Navigator
Startup
Automation

Leading vs. Lagging Indicators: Predicting Next Month's Revenue Today

Why last month's revenue doesn't matter, and which metrics actually predict your future.

• Navigator Team
leading indicators lagging indicators forecasting predictive analytics metrics

Your board meeting is next Tuesday.

Your CFO asks: “What do you project revenue will be next month?”

You look at last month’s revenue: $500k.

You assume this month will be similar, so you say: “Probably $500k.”

Your board member asks: “But what are the early signals? Are things accelerating or decelerating?”

You freeze. You don’t actually know. You’re just extrapolating the past.

This is the difference between Lagging Indicators (what happened) and Leading Indicators (what will happen).

Lagging vs. Leading: A Simple Definition

Lagging Indicators are metrics that tell you what already happened.

  • Revenue (last month is done; you can’t change it)
  • Customer churn (customer already left; the damage is done)
  • Average order value (historical; past orders)

Lagging indicators are backward-looking. They’re accurate (because they’re measuring completed actions), but they’re too late to act on.

Leading Indicators are metrics that predict what will happen.

  • Pipeline value (sales conversations happening now)
  • Email open rates (engagement happening now)
  • Website traffic (interest happening now)
  • Demo bookings (interest converting to intent)

Leading indicators are forward-looking. They’re less precise than lagging indicators (because the future is uncertain), but they give you time to act.

The Problem With Only Looking Backward

Most businesses run on lagging indicators. Here’s what that looks like:

Month 1 (January): You look at December revenue: $500k. Great month.

Month 2 (February): You look at January revenue: $600k. Growth! You’re excited.

Month 3 (March): You look at February revenue: $300k. Catastrophic. What happened?

You scramble. You analyze March. You realize that:

  • In March, your ad spend dropped because your team was busy with a product launch (in January)
  • Sales conversions slowed because your sales team was onboarding new reps (in February)
  • Customer churn accelerated because you were understaffed (throughout January and February)

By the time you see the revenue drop in March, all the bad decisions were made weeks ago. You can’t undo them.

This is reactive management. You’re constantly catching up to disaster.

Building a Leading Indicator Dashboard

A leading indicator dashboard tells you today what next month will look like.

Here’s what we track:

For SaaS (Subscription Business):

  • Monthly Recurring Revenue (MRR) Trending

  • Are your active subscriptions growing or shrinking?

  • Track: New subscriptions this week, cancellations this week

  • Example: If you signed 20 new customers this week and canceled 5, and this pace continues for a month, you’ll add 60 net new customers. That’s your leading indicator.

  • Sales Pipeline Value

  • How many deals are in your pipeline, and what stage are they in?

  • A deal in “proposal” stage is much more likely to close than a deal in “discovery” stage.

  • Example: You have $500k in proposals (high likelihood to close) and $2M in discovery (low likelihood). Your leading indicator says next month will be $300-400k in new revenue, not $2M.

  • Customer Health Scores

  • Are your existing customers at risk of churning?

  • Track: Support tickets (more tickets = higher risk), feature usage (low usage = higher risk), engagement (no logins = higher risk)

  • Example: Your health score shows 15% of customers are “at-risk.” Historically, 30% of at-risk customers churn. So, you predict losing 4-5 customers next month before it happens.

  • Website Traffic to Demo Request Conversion

  • How many people are visiting your site, and what percentage are requesting demos?

  • This is a leading indicator of sales pipeline growth.

  • Example: Traffic is up 30% week-over-week, and demo requests are up 40%. Your sales team will be busier next month, which means more closed deals in 2-3 months.

For E-commerce:

  • Cart Abandonment Rate

  • Customers add items to cart but don’t buy. This is a leading indicator of buyer intent.

  • High abandonment rate = customers are interested but something’s stopping them (shipping cost, trust issues, price)

  • Example: Your abandonment rate jumped from 60% to 80%. This predicts lower checkout conversions next week.

  • Email List Growth & Engagement

  • New subscribers = future customers

  • Email open rates = engagement/interest

  • Example: You grew your list by 5,000 new subscribers this month and they have a 35% open rate on welcome emails. That’s future revenue walking in the door.

  • Return Customer Rate

  • Are customers buying again?

  • This predicts future revenue and LTV (Lifetime Value).

  • Example: 25% of customers make a second purchase within 30 days. If you had 1,000 first-time customers last month, expect 250 repeat purchases this month.

  • Traffic by Source Quality

  • Not all traffic is created equal. Organic search traffic converts better than paid social traffic.

  • If your high-converting traffic sources are down, revenue will follow.

  • Example: Organic search traffic dropped 15%. Paid social traffic is up 50%. Your overall conversion rate will drop because you’re getting lower-quality traffic.

The Math: Turning Leading Indicators Into Forecasts

Here’s how we actually predict next month’s revenue.

Step 1: Identify Your Conversion Funnel

For a SaaS product:

  • Website visitors → Demo requests (conversion rate: 5%)
  • Demo requests → Sales calls (conversion rate: 60%)
  • Sales calls → Proposals sent (conversion rate: 50%)
  • Proposals sent → Deals closed (conversion rate: 40%, 30-day sales cycle)

Step 2: Track Each Stage This Week

  • Website visitors (this week): 2,000
  • Demo requests (this week): 100
  • Sales calls (this week): 60
  • Proposals sent (this week): 30
  • Deals closed (this week): 12

Step 3: Project Forward

  • If this pace continues for a month: 12 deals/week × 4 weeks = 48 deals
  • Average deal size: $10,000 MRR
  • Projected monthly revenue: 48 × $10,000 = $480k

So, today (based on this week’s data), we predict next month will be $480k. Not $500k (last month’s actual). Not a guess. A forecast based on real leading indicators happening now.

Step 4: Update Weekly

If next week the pipeline fills up more, we revise upward. If deal conversions slow, we revise downward.

By the time the month ends, your forecast is usually within 10% of actual revenue.

Dealing With the Lag

Not all leading indicators have the same lead time.

Some are instant:

  • Website traffic (tells you today what interest levels are)
  • Demo bookings (tells you within days what your sales team will be working on)

Some have a 2-3 week lag:

  • Sales pipeline (takes 2-3 weeks for a proposal to turn into a closed deal)
  • Product health scores (takes time for churn to materialize)

We account for this in our forecasting model. We don’t assume that 100% of proposals will close next month; we account for the typical 30-day sales cycle.

Red Flags In Leading Indicators

Here’s what we watch for:

1. Pipeline Filling Slower Than Historical Average If you normally get 50 demo requests per week and suddenly it’s 30, your revenue in 4-6 weeks will be lower.

2. Proposal-to-Close Rate Declining If you normally close 40% of proposals and it drops to 20%, something’s wrong. Your product offering changed? Your sales team lost a star performer? Deal quality declined?

3. Customer Health Scores Deteriorating If support tickets are tripling and product usage is dropping, churn is coming. You have 2-3 weeks to fix it before the cancellations hit.

4. Traffic Quality Shifting If your paid acquisition channels are suddenly generating lower-quality leads (visitors who don’t convert), your funnel will break. You’ll see it in CAC next month.

The Forecast That Feeds Into Planning

Once we have a revenue forecast, it becomes the foundation for everything else:

  • Hiring: If we forecast $400k next month, you can’t hire a $15k/month salary person today.
  • Product investments: You know what runway you have.
  • Marketing spend: You adjust budget based on the expected return.

Instead of reacting to last month’s results, you’re planning based on next month’s forecast.

The Takeaway

Stop asking, “How did we do last month?” Start asking, “What will we do next month?”

Leading indicators are the difference between a business that plans and a business that reacts.

We automate this forecasting so you don’t have to manually collect data from ten different sources. Every Friday, you get an updated forecast. You know where you’re headed before you get there.

That’s the power of prediction.