AI Sales/Marketing Agents for B2C

Over the last year, we've worked with mid market/enterprise companies in B2C services industries to optimize lead conversion with AI SMS/voice agents 

Here's everything we learned.

1. You need more than a prompt. 

To actually capture complex business logic common for mid market/enterprise companies, you need a conversational flow that consists of multiple prompts.

Only based on certain responses/triggers should the conversation switch from one prompt to another.

Early on, we tried to capture this complex business logic with a giant prompt. The LLM straight up does not follow the logic + hallucinates more often.

2. Integrations matter, especially with the CRM.

There's 2 parts to the integration.

CRM -> AI agent: you need to make sure that the moment a new lead comes (e.g. from a website form submission) that the AI automatically starts a conversation. 

Typically this looks like a CRM trigger for a new lead -> API call for the AI agent to reach out over SMS or voice.

AI agent -> CRM: the AI agents are having tens of thousands of conversations with leads, but what's the point if your sales team don't have any visibility into those conversations? 

We've built some native integrations with CRMs like Salesforce to auto-sync new info from conversations to lead objects in Salesforce, but Zapier also works for other CRMs.

3. The CTA needs to be easy to act on.

In 90% of cases, the use case for AI agents in B2C services is something like this:

- reach out to the lead

- qualify/nurture the lead till they're ready to buy

- transfer the call to a human agent or schedule a callback

You can in theory just send scheduling links to leads or a phone number for them to call, but the best user experience is just a native transfer feature built into your AI agent.

For SMS, that means an outbound call to the lead that connects them to the human agent once they pick up. For voice, that's a live transfer on the existing call.

4. Iterating/optimizing the agent is really f**king important.

Yes, you can run through a bunch of test cases + evals, and the AI will seem to work fine.

But when you actually launch with hundreds, thousands of leads, there will be a ton of edge cases + behavior you don't expect.

When those things come up, it's important to improve the agent till you get to an optimal state - it's an iterative marathon, not a sprint.

A flashy AI agent demo means little these days.

Implementation + execution are what matter.

We give all our customers white-glove onboarding/support. 

IMO it's 100% critical, especially at the mid market/enterprise level.

If you're curious to learn more about AI sales/marketing agents for the B2C world, you can book a demo here.