Solving Jobs to Be Done (JTBD) with AI

The jobs-to-be-done (JTBD) framework was developed by Tony Ulwick, founder of the innovation consulting firm Strategyn back in 1990.

In short, it’s a theory that is based on the economic principle that people don’t just buy products and services, they “hire” them to get “jobs” done. And it’s still being used today for good reason. It offers a framework through which a company can take its understanding of their customers’ needs to the next level–and bring predictability to innovation.

B2B marketers, salespeople and strategists ‘worth their salt’ have long used the JTBD framework (whether or not they even realize it!) for more than formal research. They use it to assess their customers’ situations and pain points and to uncover the ‘job’ your product or service is hired to do.

For example if your company offers a workflow automation tool to GTM teams the sales pitch is not our product can streamline your internal processes (the solution), it’s our product can automatically get an inbound lead from marketing to an SDR for qualification faster (i.e. the JTBD).

In this blog, we’ll delve into how marketers are using AI to both identify their customers’ pain points across the tools they use and supercharge their own JTBD.

Enter the era of AI

Most people think of generative AI or ChatGPT when they think of AI, but it’s far more than that. AI can track millions of data sources to surface signals and predict outcomes–everything from buyer intent to champions in the buyer committee who have changed jobs.

AI can’t replace first-party customer interaction, but it can cut through a lot of noise and provide a wealth of intent data and insights to help you hone in on your customers’ most pressing ‘jobs to be done’. And AI can even take it a step further by actually performing your jobs-to-be-done. In summary, the advent of AI supercharges tracking signals (your customer’s JTBD) and driving efficiencies (your JTBDs). It’s a win-win for everyone.

Lantern's AI revenue platform gathers customer and prospect data from multiple sources and activates it across your internal workflows and favorite apps.

JTBD that keep revenue teams up at night

The two things we hear the most from our Lantern customers in B2B sales and marketing is:

1). We need to build more pipeline in less time, which includes protecting existing business, while finding new logos.

2). We have messy, manual hand-offs of data between revenue teams. For example the CRM data is out-of-date and we get bounce backs from our outreach campaigns.

As more cloud-based tools are added to the tech stack it’s getting harder to scale. Marketers and salespeople have to manually wade through data from dozens of tools to find and piece together nuggets to leverage in personalized outreach.

Leverage AI to 'rise above the clutter'

Revenue teams know no amount of endless nurture or ‘spray and pray’ campaigns (yes, even those AI powered outbound tools that ‘personalize’ on autopilot) are going to yield the same results as a targeted, relevant and personalized outreach. It’s no longer a numbers game. By leveraging AI, GTM teams can track signals or JTBD across their customer and target accounts (website views, product sentiment/needs, role and job changes), and develop tailored campaigns that resonate with their target audience. Personalization can cut customer acquisition costs by as much as 50%, lift revenues by 5-15% and increase marketing ROI by 10-30%.

Example of Lantern AI block in a workflow

Customer data isn’t in the CRM

And most of the data on your customers does not live only in your CRM or even LinkedIn. It resides in the tools your customers use every day–Gong, Salesloft, Marketo, and more.  Lantern leverages AI to track data on these customer-specific tools to surface the latest signals.

End-to-end workflows

Marketing Operations and RevOps are spending too much time manually wading through scattered data. For example, 20% of champions change jobs every year. When a champion leaves that is both a signal that a customer may churn and also a potential buyer at a new company.  Sequences, CRMs, Marketing automation tools, Slack alerts and more all need to be updated manually for the current customer, while someone has to track down where the champion went and create a whole new workflow.

AI can automate workflows across a revenue organization to put data to work immediately. A Salesforce record can be automatically updated or created when a person changes roles, a lead can be created, a gift can be sent automatically, a Slack alert can be sent to the SMB team, and marketing can get them automatically added to a personalized nurture campaign and the newsletter.

Example of Lantern Workflow Engine

Going forward

So, what can we look out for going forward? We’ll see less ‘spray and pray’ emails and more targeted outreach based on real signals. And all those signals and changes will automatically be updated in internal workflows and processes.

Interested in learning how you can leverage AI to uncover your customers’ pain points and goals (their JTBD) and streamline your own JTBD?  

Book a demo with us to learn more about and our Champion Chaser and Customer Cloud products.

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