Building an End-to-End AI Sales Engine in HubSpot

Chapter 1: Webinar Introduction​

Miles England: Thank you everybody for being here. Today, we are talking about building an end-to-end AI sales engine in HubSpot.

To get started, I want to ask a simple question. How many of you are already paying for AI tools inside HubSpot that your team has not fully turned on or operationalized yet? Are they actually using them?

That has become one of the most common conversations we are having. Every company is being told to adopt AI. Pipeline goals are increasing. Teams are being asked to do more with less. Organizations already have powerful AI tools available, but they are not always using them in a connected way.

That is what this webinar is about.

This is not going to be an hour of AI theory or predictions about the future. Instead, we are going to show you what an AI-powered revenue engine actually looks like inside HubSpot today.

You will see how companies are increasing visibility in AI search, capturing and qualifying website visitors, generating pipeline, and converting that interest into legitimate booked meetings.

Most importantly, you will see how all of these pieces connect together. Individually, these tools are interesting. Connected, they become an actual revenue engine.

Chapter 2: Who We Are: About Vonazon

For those who do not know us, Vonazon is a full-service, AI-enabled HubSpot Elite Solutions Partner.

We have completed more than 3,000 implementations, supported thousands of onboarding engagements, and helped more than 5,000 customers get more value from HubSpot.

What makes us unique is that we work across the entire customer journey, from marketing to sales, service, operations, integrations, AI adoption, and helping companies connect everything into one revenue system.

Chapter 3: Who You’ll Hear From + What We’ll Cover

Today, we will walk through that single revenue journey.

I will start by introducing Answer Engine Optimization, or AEO, and why AI visibility matters more than ever.

Chloe will then show how companies are using AEO to drive qualified traffic.

Sheena will demonstrate Customer Agent and how businesses are capturing intent from website visitors in real time.

Sabrina will show how Prospecting Agent turns those signals into pipeline.

Will from Aloware, our partner, will demonstrate how AI voice and SMS help convert opportunities into booked meetings.

By the end of today’s session, you will see how all of these tools work together as one connected revenue system.

Chapter 4: AEO Introduction

Let’s start with where the modern buying journey begins: visibility.

Buyers are not only using Google anymore. They are opening ChatGPT, Gemini, Perplexity, Claude, and asking questions like, “Who are the best HubSpot partners?” “Who knows the best integrations?” “What solution should I be considering?” and “How should my pipeline be configured?”

AI is now influencing who makes the shortlist before a buyer ever visits a website.

That means if your company is not showing up in those conversations, you may be missing opportunities before you even know they exist.

That is why AEO matters.

Chapter 5: The End-to-End AI Sales Engine Framework

Everything starts with visibility. You need to show up where buyers are asking AI for answers.

Once they arrive, Customer Agent engages visitors and captures intent. Those intent signals help identify the right opportunities. Prospecting Agent turns those opportunities into pipeline, and Aloware’s Conversion Agent helps transform that pipeline into conversations, meetings, and revenue.

The key takeaway is simple. The future is not about having more AI tools. It is about connecting AI tools together to create better business outcomes.

That is what an end-to-end AI sales engine is all about.

Chapter 6: Set the Foundation for AI Visibility

This starts in HubSpot.

Your brand kit, company profile, products and services, ideal customer profile, buyer personas, and positioning all help AI understand who you are and who you serve.

Without that foundation, visibility becomes difficult. With it, AI can begin recommending your business to the right buyers at the right time.

Chapter 7: HubSpot Foundation Demo

Demo note: In this section, Miles demonstrated where AI data sources and brand information now live inside HubSpot, including Breeze, Context, Brand Kit, company profile, ideal customer profile, and products and services.

The key point is that AI visibility starts with clean, complete foundational data. HubSpot needs accurate information about your business, your customers, your positioning, and your services in order to support tools like AEO, Prospecting Agent, and Customer Agent effectively.

Filling out these areas properly helps HubSpot’s AI understand your company and use that context across the AI-powered tools discussed throughout the webinar.

Chapter 8: AEO Strategy + Real-World Results

Chloe Papke: When is the last time you Googled your own brand?

Now, when is the last time you asked ChatGPT about it?

Those are two very different answers. For most businesses right now, only one of them is actually shaping whether a buyer puts you on their shortlist.

Two years ago, your buyer’s journey started with a Google search. They clicked a few links and maybe found you. That was the game.

That game is very different now.

Organic traffic has declined year over year. A large percentage of Google searches now end without a single click. Millions of people are using AI tools every week to research products, vendors, and business solutions.

Here is what most people miss. The average Google search is three words. The average prompt typed into an AI tool is 25 to 30 words.

That is a completely different kind of buyer. They are not browsing. They are researching with full context.

They are asking questions like, “What is the best CRM for a fast-growing sales team that needs better marketing alignment and has a RevOps function?”

And they are getting a direct answer back with brand recommendations already included.

Visitors who land on your site from an AI referral convert at a significantly higher rate than organic traffic. These are not casual browsers. These are buyers who already trust you before they arrive.

The problem is that most companies have no idea whether they are showing up in those answers at all.

There is no Google Search Console for AI. You cannot easily rank-check it. Most companies are completely blind to their own visibility.

HubSpot tested this on itself first. They tracked their own AI visibility, identified which content was getting cited, adjusted their strategy, and saw a major increase in qualified leads from AI.

The tool they built to do that is what we are walking through today.

Before we jump in, there is one thing that reframes everything.

When someone asks an AI tool to recommend a product, it is not just reading your website. It is pulling from earned media, peer review sites, Reddit threads, YouTube, competitor sites, third-party blogs, and yes, your own domain.

Your own website typically makes up only a small portion of the citation mix. That means most of your AI visibility is happening on sites you do not own, in conversations you did not start.

The brands winning in AI search are the ones with the broadest, most credible presence across all the places AI actually looks.

Chapter 9: AEO Visibility Demo

Demo note: In this section, Chloe demonstrated HubSpot’s AEO dashboard using HubSpot.com as the example brand.

She walked through brand visibility, sentiment analysis, competitor landscape, prompt-level visibility, citation analysis, and recommendations.

The demo showed that even a highly recognized brand like HubSpot can have AI visibility gaps. HubSpot showed strong visibility overall, but certain early-stage problem-aware prompts had very low visibility.

That matters because those are the prompts buyers ask before they search for a specific brand or solution.

Chloe also showed that competitor domains, peer sites, Reddit, LinkedIn, blogs, listicles, and guides can all influence which brands appear in AI-generated answers.

The AEO dashboard helps diagnose three core types of gaps:

A content coverage gap means you do not have content addressing certain prompts at all.

A format gap means you may have content, but not in the formats AI prefers to cite.

An authority gap means your own domain is thin and third-party sources are not picking you up either.

The recommendations section then turns that analysis into prioritized action. Instead of guessing what content to create, the platform shows what sources are already being cited, which prompts they are tied to, and what actions can help improve visibility.

Once new content is published, HubSpot can track how often that URL gets cited in future AI responses.

That creates a measurable loop from visibility gap to recommendation, from published content to citation impact.

Chapter 10: AEO Strategy Takeaway

The biggest takeaway is that even HubSpot, one of the most recognized brands in CRM, has visibility gaps in AI search.

If that is true for HubSpot, it is worth asking what your own brand visibility looks like if you have not checked yet.

Teams that are getting results from AEO are treating it as a content operation system. They have clear prompt strategies organized by buyer stage, regular citation reviews, and recommendations that are actually executed across the channels AI trusts.

The teams that do not see results are usually the ones that set it up, looked at the score once, and did not know what to do next.

Data without interpretation is just noise. The gap between having the tool and having a strategy is exactly where Vonazon works with clients.

Miles England: One question I know a lot of clients would ask is whether AEO is ongoing or a one-time setup.

Chloe Papke: It is definitely ongoing. AI models are shifting constantly. Competitors adapt. New prompts emerge. Visibility compounds over time.

The brands being cited today become harder to displace six months from now. But brands that stop investing in visibility can lose the ground they built.

Chapter 11: Customer Agent + Buyer Intent Capture

Sheena Heppern: Today, I am going to discuss Customer Agent, Buyer Intent, and how they work within the revenue platform.

Every company has a target audience, but it is difficult to measure activity and turn marketing and sales engagement into actionable tasks.

Buyer Intent identifies who is ready to engage. Customer Agent determines how to engage them.

Within HubSpot, these tools can show interest in your product, which companies to pursue, and where there may be opportunities to grow product or service awareness.

This is about being proactive.

Once you have optimized your company with the AEO tool, the Buyer Intent module in HubSpot is an area marketers and sales teams should be reviewing regularly. It helps identify research activity and visitor activity so you can see which accounts are showing interest now.

Buyer Intent identifies demand. Customer Agent captures and converts that demand.

Customer Agent provides the inbound engagement and conversation experience for your visitors. Together, Buyer Intent and Customer Agent create a full-cycle, AI-assisted revenue system.

Chapter 12: Every Question is an Intent Signal

Customer Agent is not just a support tool. It is a revenue growth tool when used correctly.

The big idea is that every customer and prospect question is a revenue moment.

When someone asks about integrations, support, features, pricing, delivery, or product fit, that is intent. Customer Agent helps close the gap by answering questions instantly with approved business content.

This is not a predetermined flow. It listens to the contact or visitor and responds with the appropriate information.

Customer Agent handles repetitive conversations so your team can focus on higher-value inquiries.

HubSpot has reported that Customer Agent already resolves a large percentage of conversations and reduces resolution time across thousands of active customers.

This creates a clear business case for faster answers, fewer repetitive tickets, better conversion from high-intent visitors, and more time for sales and service teams to focus on complex revenue-generating conversations.

Chapter 13: Customer Agent Demo

Demo note: In this section, Sheena demonstrated Buyer Intent and Customer Agent using a fictional company called The Plant Company.

The demo showed how Buyer Intent can identify target markets, addressable companies, visitor activity, page engagement, and available contacts.

She then demonstrated how Customer Agent can answer visitor questions using approved business content, including website pages, product information, sales resources, and other knowledge sources.

The Customer Agent answered questions about product options, shipping, pricing, and delivery. When it could not fully answer a question, the system showed how a handoff process can connect the visitor with a live sales or support representative or provide a meeting link if a person is not available.

The demo also showed how a sales team member can view the full conversation history and use that context to continue the conversation.

If a visitor demonstrates serious buying intent, HubSpot can automatically create a deal for the salesperson based on trigger criteria.

The key point is that Customer Agent can capture intent, qualify interest, support a seamless handoff between service and sales, and equip the sales team with the context they need to move the opportunity forward.

Chapter 14: Three High-Impact Use Cases for Customer Agent

The biggest use cases are converting high-intent visitors, identifying expansion opportunities, and creating a seamless interaction between service and sales.

Pricing questions, product questions, demo requests, and support conversations all provide valuable signals.

Customer Agent can help qualify and route visitors, notify the right team, and book meetings faster.

Miles England: When it comes to the information Customer Agent knows, where is it getting its data?

Sheena Heppern: The data is compiled by the team. You can use sales resources, websites, blog posts, product information, and other approved materials to train it.

There is also an opportunity to coach the agent based on questions people ask that it cannot answer. You can continue updating the knowledge base so it answers questions more effectively over time.

Chapter 15: Prospecting Agent

Sabrina Marshall: Sheena showed us how AI can help capture and respond to intent across the customer journey.

Now I want to show what happens when your sales team needs to turn signals and account context into pipeline.

That is where Prospecting Agent comes in.

It helps your team identify which accounts deserve attention, understand why they matter right now, and generate outreach that gives reps a stronger starting point.

This is not a template library or a sequence builder. HubSpot positions Prospecting Agent as an always-on AI sales BDR.

The Spring Spotlight 2026 version is organized around plays.

A play is a prospecting motion. You define who you want to target, which signals matter, and how outreach should happen.

From there, the agent helps prioritize accounts, explain the reasoning, and generate outreach your team can review and refine.

Chapter 16: What Changed in Spring 2026

Spring Spotlight 2026 introduced a complete rebuild of Prospecting Agent, not just a feature update.

There are four major changes.

First, smarter buying signals. The agent now surfaces high-priority accounts based on signals like growth metrics, executive hiring, physical expansion, funding, mergers and acquisitions, and more.

Depending on your setup, teams can also bring in context like hiring trends, leadership changes, technology adoption, website engagement, CRM engagement, and other indicators that suggest a company may be entering a buying cycle.

Second, full lifecycle coverage. Prospecting Agent can help map the buying committee, identify stakeholders involved in a decision, and prepare your rep with context on recent activity, pain points, and why now is a good time to reach out.

That pre-call preparation is a big part of what makes the Spring 2026 version more useful for sales teams.

Third, deeper multi-channel outreach. Depending on what is enabled in your portal, Prospecting Agent can support call tasks, LinkedIn outreach, and automated email sequences.

The larger shift is that the agent can move from identifying an opportunity to recommending the next action.

Fourth, a new pricing model. You now pay for recommended leads, not ongoing monitoring. That makes the setup more outcomes-focused, and there is a 28-day free trial available to get started.

If you used Prospecting Agent before Spotlight, what you are about to see is a different tool.

Chapter 17: Prospecting Agent Demo

Demo note: In this section, Sabrina demonstrated Prospecting Agent using a fictional business called Plant People Company.

The demo company sells B2B wholesale houseplants and plant programs to offices, hotels, and commercial spaces.

The setup included a focused ICP: offices, hotels, and design firms creating or refreshing physical spaces.

The demo showed how to set up a play, define the audience, select the signals, review the reasoning, and act on outreach.

For Plant People Company, the play focused on companies entering a buying cycle tied to space planning, guest experience, hospitality growth, or design projects.

Inside the play, Sabrina showed how the agent can be given persona information, value propositions, pain points, and buying signals.

The target persona included roles like office manager, facilities director, hotel general manager, and hospitality manager. The value propositions included zero-maintenance guarantee, local delivery, hospitality and office expertise, a single reliable vendor model, curated plant subscriptions, and expert curation.

Pain points included maintenance burden, dead plants, finding reliable suppliers, and making a space feel welcoming.

Signals included growth metrics, executive hiring, mergers and acquisitions, physical expansion, funding, research intent, and geographic expansion.

The power of the tool comes from how these pieces work together. The agent is not reacting to one signal in isolation. It combines the signal with the persona, pain points, and value propositions you provide.

That context helps the sales team focus on accounts with a timely reason to engage instead of treating every prospect the same.

The demo then showed a contact named Emma Thornton, an office manager at Canopy Property Group. The agent prioritized the account because it identified a meaningful growth signal: Canopy had recently listed four new office buildings for lease.

That created a timely opportunity to outfit reception areas, common spaces, and tenant-facing environments.

The agent explained why the account deserved attention, what business event triggered the recommendation, and what outreach could be generated from that context.

This is where Prospecting Agent starts to feel different from a traditional prospecting tool. Instead of asking a rep to research the account, interpret the information, and decide what to do next, the agent brings those pieces together and recommends a course of action.

The email draft was built using the contact record, company context, buying signals, and the instructions provided in the play.

The rep still reviews and refines the outreach, but they are editing from a stronger starting point instead of writing from scratch.

The same idea applies to other contacts and use cases. Each contact can give the agent a different angle for prioritization and outreach.

For teams with more connected data, this can become even stronger. Website activity, forms, enrichment partners like Aloware, and additional buying signal sources can all add more context.

Chapter 18: Three Best Practices from Real Prospecting Agent Implementations

There are three best practices for using Prospecting Agent effectively.

First, set up your plays with intention. Vague criteria get vague outputs. Be specific about the signals that actually indicate buying readiness for your business.

Second, start simple and make the context useful. A focused play with a few strong signals is better than an overloaded play with weak criteria. Concrete details like expansion plans, new locations, or active projects give the agent something meaningful to work with.

Third, review the reasoning before you send anything. The reasoning tells you what the agent is using to make its recommendation, and that helps reps learn which signals are actually meaningful.

That is Prospecting Agent, rebuilt in Spring 2026 to help sales teams move from signal to action.

Miles England: One question I know clients would ask is whether reports can be set up to track the journey from Prospecting Agent activity through to the end goal of becoming a customer.

Sabrina Marshall: Absolutely. All Prospecting Agent activity is recorded on the contact record, so you can build reporting around the entire journey.

Chapter 19: Conversion Agent + Aloware

Will Scholl: My name is Will, and I am the Director of Product at Aloware.

Aloware is an AI-driven, fully compliant phone solution and a leading HubSpot technology partner with a deep and customizable integration.

Aloware dramatically increases speed-to-lead and connection rates. Today, I will show how we complete the sales engine discussed across the webinar.

AEO drove the traffic. Customer Agent captured intent. Prospecting Agent built the pipeline. But then the lead can sit. Reps get to it when they get to it, and by then, much of that intent may be gone.

Aloware uses the signals captured by Customer Agent and Prospecting Agent to trigger automated outreach in under 60 seconds while intent is still high.

Those calls also get answered because the numbers are verified and recognizable. Aloware’s branded calling displays your business name and logo on the buyer’s screen, similar to a saved contact.

When plugged into the engine we are building today, that means more connection with high-intent leads.

There are four key moments to watch for: trigger, talk, sync, and escalate.

Trigger and talk show how the outreach begins. Sync is the anchor point because it is the moment a conversation becomes structured HubSpot data automatically.

Chapter 20: Aloware Conversion Agent Demo

Demo note: In this section, Will demonstrated how Aloware can respond to high-intent behavior inside HubSpot.

The example workflow was based on a lead visiting the pricing page multiple times. The workflow evaluated fit score and triggered different actions depending on whether the lead was high, medium, or low fit.

For a high-fit lead, an Aloware AI agent placed a call in under 60 seconds.

For a medium-fit lead, the contact could be enrolled into Aloware’s Power Dialer so a human agent could reach out within the hour.

For a low-fit lead, Aloware could send an automated text message, with replies handled by an AI text agent.

The demo showed an AI voice agent calling Will after he visited the pricing page. The AI agent asked what he was interested in, whether he needed outbound sales, inbound support, or both, what phone solution he currently used, what pain points he had, what CRM he was using, and how many agents would need the solution.

The AI agent captured that Will was using RingCentral, that his pain point was having too many separate tools, that he was using HubSpot as his CRM, that he had about 10 agents, and that he was interested in both inbound and outbound calling.

The agent then discussed pricing options and helped schedule a demo earlier in the week.

After the call, Will showed how those answers were automatically written back into HubSpot as structured contact properties.

The fields included current phone solution, pain point, CRM platform, user size, pricing discussion, and use case.

The result is that the sales team can continue the conversation with the context already captured and organized inside HubSpot.

The key takeaway is that the conversation becomes data. Aloware helps close the loop by turning high-intent behavior into an immediate conversation and syncing the result back into HubSpot automatically.

Chapter 21: Key Takeaways

Miles England: I have to mirror one of the comments in the chat. Someone said they were impressed and a little scared at the same time because of how realistic the AI voice sounded.

Will Scholl: We hear that often. The quality has improved significantly over time. Even I am sometimes surprised when I receive a call from one of our newer models. It sounds very natural.

Miles England: Setup was also discussed in the chat. It looks like setup is about two hours. Would you agree with that?

Will Scholl: It depends on how much you want to configure. There are options that guide you into a simpler setup, but the sky is the limit in terms of how much you can add.

When you start talking about HubSpot properties and custom entities syncing into HubSpot, complexity can increase. The timeline depends on how complex you want the configuration to be.

Miles England: As we wrap up, I want to bring everything back to where we started.

This is not about individual AI tools. It is about connecting them so they work together across the customer journey.

Visibility starts when buyers use AI tools and platforms to research solutions and build shortlists. AEO helps ensure your company shows up in those conversations.

Once visitors arrive on your site, Customer Agent engages them, answers their questions, and captures intent in real time.

Those signals feed into Prospecting Agent, helping sales teams identify the right opportunities.

Finally, Aloware’s Conversion Agent helps close the speed-to-lead gap by turning interest into a meeting quickly.

When all of these pieces work together, you create a system that moves buyers from traffic to engagement, from engagement to pipeline, and from pipeline to revenue.

The biggest takeaway is that the future is not more tools. It is better business outcomes through connected AI systems.

That is what an end-to-end AI sales engine is all about.

Chapter 22: Audience Q&A

Question: What percentage of people answer the phone call?

Will Scholl: As shown earlier, answer rates drop dramatically after five minutes. Within that early response window, we see a much higher percentage of calls answered when the agent calls automatically.

Speed matters, and branded calling also helps because the call is more recognizable to the recipient. Together, those factors help improve answer rates.

Question: Can Aloware’s AI conversion agent close people over the phone, or can it only qualify them?

Will Scholl: The agent is designed to capture information and hand the conversation off to a real human.

As you saw in the demo, it captures information, updates HubSpot, and gives the closer the context they need. The AI agent starts the conversation, logs the information, and then passes it to a human for the next step.

Miles England: Thank you to all of our speakers today, including Will from Aloware, Chloe, Sabrina, and Sheena.

If you have additional questions, we will make meeting links available. You will also receive the recording and follow-up information after the session.

The most important thing is that we continue the conversation.

Thank you again for your time, and have a great rest of your day.