If you want more leads, artificial intelligence can help.
Insent uses AI to instantly connect you with prospects on your website through smart conversational marketing.
With its AI and machine learning, Insent's platform can understand conversations and their context, then route the right leads to the right people.
The result is that marketers capture more leads from the traffic coming to their website, automatically qualifying those leads in real-time and notifying sales when they're good leads.
We spoke with Insent founder and CEO Arjun Pillai to learn more.
In a single sentence or statement, describe your company.
Insent is a human-first B2B conversational marketing platform that enables marketers to deliver red carpet experience to high-value/ABM prospects.
How does your company use artificial intelligence in its products?
We use AI and machine learning to understand the conversations, the person/company behind the chat, its intent, expected next step(s), and how the bot should respond.
What are the primary marketing use cases for your AI-powered solutions?
Primary marketing use cases for Insent include conversational marketing, ABM, demand generation, and opportunity acceleration.
What makes your AI-powered solution smarter than traditional approaches and products?
Insent proactively engages the website visitors in a personalized way, understands the context of the interaction, and passes on the right deals to the right sales people in real time.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
No, but having HubSpot, Marketo, Pardot, or Salesforce will make the tool 10X more effective.
Who are your ideal customers in terms of company size and industries?
Our ideal customers have 100 to 1,000 employees, and work in industries like software, advertising, and finance.
What do you see as the limitations of AI as it exists today?
Understanding context is a big problem. Accurately judging when to pass leads on to a human being without giving false positives is another limitation.
What do you see as the future potential of AI in marketing?
It is huge. If you look at automation platforms we use today, many were architected in 2004 or 2005. They cannot handle account based, unified profiles, or big data, and there are no proactive suggestions. They are simple workflow systems.
Marketing automation 2.0 will be based on account-based marketing, big data, and AI-based recommendations that make marketers' jobs far easier than they are now.
Any other thoughts on AI in marketing, or advice for marketers who are just starting with AI?
AI is not a magic wand. In its current state, it has a lot of limitations. Either you can have a specific AI for you that needs a lot of money and training OR you can have a system with some AI, but faster implementation and less cost. You have to decide the balance.
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).