Will messy CRM data lower our valuation when we raise or sell?

Read Time: 5 Minutes

An investor asks for 5 numbers.

Your team says sure, give us a few weeks.

And the price of your company just dropped... before anyone opened a spreadsheet.

Short answer: Yes, when the buyer or investor is financial. They don't grade your dashboard. They time how long it takes you to send the numbers. If it takes weeks, they assume your leadership team doesn't run on data, and that risk comes out of the price.

This one comes from my podcast with Scott Stouffer. He's the founder and CEO of Scale Matters and on his 5th CEO stint, with 3 exits: 1 IPO, 1 sale to a strategic, and 1 sale to a PE firm. His first company, Visual Networks, grew from scratch to over $120M in annual revenue, went public in 1998, and hit a value north of $3B. He's also done 7 or 8 acquisitions, so he's sat on both sides of the table.

How do investors judge our data when we raise or sell?

They time you. Every company can pull the numbers in the end. What buyers watch is how long it takes. If you need 6 weeks, it proves your leaders never needed those numbers to run the business. If you send them the next day, it proves you run the company on data. Speed is the grade.

Scott sees this all the time. In his words, "the vast majority of sub thirty million dollar companies. They don't have great data."

So they scramble. They do backflips to pull the numbers once for a deal, and buyers can tell.

The gap is between a team that "takes them six weeks from the time there's an ask to where they can actually provide the data" and "somebody that can get it to them the next day because that's how they manage their company."

6 weeks isn't a data problem. It's a confession.

The buyer isn't marking down your reports. They're marking down your team. A team that makes calls on data everyone trusts reads as "this is lower risk" and a "more capable management team." If they plan to keep you after the deal, that difference shows up in the price.

Does this matter if a strategic buyer wants to acquire us?

Much less. A strategic buyer who wants your tech has a hole in their product. They don't care much about your sales numbers. They plan to fold your go-to-market team into theirs or cut it. Clean data matters most when the money is financial: PE, growth equity, or a Series C round.

Scott was blunt about the strategic case. They're "basically gonna either absorb or fire your whole go-to-market team."

The financial case is different. Once you have product market fit, "these financially oriented investors are going to want to understand the efficiency of your company." How well you grow is the thing they're paying for.

So if you might raise again, or sell to a PE firm, this is your problem. Most companies under $30M don't know which buyer they'll get. Plan for the one who checks.

What makes a revenue metric worth reading?

A metric needs 2 more things next to it: where you should be and where you were. Without a benchmark and a trend, a number can't tell you if things are good or bad. Most revenue dashboards show 1 column. A useful one shows 3, so a leader can see the problem and act on it.

Scott calls the usual dashboard "context-free data."

His example is annual lab work. Your lab report shows where you are, where you should be, and where you were last year. An A1C of 5 means nothing alone. It means a lot when you know 5 is pre-diabetic and it was lower 6 months ago.

Do the same with every number you show your board:

Where you are: win rate today.
Where you should be: the benchmark for a company like yours.
Where you were: the same number last year.

Add the benchmark and the trend, or stop calling it a KPI.

Where do we start if our data is bad today?

Start with the questions, not the dashboard. List the biggest choices your leaders have to make. Then ask what data answers each one, and what context makes that data worth trusting. Be honest that today's data is weak. Lean on your most experienced people for now while you build toward better data.

Scott's order:

"what are the most impactful business decisions or questions you need to be able to answer?"
What data answers those?
What context does that data need to be trusted?

For a company that already has product market fit, his top question is simple: "What is the least amount of money we can invest to reach these growth goals?" And then how to split that money across sales, marketing, and customer success.

He also keeps a sticker on his monitor: "don't manufacture precision if you don't have the data to support it."

If your data is a mess, say so out loud. Building it right takes time. Scott puts it at a 2, 3, or 4 year path. That's not failure. That's the honest timeline. As he says, "there's no point you know reaching for the stars when you've got garbage to start with."

Why don't our revenue leaders care about company value?

Because you don't pay them to. Most CROs earn most of their bonus on commission from new bookings. But company value comes from fast growth and efficient growth. Pay your sales, marketing, and CS leaders on the metrics that track value, and they stop working in silos and start working together.

Scott names 3 metrics that track value:

Year over year ARR growth rate.
LTV to CAC.
A rule of 40 type score.

Then he asks the obvious question. "Commission on new bookings is not. Why do we keep doing this?"

His fix: pay all 3 revenue leaders on those metrics. He's put this in place at a couple of his companies, and he says "it completely annihilates the siloed thinking." A sales leader starts to say things like: I'd give up 2 AE seats and put $300,000 into marketing for more top of funnel.

He also called out the 2 most common ways 1 + 1 = 0 on a revenue team:

"A lot of money spent by marketing generating leads that sales doesn't even touch."
"Salespeople going and booking deals with non-ICP customers" who then churn after CS works overtime to save them.

He'd bet 70 to 80% of companies see one or both of these on a regular basis.

How fast could we answer a buyer's questions today?

Test it this week. Pick the 5 numbers a diligence team would ask for and ask your team for them today. Time how long it takes. Next day means you run on data. Over a week means your board meetings run on opinions with numbers attached. That gap is the number a buyer sees.

Do this today (20 minutes):

Write down the 5 questions diligence would ask: growth rate, LTV to CAC, pipeline conversion, net revenue retention, and cost to acquire a customer.
Ask your team for those 5 numbers. Today. Don't explain why.
Note the hour you asked.
Write the number of days it took at the top of your next leadership meeting agenda.

And watch for the old excuse: do you want reps filling out the CRM, or selling? Scott calls it "this mythical paradox that you can't do both." Reps who log their deals give the CRO better data. Better data means better coaching. Better coaching means more sales.

More on this: 5 Metrics Leadership Expects From Salesforce, Stop your Salesforce forecast from lying to you every Monday, and "No freaking idea" is not a KPI

Bottom line

Winging it isn't the lack of data. It's the lack of a decision you made with it.

You don't need a better dashboard. You need 5 questions you can answer by Thursday.

Frequently asked questions

Does messy CRM data really lower what a company is worth?

It can, when the buyer is financial, like a PE firm or a Series C investor. Slow, messy numbers tell them the leaders don't run on data. That reads as risk, and risk comes out of the price. A strategic buyer who mostly wants your tech cares much less.

What numbers will investors ask for in diligence?

Start with 5: growth rate, LTV to CAC, pipeline conversion, net revenue retention, and cost to acquire a customer. If you can send all 5 the next day, you're in good shape. If it takes weeks, start there.

How long does it take to fix bad revenue data?

Plan on years, not weeks. Scott puts a real build at 2 to 4 years, and it never fully stops. Start with the questions your leaders need answered, then fix the data behind those first.

What is context-free data?

It's a number with nothing next to it. A win rate alone can't tell you if it's good or bad. Add where you should be (a benchmark) and where you were (last year), and now it can drive a decision.

How should we pay our CRO?

Tie a big part of their pay to metrics that track company value: ARR growth, LTV to CAC, or a rule of 40 type score. Do the same for your marketing and CS leaders, so all 3 pull in the same direction.

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