Want to identify more of your ideal customers automatically?
AI from a company called Rehinged can help.
Rehinged uses AI in the form of natural language processing and machine learning to convert tons of data into actionable intelligence for sales and marketing teams. This data allows those teams to identify ideal customers and actionable market intelligence from real-time business signals.
We spoke to Jim Sagar, CEO at Rehinged, to learn more about how this AI-powered marketing solution works.
In a single sentence or statement, describe Rehinged.
The Rehinged.AI platform converts massive streams of business data into actionable intelligence for sales and marketing teams—to identify their ideal customers based on real-time signals.
How does Rehinged use artificial intelligence in its products?
Our platform uses natural language processing to extract meaning from business news, industry forms, government data, video, social media and job postings, as well as machine learning for scoring algorithms.
What are the primary marketing use cases for your AI-powered solutions?
Since our platform identifies real-time signals from companies that match their ideal customer profile, marketers use our AI platform to send relevant marketing messages based on real-time activity. SDRs, sales reps and account executives use our platform to deliver relevant one-to-one communication.
What makes your AI-powered solution smarter than traditional approaches and products?
Our AI platform creates dynamic lists scored for our customers' ideal targets and groups these by signal type. This allows SDRs / sales reps to improve their productivity by 10X because they can target the relevant portion of their target market, and allows marketers to reduce cost and increase conversions by focusing timely messages on a narrow, highly-targeted audience.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
We monitor businesses and organizations, so our platform is more valuable for marketers who place a higher value on dynamic signals - meaning events, strategies, hiring, software used, funding, violations, licenses, etc. - to target their campaigns.
Who are your ideal customers in terms of company size and industries?
Healthcare and SaaS are two prominent verticals—any company selling a SaaS solution or a company selling into healthcare facilities. Since we're monitoring small to mid-market businesses across the US, other ideal customers are anybody selling into those companies, like insurance, employee benefits, banking, professional services, and consulting.
What do you see as the limitations of AI as it exists today?
For our audience, the data engineering provides the greatest value. NLP isn't perfect, but it's effective enough when applied to large, relevant data streams. When people use NLP to extract meaning from small volumes of content, they're usually disappointed with the results, as a human is still going to out-perform a machine.
What do you see as the future potential of AI in marketing?
There are so many use cases in marketing! However, we're still very early in many of them. Automating the customer journey is one that's gaining traction in B2C. For us in B2B, we're focused on delivering an end-to-end solution wherein we use AI to identify target customer groups, match to marketing and sales messages and deliver one-to-many digital campaigns to deliver sales-qualified leads. In short - we're automating much of the B2B sales and marketing function.
Any other thoughts on AI in marketing, or advice for marketers who are just getting started with AI?
Always start with your use case and make sure it's worth automating. Then look for solutions.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).