How Avoca built an AI-native ABM machine across its sales cycle

See how Avoca uses 3 AI-native ABM workflows to open accounts, turn discovery calls into business cases, and explain complex proposals.

Ploy13 min read

When Avoca first started working with Ploy, they thought Ploy would be a great cold outbound tool for its SDR team.

That ended up being wrong in the best possible way.

Avoca’s AEs started using Ploy after discovery calls. Then they brought it into late-stage proposals. Before long, the team was using personalized pages from the first touch through the final stretch of a deal.

Jack Gashi, Avoca’s VP of Sales, put it plainly during our recent webinar:

“Ploy has gone from being a point solution toward cold outbound for us to part of pretty much every step in the process as we go through a deal.”

Avoca sells AI products to service businesses, including companies in HVAC, plumbing, and electrical. Its annual contracts range from roughly $20K into the millions. That range makes the company an interesting test case for account-based marketing.

Historically, ABM was reserved for the accounts that could justify weeks of planning across sales, marketing, and RevOps. Jack had seen programs where several teams needed to agree on targeting, creative, and execution before anything went live.

AI has compressed that process enough that one AE can now give a $30K opportunity the kind of thoughtful treatment that used to be reserved for a seven-figure account.

The result at Avoca is a practical AI-native sales cycle built around 3 plays:

  1. Crack open an account with a deeply researched, interactive page.
  2. Turn a discovery-call transcript into a buyer-facing business case.
  3. Package a complex late-stage proposal so every stakeholder can understand it.

Here is how each one works, what Avoca learned, and where the team still keeps a human firmly in the loop.

Prefer YouTube? Watch the full webinar recording.

Table of contents

Why this version of ABM works now

Jack describes ABM as targeted, high-level outreach to executives and premium accounts. The old-school versions could include a billboard near a prospect’s headquarters or a bespoke campaign for the few accounts that could change the quarter.

AI changes the economics. One AE can now handle research, strategy, copy, and page creation through a single workflow. That makes the approach viable for opportunities where several planning meetings and a custom creative project never would have made sense.

The timing matters too. AI writes more outbound, AI filters more outbound, and buyers ignore messages that look like every other sequence. A thoughtful account page is still unusual. It lets buyers follow the seller’s thinking at their own pace and share it internally.

Jack calls this a “high-alpha zone.” The opening will not last forever, but teams that combine good targeting, taste, and account knowledge have room to stand out now.

Play 1: Crack open an account

The first play was the use case Avoca initially brought Ploy in for: cracking open a target account with a bespoke page. Instead of asking an SDR to compress the entire pitch into a cold email, Ploy helps the team turn account research into a tailored story the buyer can explore and share.

Start with some smoke

Avoca looks for a reason to reach out, such as a first-party website visit, product activity, CRM score, intent signal, or referral. The company is investing in signal-based targeting, but Jack says the team still operates more like snipers than a machine firing at the whole market.

A beautiful page will not rescue weak targeting.

To apply this play on your own team:

  1. Choose the signals that justify an AE’s attention, such as a website visit, product activity, an intent spike, or a referral.
  2. Route each signal to the person who owns the account.
  3. Ask the AE to write down why the signal matters now and which business priority it may connect to.

That gives the research a clear starting point. Instead of producing a generic company summary, the workflow can investigate a specific reason to believe the account may be ready for a conversation.

Build the brief before the page

A useful account brief connects the prospect’s world to the seller’s offer. It answers 3 questions:

  1. What is the company trying to accomplish?
  2. What could get in the way?
  3. Which part of Avoca’s product portfolio could help?

The research can draw from executive statements, press coverage, company reports, and social content. The brief then helps the AE choose which Avoca products belong in the story.

By the end of this step, the AE should be able to explain why this account is worth contacting now, what the company appears to be working toward, and where Avoca may fit. If the brief cannot answer those questions, there is not enough material to build a useful page yet.

Give the buyer the whole story

Ploy turns the brief into an account page inside Avoca’s brand. Jack described it as “the whole boat in one scrollable page.” It can include the value proposition, relevant products, visuals, and an ROI calculator where the buyer enters their own numbers.

Jack finds the format easier to consume than a Loom. An executive can open the page during a meeting, scan it at their own speed, and return later. He called it a new genre: better than a cold email and more approachable than short-form video.

Interactive pieces move the experience from a polished pamphlet toward a small, self-guided demo.

Review it, send it, and watch the account

The AE checks the research, removes weak claims, adjusts the positioning, and decides whether the page is good enough to send. Ploy gives the team a high design floor and ensures that what Jack called “vibe-coded slop” does not leave the building.

After the send, the page creates another signal. Repeat visits or activity from people who never received the original email can show that the experience is moving through the account.

When Avoca sees a page being forwarded or opened by additional people, Jack says the team knows it has “struck a nerve.” The page delivers the pitch and helps the AE decide where to spend time next.

Play 2: Turn discovery into a business case

This became the use case Avoca’s AEs were most excited about.

Before Ploy, Jack built a simple Claude project where an AE pasted a discovery-call transcript and received 5 or 6 outputs, including missed questions, the shape of a business case, and a suggested follow-up email. It caught on because it was easy.

About 6 months later, Avoca connected the same idea to Ploy and its call-recording system.

Turn the call into something the champion can use

Many Avoca buyers are business owners who know their operations deeply and bring real numbers into the first call. Ploy turns the transcript into one place that captures their current process, pain points, goals, numbers, proposed approach, open questions, and next steps. The AE can send that page back to the buyer as a shared record of the conversation and something useful to forward to their team.

For another team setting up this workflow, the test is whether someone who missed the call can understand and share the page without the AE filling in the gaps. Before the page goes out, check that it:

  • Explains the buyer’s current process in plain language
  • Shows where the numbers came from
  • Connects the proposed approach to the buyer’s goals
  • Calls out open questions instead of filling the gaps with assumptions
  • Makes sense to someone who was not on the discovery call

Let the page become the hub for the deal

The first version starts with the discovery transcript, but it does not stay frozen. As the deal progresses, the AE keeps adding context to the same page, including:

  • Operating metrics from the buyer
  • Spreadsheets or other supporting files
  • New stakeholders and what matters to them
  • Decision criteria and implementation constraints
  • Updated questions, assumptions, and next steps

That gives the buyer and the Avoca team one place to return to as the conversation develops. They do not have to reconstruct the deal from call recordings, email threads, and separate spreadsheets.

The gaps are useful too. If the page is missing a baseline metric, stakeholder, decision criterion, or implementation constraint, the AE knows what to ask about on the next call. Jack says this feedback has helped his team improve its discovery conversations.

When a version gets a strong response, other reps ask for the Ploybook and adapt it. Avoca now has a small set of standard structures that start from a transcript while leaving the buyer details and seller judgment fresh.

Play 3: Give a complex deal one clear system view

By the late stages of an enterprise deal, Avoca has accumulated details across calls, emails, technical discussions, spreadsheets, and internal notes. The buyer now needs to see how Avoca’s AI voice technology would fit into their existing telephony and operating systems.

Avoca uses Ploy to turn that context into a deal-specific system view. The page can show:

  • How the buyer’s current systems work together
  • Where Avoca fits into that environment
  • Which APIs and integrations are involved
  • What changes during implementation
  • Who owns each part of the rollout
  • Which questions still need an answer

The goal is to save the buyer from translating a general proposal into their own environment. The CEO can understand the plan without decoding a technical document, while the implementation team still gets the detail it needs.

About an hour after receiving the finished page, the CEO emailed back: “This looks excellent. Let’s get on the call as soon as possible.”

Match the effort to the opportunity

Avoca does not put every deal through the same production process. The team adjusts the depth of the page to the size and complexity of the opportunity:

  • Standard opportunities: Start with a repeatable Ploybook and produce the first version quickly
  • Large or complex opportunities: Spend more time refining the system view, implementation plan, visuals, and business case

For a $500K or $1M opportunity, Jack is comfortable giving the team a few days to “Picasso” the page. Ploy handles the repeatable parts of the workflow so the AE can spend that time checking the details and shaping the proposal around the deal.

How Avoca got sales to adopt Ploy

Jack does not expect every rep to adopt AI in the same way or at the same speed. His approach gives the team two kinds of support:

  • Foundation model credits give curious reps room to explore, test ideas, and find new uses on their own
  • Workflow tools like Ploy turn the uses that work into repeatable processes the rest of the team can run

The early adopters help decide what should become a standard workflow. Avoca’s adoption loop looks like this:

  1. Give an interested rep room to test an idea on a live deal
  2. Ask them to share the page and the buyer’s response in the AE channel, not only in a private message
  3. Turn repeated wins into a Ploybook another rep can copy and adapt
  4. Pair the early builder with an executive who can remove blockers and support a broader rollout

At a smaller company, this can stay informal. A few motivated reps can test and validate new workflows before the rest of the team adopts them. As the company grows, the work may need a clear owner. Jack eventually moved one of Avoca’s most active AI users from an AE role into AI ops so he could help the rest of the sales team build and improve these workflows.

How far should you automate the motion?

The technology can create pages for 100, 1,000, or 10,000 accounts. That does not mean it should.

For Jack, the point of automation is to give salespeople more time in front of customers. He has tested this strategy with roughly 200 high-intent account experiences and is seeing results. Part of the value is that each buyer feels like the seller spent time thinking about them, so Avoca is scaling the motion carefully:

  1. Get the targeting, research, and page quality right
  2. Confirm that the pages lead to meetings and deal movement
  3. Increase volume without losing the care that made the experience work

Will summarized the risk well:

“If it’s not effective, you’re just going to make yourself worse faster and cheaper.”

How to build your own AI-native ABM machine

Avoca’s system grew through experimentation, but the pattern is straightforward:

1. Pick one stage

Start with a repeated job that already causes friction, such as researching a warm account, creating a discovery follow-up, or explaining a complex proposal. Prove one play before taking on the whole revenue process.

2. Use real inputs

Feed the workflow CRM data, first-party signals, call transcripts, buyer spreadsheets, public research, and product information. Generic inputs produce a generic asset.

3. Give the page a job

Decide what the buyer should understand or do after opening it. The page might help them explore an ROI model, share a business case, or understand how a technical system fits together.

4. Keep human review

Have the AE check every claim, number, recommendation, and visual before delivery, especially during the first runs.

5. Share and systemize the wins

Post successful pages and buyer responses in a shared channel. Once a structure works across several deals, turn the repeatable parts into a Ploybook while keeping the account research and seller judgment fresh.

Final thoughts

Avoca did not begin with a mandate to automate ABM. It started with a cold outbound idea, put the system into the hands of creative AEs, and followed the uses that helped real deals move. Those uses now span the sales cycle, from opening an account with a researched page to building the business case and explaining a complex proposal.

Across each play, Avoca starts with a real signal, uses the buyer’s information, reviews the work, and shares successful examples with the team. Ploy handles more of the production, leaving sellers more time to choose the right accounts, understand the problem, and build trust. Avoca scales each workflow only after it proves useful on real deals.

Watch the full AI-native ABM webinar or see how Ploy supports account-based marketing.

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