Signed in as:
filler@godaddy.com
Signed in as:
filler@godaddy.com
AI was exploding.
Customers wanted to talk about it. Leadership saw the opportunity. The technology and solutions existed.
But there was a problem.
The sales organization knew the products. They didn't necessarily know how to translate those products into meaningful AI conversations across industries like manufacturing, retail, transportation, supply chain, state and local government, and education.
A sales leader came to me with a straightforward challenge:
So that's what I built.
The organization had already invested heavily in educating sellers about the technology.
They understood servers.
They understood storage.
They understood networking.
They understood the products and, at varying levels, the technical capabilities behind them.
But customers weren't necessarily asking:
“Which server should I buy?”
They were trying to understand how AI could improve manufacturing, modernize a supply chain, support public services, improve retail operations or change the way their organization used data.
That required a different sales conversation.
Generalist sellers were particularly hesitant.
They had strong relationships with their customers and were comfortable discussing the solutions they knew well. But AI and data-center infrastructure felt more technical, more complicated and outside their normal lane.
The knowledge gap was creating a confidence gap.
The answer wasn't to turn every salesperson into an AI engineer.
And it wasn't another product-training deck.
The sellers needed enough industry context, business understanding and practical guidance to confidently start the conversation.
They needed to know:
and critically:
That changed the objective. We weren't trying to make every seller the expert.
We were giving them enough clarity to open the right door.
I designed an industry-specific AI sales playbook covering approximately eight priority vertical markets.
Rather than starting with individual products, each section started with the customer's world.
What was changing in the vertical, where AI was gaining traction and the business problems organizations were trying to solve
I designed an industry-specific AI sales playbook covering approximately eight priority vertical markets.
Rather than starting with individual products, each section started with the customer's world.
What was changing in the vertical, where AI was gaining traction and the business problems organizations were trying to solve.
Practical examples of how AI and modern infrastructure could improve productivity, performance and business outcomes within that industry.
Questions sellers could use to understand the customer's environment, priorities, challenges and potential AI opportunities.
Words, needs and customer comments sellers could listen for that indicated where the conversation should go next—and which specialist should be involved.
Instead of saying “sell this server,” the playbook connected the larger solution.
Compute. Storage. Networking. Software. Infrastructure.
Sellers could understand how the pieces worked together to support the customer's intended outcome.
Baseline solution configurations gave teams a practical starting point for discussing and developing opportunities without pretending every customer needed the same thing.
One playbook wasn't enough.
Generalist sellers needed something accessible. They needed enough information to recognize an opportunity, ask intelligent questions and confidently bring the right specialist into the conversation.
Technical sellers needed more depth.
So I created two versions of the playbook.
The generalist version emphasized:
In
One playbook wasn't enough.
Generalist sellers needed something accessible. They needed enough information to recognize an opportunity, ask intelligent questions and confidently bring the right specialist into the conversation.
Technical sellers needed more depth.
So I created two versions of the playbook.
The generalist version emphasized:
Industry → Business problem → Use case → Questions → Trigger → Handoff
The technical-sales version went deeper into:
Solution architecture → Products → Infrastructure → Technical considerations → Configuration
Same customer conversation. Different levels of depth.
And a clear connection between the two teams.
The playbook became a reference for sellers and leadership and was used alongside AI-focused marketing programs and customer opportunities.
More importantly, the conversations changed.
Generalist sellers didn't need to stop at:
“I don't know enough about AI.”
They had somewhere to start.
They could recognize an opportunity. Ask the first que
The playbook became a reference for sellers and leadership and was used alongside AI-focused marketing programs and customer opportunities.
More importantly, the conversations changed.
Generalist sellers didn't need to stop at:
“I don't know enough about AI.”
They had somewhere to start.
They could recognize an opportunity. Ask the first questions. Listen for the right signals.
Bring in the right specialist. And keep the customer conversation moving.
Technical sellers weren't entering cold either. They had context around what had already been discussed and a framework for taking the conversation deeper.
In some cases, that progression could move from an initial conversation to the appropriate technical resource and into solution development or quoting within a short period of time.
The organization saw increased pipeline around these solutions as the teams began having more productive AI conversations.
I don't have a defensible pipeline number today, and I'm not going to invent one. The more important result was visible in the behavior of the team. Sellers who had previously been hesitant to enter these conversations now had a way in. Generalists and specialists had clearer roles. Customer conversations became easier to advance. Leadership had a common reference point for coaching teams.
And the organization had a repeatable framework it could use across multiple industries rather than expecting every seller to figure it out independently.
They knew enough to confidently start the right conversation—and how to bring in the right person to finish it.
Traditional product training answers:
“What does this product do?”
Customers don't always care.
They want to know:
“What can this do for my business?”
The playbook connected those two questions.
INDUSTRY
↓
BUSINESS PROBLEM
↓
USE CASE
↓
DISCOVERY
↓
SOLUTION
↓
RIGHT EXPERT
↓
OPPORTUNITY
Instead of asking sellers to memorize more technical information, we gave them context for using the information they already had.
That created something much more useful:
Looking back, this work reflects another principle that eventually became part of how I think about MomentumOS:
People struggle to execute when they don't understand what good looks like, what they're responsible for or what they're supposed to do next.
Give them clarity and behavior changes.
This playbook also connected pieces of the organization that already existed:
The individual pieces were already there. The playbook gave them a clearer way to work together.
That's MomentumOS thinking.
Not another process for the sake of process.
Clarity. Alignment. Execution.
Sometimes the problem isn't your people.
They may simply lack the process, tools or clarity needed to confidently execute.
An Opportunity Snapshot can help identify where those gaps exist and what I'd address first.
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