Scoob!, Mad Tasty, Fandom and Fanta Soda, Delta Airlines, NCM, Condé Nast, Wefunder, Noovie, Nikola, American Lung Association, CitizenNet, and Accenture.
RAD AI Results 📊
RAD AI will analyze content across different channels. This is important to understand because content that you create for, say, a blog, won’t be as effective when used in email, social platforms, or other channels of communication with your customers. A Tweet won’t work as a web page, etc.
Companies who use RAD AI find that across all channels of communication they experience clear, measurable improvements.
Of the many examples we looked at include; 👀
- A Google Ads campaign for a food franchise company: 36.6x increase in ad clicks and increased daily impressions 20x.
- A blog for a B2B financing company: Increased organic traffic by 246% and increased lead volume by 250%.
- For Accenture: Improved average unique article views by 81% and average daily article uniques by 60%. Additionally, improved email open rates by 32.9%.
- Top 5 enterprise healthcare brand: Improved pageviews by 215%, sessions by 253% and lead conversions by 130%.
- Top Hollywood Studio Scooby Doo Campaign: 7.3B views with a 9.63% engagement rate.
- Viral Banking Campaign on TikTok: Total Followers: 13.2 Million views with a 17.89% Engagement Rate: 17.89% and 3.7 Million likes
- Top Mobile Sports App for iPhone & Android Stores: 20.91% engagement rate
- On average, RAD AI’s customers see a 4x increase in content volume for any specific allocated budget. They experience a 250% performance increase across every digital marketing channel they apply RAD AI’s technology in. And RAD AI powered over 100 million impressions last year alone.
The promise RAD AI makes to business is well borne out by what we saw across a wide client base in many different industries and projects
The RAD AI Business Team
A great business can be let down by a poor management team or one without a shared vision among the principles within the company. Within Boardroom we always look for good cohesion, cooperation, and shared goals within the leadership team for any company we consider as an investment opportunity.
RAD AI’s core management and leadership team are all experienced in building, funding, growing, and existing businesses before.
Speaking with them and hearing them speak about RAD AI and their vision for the company, you can tell that they get on with each other and that they share similar visions and directions for the business. This is a good sign. You don’t want leadership to have vastly differing ideas about what they want from the business.
- Jeremy Barnett, CEO of RAD ai, is an experienced CEO and a 3X founder with 2 exits under his belt. He’s used to building startups from 0-100+ employees. He’s also got solid experience in working with venture funds and raising capital.
- Bradley Silver is the Founder and President of RAD AI. Like Jeremy he is a 3X founder with 2 exits. He’s solid experience working with venture funds and has experience in scaling companies to $30M+ in annual recurring revenue.
- Stephen Klein is RAD AI’s Chief Growth Officer and comes with a Harvard Business School MBA. He is Former Chief Marketing Officer at Next Law, Dentons, the world’s largest law firm with 10,000+ employees. He holds SEC/FINRA brokerage and banking licenses.
The rest of the senior management team are similarly credentialed and well suited to running and growing, and exiting a business like RAD AI. We wouldn’t be surprised to see many of them in future years having listed RAD AI as another successful business they’ve grown and successfully exited. As a whole the RAD leadership team have five previous companies exits between them, so moving on and profiting from the sale of a company they’ve built is in their bloodstream.
Investing in RAD AI
RAD AI is currently open for investment through crowdsource platform WeFunder.
Some notable highlights worth summarizing for anyone considering investment in the company;
- $2.2M revenue run-rate & 310% annual revenue growth
- Very strong client base including Accenture, Condé Nast, Dignity Health, and Fortune 500s
- A $300M potential serviceable market among already contracted clients
- World-class team with 5 exits & experience scaling companies to $30M+ ARR
- Already delivered 100M+ marketing impressions with 92% accuracy over the past year alone
- Positioned to disrupt the explosive marketing technology industry which is valued at $120BN
- Backed by Fidelity Investments & Expert Dojo, the 3rd most active US seed investor after Techstars & Y Combinator
- Featured in Bloomberg, TechCrunch, Yahoo Finance, Entreprenuer, Time, Facebook Business and more
RAD AI aims to become the premier AI marketing platform for enterprise clients. They intend to use the capital raised to continue building and scaling their technology, and their product offerings. By strengthening their development and sales engine, RAD will further expand and develop key product offerings that lead to both recurring and new business revenue.
Although RAD AI could raise at a valuation at least double the listed price for this round given that AI technology and software companies consistently raise at 15-50X contracted revenues, they chose to price this round conservatively which is why this current investment round has good scope for crowdsourced funding. By pricing their offering conservatively and aimed at the retail investor, RAD aims to create a realistic upside for each individual investor.
The minimum investment for RAD AI in the current round of funding is currently just a few hundred dollars.
Although we have looked at many facets of a potential investment in RAD AI and believe it is worth considering for a potential crowd-sourced investment as part of a balanced startup investing portfolio, you must still do your own research and due diligence. Prospective investors should fully satisfy themselves as to the information they require to make any investment. Like any investment, you could lose your entire investment, not be able to get at funds when you need to, and might see your own investment in RAD AI diluted by any future rounds of investment the company may undertake.
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