The Modern Marketing Automation Platform

Introduction

As your business scales, managing inbound volume quickly becomes a frustrating challenge. Legacy MAP such as Marketo, Pardot, or Hubspot also introduce operational complexities – fragmented data, manual upkeep, and rigid workflows that prevent your team from scaling. 

Your CRM may be getting crowded with spam/low-intent leads, AEs are getting the wrong/low-quality leads, data is missing, and people are falling off forms. 

Marketing teams at Adaptive, MyOutdesk, and Hockeystack have set up AI-native inbound marketing funnels on Conversion that scales with them:

• Form Creation
• Spam Check
• Data Enrichment
• Lead Scoring
• Lead Routing

For this workflow, you’ll need a form that’s either built in Conversion or hooked into Conversion via iframe.

Trigger

Most inbound workflows start by triggering off a form submission. You can simply set this up in Conversion by selecting an Engagement -> Form Submission for your trigger. You can choose multiple forms using the OR operator if you have multiple forms hosted throughout your website. 

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Spam Check

A fundamental issue with inbound workflows comes from the amount of spam that enters through forms. Your CRM ends up getting populated with tons of records that look like [email protected]. 

Using a magic enrich node, you can prompt AI to filter out any emails that may look spammy by inserting the email and domain variable.

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Lead Scoring Form Submissions

Right after a prospect fills out a form, you’ll want to identify how strong of a lead they are with lead scoring - one of Conversion’s most powerful features. Traditional MAPs use a point-based system to keep track of lead activities, demographic fit, and behavioral intent. 

With Conversion, you can prompt in natural language to score leads and identify who your most likely buyers are. These prospects typically deserve higher budget ad campaigns, more personalized email nurture sequences, and high-touch outreach from the sales team. 

Using a magic enrich node, you can write a prompt instructing AI to score your leads. There are 2 types of lead scoring you can do in Conversion. As a baseline in both these types, include examples of what a good lead looks like, what an average lad looks like, and what a poor lead looks like. You want to give AI as much context as possible to make informed decisions. You may have to tweak the prompt a couple of times to get it right but once it’s set up correctly, you’ll never have to touch it again!

Demographic 

For demographic lead scoring, you can pull in factors like company domain, industry, job title, seniority, and employee count to assess how good of an ICP fit the lead is. For Conversion, Directors of Marketing Operations at a 200+ employee B2B SaaS company is our perfect ICP. 

Behavioral

You can also behaviorally lead score in Conversion to assess how high-intent certain buyers are and prioritize getting them over the finish line. Instead of demographic variables, you can bring in engagement variables such as “Number of site visits”, “Form Submitted”, “Webinar attendances", “Sales Meetings Attended”, etc.

Here’s an example of a well-written prompt for lead scoring in Conversion.

Given [Job Title], [Number of Employees], [Industry], and [Company Domain], and available data from the website, assign a lead score from 1–10 (10 = highest intent/fit). Include a short rationale focused on fit for a data analytics solution.

Examples:
"Lead Score: 9 — Business Intelligence Lead at a 500-person B2B SaaS company actively hiring data engineers."
"Lead Score: 6 — Finance specialist at a medium sized nonprofit; fit is moderate due to limited scale."
"Lead Score: 10 — Director of Product at a fast-scaling consumer software company actively launching regional campaigns."
"Lead Score: 2 — Sales person at a local service business with limited digital data."

Return ONLY a number between 1 and 10.

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Routing & Post-Form Submission

Now that you are effectively lead scoring your form submissions, you can perform a host of actions in Conversion. 

If a lead score is greater than a certain number, you can assign account owners in Salesforce, create tasks, enroll people in nurture sequences, or send Slack notifications. 

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Introduction

Sending a prospect a highly-targeted relevant case study can be one of the biggest needle movers during the marketing lifecycle. In a world where competition is continuously increasing, building social proof and trust has become a moat in itself. 

However, sending a generic case study to all your prospects is a signal that you don’t know your buyer or their needs well. 

Here’s how you can build a Case Study Suggester in Conversion using call transcript data (or general firmographic data points). 

Prerequisite

For this workflow, you’ll need a repository of case studies hosted on your website and (optional) call transcript data.

Find a customer’s biggest pain point

This step is optional in the case you don’t have call transcript data available in your CRM. If you do, we can put together a small workflow using a magic enrich node to find a customer’s biggest pain point using the call transcript.

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Using an AI Snippet to suggest a case study

Now that we’ve established what a customer’s biggest pain point is, we can use Conversion’s AI snippet builder to suggest a case study. 

Simply, create a ‘snippet’ on the Snippets tab and prompt it similar to the image below. Make sure that you include a fallback and good examples for AI to have context.

Awesome! Now your case study snippet is built. You can now insert this into nurture emails in Conversion and let social proof become your moat!

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Introduction

Job titles are continuously being populated in your CRM whether it’s from AEs manually filling data out, first-party form-fill data, or LinkedIn enrichments coming in from ZoomInfo, Clay, Apollo, or Conversion.

For the same role type, you may have over 50+ variants of how the job title is portrayed in your CRM.

Ex:

• VP of MarOps
• Director, Marketing Operations
• Head of Marketing Operations
• Marketing Operations Manager
• Senior Marketing Operations Manager

You can’t segment by job title because all of them look different within your CRM.  This leads to a fundamental issue for marketing teams where personalization by job title is virtually impossible. 

How to segment personas in Conversion

Here’s how Conversion helps. 

Using a magic enrich node, you can use AI to segment contacts into distinct persona buckets enabling you to personalize journeys, emails, and ads to a unique persona. 

Simply create a “Persona” variable  and prompt a magic enrich node along the following lines:

Based on the job title of this contact [insert job title variable], identify which of the following persona buckets they fall into:
- MarOps
- RevOps
- Marketing
- Sales

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You can change the buckets however you’d like depending on your company’s ICP.

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Now that you have distinct persona variables in your Conversion platform, you can dynamically change the text in emails based using magic blocks, create variable branches based on these personas, put contacts into custom ads audiences, and so much more.

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