Case Study: How to Build a Full-Funnel AI Workflow for Lead Nurturing

EDITOR'S NOTE

Hey there, 👋

Traditionally, lead nurturing meant setting up a fixed email sequence and letting it run on autopilot. Then, someone downloads a guide, receives scheduled follow-ups, and either books a call, buys the product or service, or stops engaging.

This model still exists, but the focus is on systems that adapt based on lead behavior, company profile, and engagement over time, rather than on fixed rules.

In this issue, we look at how Grammarly and Graphisoft designed full-funnel AI workflows that connect lead capture, qualification, nurturing, and sales into a single adaptive process.

The outcome has been higher-quality conversations, improved upgrade rates, and sales teams that begin with meaningful context.

Let’s go! 🚀

TL;DR 📝

• Grammarly uses Salesforce Einstein AI to identify and score enterprise accounts, helping sales teams prioritize higher-intent leads and improve conversion to paid plans.

• Graphisoft Italia built behavior-triggered workflows in HubSpot, increasing marketing-qualified leads and achieving 55% email open rates.

• Lead quality (rather than lead volume) is the main driver of better sales outcomes.

• The core architecture combines centralized lead capture, AI-assisted scoring, behavior-based nurturing, and automated sales handoff inside a single system.

NEWS YOU CAN USE 📰

Grammarly's 80% Upgrade Increase Shows the Power of AI Lead Scoring. By implementing Einstein AI-powered lead scoring, Grammarly identified high-intent accounts and prioritized them for sales engagement. The result: 80% increase in plan upgrades and 30% shorter sales cycles. [Source: Salesforce]

Graphisoft's 4X MQL Growth Proves Workflow Automation Works. Within six months of implementing lead scoring and behavior-triggered workflows, Graphisoft Italia increased its marketing-qualified leads by 330% and reported commercial growth, driven by improved lead qualification and sales alignment. [Source: Hubspot] 

Why Loop Marketing matters in 2026, according to the State of Marketing report. HubSpot’s latest State of Marketing data shows that 65% of companies exceeded their goals last year, and 93.7% improved lead quality. [Source: Hubspot] 

Why CRM Is the Trusted Foundation of the Agentic Enterprise. CRM isn’t just data storage. It’s the memory, logic, and governance that give AI agents the context and rules to get real work done. [Source: Salesforce] 

THE FULL-FUNNEL AI WORKFLOW CHAIN: AN ARCHITECTURE 🏗️

A full-funnel AI workflow chain for lead nurturing consists of five interconnected stages, each powered by AI and automation.

Awareness & Lead Capture

Leads come from multiple channels: paid advertising, organic search, content marketing, webinars, and social media. The key is to capture these leads consistently and store their information in a centralized system.

Graphisoft, for example, diversified its lead capture across multiple channels, including webinars, blogs, social media, and its e-learning platform, ensuring a steady stream of leads from different sources.

The captured data includes basic information (name, email, company) and behavioral data (which pages they visited, which content they downloaded, how long they spent on the site).

Lead Qualification with AI Scoring

Once leads are captured, they need to be qualified. Instead of manually reviewing leads, AI-powered lead scoring systems analyze multiple data points to predict which leads are most likely to convert.

Grammarly's approach is instructive here, as it uses Einstein AI to identify multiple users from the same company and score them based on company size and engagement with Grammarly resources. This company-level insight is more predictive than individual user behavior alone.

Graphisoft takes a similar approach, but with more granular scoring. They assign points for specific actions: email opens (+), clicks (+), site visits (+), event participation (+), and deduct points for inactivity, creating a dynamic score that changes as the lead engages.

Lead Nurturing with Behavior-Triggered Workflows

Once leads are scored and qualified, they enter nurturing workflows, but these aren't one-size-fits-all email sequences. They're behavior-triggered, personalized journeys that adapt to each lead's actions.

Graphisoft's approach is particularly sophisticated. They created multiple workflows, each triggered by a specific action: downloading an e-book, signing up for a webinar, or starting a free trial. Each workflow sends a series of emails with content related to that specific action.

Graphisoft realized that many leads trigger multiple workflows simultaneously. So they built logic to queue the content intelligently. If a lead downloads all three e-books at once, the workflows don't bombard them with emails; instead, the content is staggered over time.

The results were 55% email open rate and 27.5% click-through rate, far exceeding industry averages.

Sales Enablement & Internal Alignment

Once a lead is sufficiently nurtured and reaches a high score, they need to be handed off to sales, but this handoff needs to be intelligent and timely.

Grammarly automates this with two key mechanisms: First, Einstein Account Insights scores leads and makes those scores visible to sales reps without requiring them to leave their CRM. Second, automation routes the lead to the best-suited salesperson based on territory, specialization, or availability.

Graphisoft sends an automated alert to the assigned salesperson when a lead exceeds the scoring threshold, signaling that the lead is ready for sales engagement.

Internal collaboration tools like Slack play an important role here: Grammarly uses Slack to keep sales and marketing in sync, sends real-time notifications when new leads come in, and allows teams to discuss lead quality and strategy without leaving the collaboration platform.

Conversion & Continuous Optimization

The final stage is conversion, but it's not the end of the workflow. The data from this stage feeds back into the system, informing future iterations of the lead scoring model and nurturing workflows.

Grammarly tracks conversion rates and uses this data to continuously refine its lead scoring model. Graphisoft measures the effectiveness of each workflow and adjusts content and triggers accordingly.

This feedback loop is essential as it ensures that the AI system gets smarter over time, continuously improving its ability to predict which leads will convert and which nurturing sequences are most effective.

GRAMMARLY: AI LEAD SCORING FOR ENTERPRISE CONVERSION 🎯

Grammarly is the world's leading AI writing partner, trusted by over 40 million daily users and more than 50,000 professional teams. We used to use it a lot at my agency, Rise Up Media, actually, for spelling and grammar checks. But scaling from millions of free users to thousands of paying enterprise accounts requires a sophisticated lead nurturing system.

The Challenge

Grammarly's marketing operations team faced a classic problem: they had plenty of leads, but most weren't ready to convert.

They were spending hours manually building email lists based on user open rates and perceived interest. Each month, they sent about 400 marketing qualified leads (MQLs) to sales. However, many of these leads were spam bots or accounts that weren't ready to buy, wasting the sales team's time.

The Solution

Grammarly implemented a full-funnel AI workflow chain using Salesforce's Einstein AI platform. The architecture included:

• Lead identification: Einstein Account Insights identifies multiple Grammarly users who work at the same company, revealing potential enterprise opportunities.

• Lead scoring: Einstein AI scores leads based on company size and engagement with Grammarly resources.

• Lead routing: Automation routes leads to the best-suited salesperson.

• Email optimization: Einstein Engagement Frequency automatically determines optimal send times and frequency to prevent email fatigue.

• Internal collaboration: Slack integration keeps sales and marketing aligned in real time.

• Sales planning: Tableau dashboards provide visibility into lead sources, conversion rates, and the sales pipeline.

The Results

• 80% increase in plan upgrades: By prioritizing high-quality leads, Grammarly saw a massive increase in customers upgrading to paid plans.

• 30% increase in MQL conversion: Despite sending fewer leads (200 vs 400 per month), conversion improved significantly.

• Improved email performance and engagement: Better send practices and reputation management improved inbox placement.

Key Insight

Grammarly's success came from a shift in thinking: quality over quantity. By cutting their lead volume in half but improving lead quality, they actually increased conversions. This required trusting the AI scoring system and being willing to send fewer, higher-quality leads to sales.

GRAPHISOFT: BEHAVIOR-TRIGGERED WORKFLOWS FOR LEAD NURTURING 🔄

Graphisoft, the maker of ArchiCAD BIM software, serves the architecture and engineering community. Their sales cycle is long (multiple months of evaluation), and their target audience is highly specialized. 

The Challenge

Graphisoft Italia had multiple lead-capture channels (webinars, blogs, social media, e-learning platform), but once leads were captured, they weren't effectively nurtured. Leads would download an e-book or sign up for a webinar, but nothing would happen afterward. There was no systematic way to keep leads engaged.

Additionally, the sales team had no visibility into which leads were actually interested. They were contacting everyone equally, wasting time on cold leads.

The Solution

Graphisoft implemented a behavior-triggered workflow system using HubSpot. The approach included:

• Content enhancement: Created a series of e-books ("lead magnets") that follow the buyer's journey, providing value at each stage.

• Workflow creation: Built 20+ workflows, each triggered by a specific action (e-book download, webinar signup, free trial start).

• Intelligent queuing: Implemented logic to prevent email overload. If a lead triggers multiple workflows, content is queued intelligently over time.

• Lead scoring: Developed a scoring system that awards points for engagement (email opens, clicks, site visits, event participation) and deducts points for inactivity.

• Sales alerts: Automated alerts notify the assigned salesperson when a lead exceeds the scoring threshold.

The Results

• 4X increase in MQLs: Marketing qualified leads increased by 330% in the first six months.

• 55% email open rate: Behavior-triggered, personalized workflows achieved a 55% open rate, far exceeding industry averages.

• 27.5% click-through rate: The CTR of 27.5% showed that leads were not just opening emails, but actively engaging.

Key Insight

Graphisoft's success came from understanding that one size does not fit all. By creating multiple workflows triggered by specific actions and by intelligently managing email frequency, they were able to nurture leads effectively without overwhelming them. 

The 55% open rate and 27.5% CTR demonstrate that personalized, behavior-triggered content resonates far better than batch-and-blast campaigns.

THIS WEEK'S PROMPT 🧠

Use this prompt with your preferred LLM to design your own full-funnel AI workflow chain.

The Scenario: You are the Head of Marketing for a B2B SaaS company. Your CEO has asked you to build a full-funnel AI workflow chain for lead nurturing to increase conversion rates by 30% within 12 months.

The Prompt: "You are a Lead Nurturing Strategist. I need your help designing a full-funnel AI workflow chain for my B2B SaaS company.

Current Situation:

• We generate approximately 500 leads per month from various channels (paid ads, content, webinars, organic search)

• Our current conversion rate from lead to customer is 5%

• Our average sales cycle is 90 days

• We have a sales team of 8 people

• We use HubSpot for CRM and marketing automation

• We don't currently have a formal lead scoring system

Goal: Design a full-funnel AI workflow chain that increases conversion rates to 6.5% (30% improvement) within 12 months, reduces the sales cycle to 60 days, and improves sales team productivity.

Questions:

1. Lead Scoring architecture: Based on our business model and customer profile, what lead scoring approach would you recommend? Should we use company-level insights, individual actions, or a combination? What specific signals should we track?

2. Workflow design: Design 5 core workflows that we should implement first. For each workflow, specify:

• The trigger (what action initiates the workflow)

• The sequence (how many emails, what's the cadence)

• The content themes (what should each email focus on)

• The success metric (how do we know if this workflow is working)

3. Sales enablement: How should we integrate these workflows with our sales process? What alerts and dashboards should we create? How do we ensure sales and marketing stay aligned?

4. Implementation timeline: Create a 12-week implementation plan. What should we do in weeks 1-3? Weeks 4-6? Weeks 7-12?

5. Success metrics: What KPIs should we track to measure the success of this workflow chain? How often should we review them?

6. Optimization strategy: How should we continuously improve this system? What data should we analyze? How frequently should we iterate?

For each question, provide specific, actionable recommendations based on best practices from Grammarly and Graphisoft.

HAVING FUN WITH AI

The Clawdbot (now Moltbot) memes were fire on X in the past week. I may have already ordered a Mac Mini myself. 😆

WRAPPING UP 🌯

The evolution from traditional email marketing to full-funnel AI workflow chains represents a shift in how B2B companies approach lead nurturing; it's the difference between automation and orchestration.

Automation follows rules while orchestration understands context and makes intelligent decisions.

Grammarly and Graphisoft have mastered orchestration and built systems that don't just send emails on a schedule. They identify high-intent leads, nurture them with personalized content triggered by their specific actions, route them to the right salesperson at the right time, and continuously learn and improve.

You don't need to build these systems from scratch; platforms like HubSpot and Salesforce have built the underlying capabilities. The work now is to design the right architecture for your business, implement it thoughtfully, and continuously optimize it based on data.

Brands need to treat lead nurturing as a strategic system that combines AI, automation, and human insight to move leads through the funnel efficiently and effectively.

Until next time, keep exploring the horizon. 🌅

Alex Lielacher

P.S. If you want your brand to gain more search visibility in Google AI Mode, ChatGPT, and Perplexity, reach out to my agency, Rise Up Media. We can help you with that!