How to increase revenue

 

When I coach CEOs on growth, I start with one formula:

Because you can grow revenue without touching your pricing.

3x your leads
1.7x your win rate
2x the average size of client accounts

3 × 1.7 × 2 = 10.2x growth

A $2M business becomes a $20.4M business.

5 ways to grow revenue while keeping prices steady:

1. Focus on your best customers
↳ Best-fit clients close faster and stay longer.
↳ Define your top customer profile. Move pipeline effort toward that group.

2. Fix your sales conversion
↳ Audit your last 20 lost deals.
↳ Find the #1 reason they stalled. Fix that first.

3. Keep more customers
↳ Bain & Company found a 5% lift in retention can raise profit 25% to 95%.
↳ I tell CEOs the renewal decision gets made in the first 90 days.

4. Grow existing accounts
↳ The trust is already there.
↳ Review your top 20 customers.Find one more problem you can solve.

5. Build a referral engine
↳ A Wharton study of a German bank found referred customers were worth 16% more.
↳ Ask your 10 happiest clients for one intro.

Start where you’re leaving the most money on the table. Then work through the rest.

Which of these five do CEOs overlook most?

https://lnkd.in/p/d8vhafdk

Get More Out of Your Work Experience

 

You've spent years making yourself valuable at work.
But are you getting the full value of that experience?
Here's what we want you to consider:

We see talented people spend years learning, solving problems, and becoming the person everyone turns to when something goes wrong.

Yet when they want something more, they assume they need to start from zero.

A new degree. A new job. A completely new skill.

But what if the most valuable thing you could build your future around is something you've already done a hundred times?

Think about it.

That spreadsheet you built to save hours? Someone else might pay for the template.

That process you've explained to 20 coworkers? Someone else might pay for the guide.

That problem you solve without thinking? Someone else might still be struggling with it.

𝗧𝗵𝗲 𝘄𝗼𝗿𝗸 𝘁𝗵𝗮𝘁 𝗳𝗲𝗲𝗹𝘀 𝗼𝗿𝗱𝗶𝗻𝗮𝗿𝘆 𝘁𝗼 𝘆𝗼𝘂 𝗺𝗶𝗴𝗵𝘁 𝗯𝗲 𝗶𝗻𝗰𝗿𝗲𝗱𝗶𝗯𝗹𝘆 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲 𝘁𝗼 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝘄𝗵𝗼'𝘀 𝗻𝗲𝘃𝗲𝗿 𝗱𝗼𝗻𝗲 𝗶𝘁.

And that's the part we want more people to recognize.

You don't always need to learn something new to create a new opportunity.

Sometimes you need to look at what you already know through someone else's eyes.

Start small:

• Write down 3 problems you solve at work.
• Find people who struggle with those problems.
• Share one useful solution on LinkedIn.
• See what questions people ask you next.

Those questions can reveal what people actually need.

And that knowledge could become a guide, a service, a workshop, or even your own business.

We put together this infographic to help you recognize the opportunities hiding in your everyday experience.

And if you're sharing your knowledge on LinkedIn, there's another question worth asking:

Is your profile actually turning that experience into business opportunities?

Get your free LinkedIn audit and find out in just 2 minutes.

🎤 Is your LinkedIn actually bringing in business?
Get a free audit and find out in 2 minutes.
➡️ Grab yours: https://tally.so/r/BzDW5A

https://tinyurl.com/mv5ay53m

Layers of AI Complexity

 

Your company is probably paying for the same AI three times.
The fix is the one layer nobody demos.
⠀
Every AI roadmap wants to reach Layer 8 below.
The companies that get there know when each layer is ready to build on.
⠀
LAYER 8: GOVERNED AUTONOMOUS AI
AI runs work across departments, and every decision can be traced.
Ready when: you can explain any AI decision to an auditor in minutes.
⠀
LAYER 7: PRODUCTION AI PLATFORM
Shared monitoring, cost control, access rules and testing for every AI tool.
Ready when: a new AI use case can launch on it without a new build.
⠀
LAYER 6: MULTI-AGENT SYSTEMS
Specialist agents split a job, and a supervisor agent coordinates them.
Ready when: you can see which agent did what, and why.
⠀
LAYER 5: STATEFUL AI AGENTS
The AI remembers, plans several steps ahead, and acts toward a goal.
Ready when: the steps that matter still require a person's approval.
⠀
LAYER 4: TOOL-USING AI
The AI takes action: searching, updating systems, triggering workflows.
MCP (Model Context Protocol) is the standard plug that connects it to those tools.
Ready when: it can only touch the systems it has permission to use.
⠀
LAYER 3: RAG AND KNOWLEDGE SYSTEMS
RAG (retrieval-augmented generation) is open-book AI.
It answers from your documents and shows where each answer came from.
Ready when: people can open the source behind every answer.
⠀
LAYER 2: LLM APPLICATIONS
A large language model (LLM) built into a product, with set instructions and guardrails.
Ready when: someone owns those instructions and tests every change to them.
⠀
LAYER 1: PROMPT-BASED AI
People type a question, copy the answer, and check it by hand.
Ready when: you know which tasks people repeat often enough to automate.
⠀
Here's the pattern I'd add from the field.
⠀
Layers 5 and 6 demo beautifully.
Layer 7 has no demo, so it gets funded last.
⠀
I've watched what follows.
One team builds an internal document search. A second team builds its own.
Then a third, because neither of the first two was designed to be shared.
⠀
Three versions of Layer 3. No Layer 7 to connect them.
The company paid for the same thing three times, and none of it could be shared.
⠀
How to use this on your next AI proposal:
→ Find the layer it sits on.
→ Read every "ready when" line beneath it.
→ Anything not yet true is the work to fund before the agent.
⠀
An agent is only as reliable as the least-ready layer under it.

Visual Credit: Rathnakumar Udayakumar

https://lnkd.in/p/dPnK4Fkr

12 Problem-Solving Techniques

 

I've seen founders bleed revenue for the same reason.

They were solving the wrong problem.

A retention issue needs a different fix than a bottleneck.
A trust problem looks nothing like a scaling constraint.

Treating them the same is exactly why people stay stuck.

The best operators I know reach for the right tool for the right problem.

Here are 12 I swear by:

1️⃣ Root Cause Analysis:
Most problems have a problem underneath them.

Ask why 5 times before you decide anything.
Solve the problem underneath the problem.

2️⃣ First Principles Thinking:
Stop copying what worked for someone else.

Strip back every assumption,
and rebuild from what you know to be true.

3️⃣ Reverse Thinking:
Work from the end, not the beginning.

Start with the outcome you most want to avoid.
Work backwards from there.

4️⃣ The Pre-Mortem:
Most launches fail for reasons you could have caught early.

Before any launch, assume it fails.
Map the most likely reasons why and fix them first.

5️⃣ Scenario Planning:
Single-source strategies are fragile.

Build 3 versions of what happens if your top traffic source disappears.
If you have no answer, that's the problem.

6️⃣ The Impact vs. Effort Matrix:
Not every problem deserves equal energy.

High-impact, low-effort moves first.
Plot your to-do list on a grid and cut or delegate the bottom half.

7️⃣ The Trust Audit:
Most bad partnerships were avoidable; you just didn't ask the right questions upfront.

Before signing anything, verify 3 things:
Does this person have a real audience, do their followers trust them, and does their brand align with yours?

8️⃣ The Loyalty Check
Retention is built between the deals.

When did you last reach out to a top partner with no agenda?
If you can't remember, you already have a retention problem.

9️⃣ The Stability Test
A fragile program looks like growth until it doesn't.

Find out what happens to your revenue
if your top 3 partners stop promoting tomorrow.

🔟 The Bottleneck Finder
You can't scale past your weakest link.

Most scaling problems are people and process problems.
Find the one constraint slowing everything else down and fix it.

1️⃣1️⃣ The Right Room Filter
Your time is the one thing you can't get back.

Before any commitment, ask whether it gets you closer to your top 3 goals.
If not, you know what to do.

1️⃣2️⃣ The Relationship ROI Review
The best opportunities rarely come from where you expect.

Every quarter, look at where your best opportunities and revenue came from.
Double down there.

The founders who scale consistently are the ones who know exactly which lever to pull when something breaks.

Build that instinct, and the problems stop feeling so heavy.

Credit to Amber Spears, make sure to follow!

https://tinyurl.com/3hvjbfkp