What your sales team's forecast would look like with clean data behind it

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Good Morning {{first_name}}!

It’s Tuesday - and if you missed last week’s update, you may be wondering where this issue was yesterday and why you are getting an email on a Tuesday. Last week, I shared a few newsletter changes. Moving forward, we’re consolidating the three issues into one.

Because the two go hand in hand, right?

So, without further ado, it’s Tuesday - and that means it’s time for your Growth Loop addition - an issue where we dig into whatever people are talking about this week from a marketing lens and see how it affects your CRM. ✨

This week, the biggest story online was how new benchmarks are changing how companies are addressing forecasting - or the lack thereof. The median B2B forecast accuracy is at 70%-79%, where close to 47% of deals miss their forecast by more than half. To add to this mix, contact data decays at 2.1% per month, so the deals, the contacts and the forecasts are constantly affected.

In fact, it’s only 7% of B2B sales organizations that hit 90% or higher on their forecast accuracy, according to ORM's forecasting guide. But we’ve all heard the joke about sales blaming marketing, marketing blaming sales, and no one trusts the reporting.

Ready to investigate? Let’s dive in.

Forecasting is nothing new. But with the rising costs of paid acquisition, and retention slipping due to AI advancements, forecasting becomes a desired feature. And in some companies - a must.

While we’d all like to point to sales, I believe that forecasting is a joint goal between sales and marketing. Marketing is responsible for generating and enriching contacts, ensuring that sales teams are working with quality leads. Without those, sales will struggle to forecast anything. Of course, sales should be great at adding information to ensure forecasting numbers are as accurate as possible.

ORM's guide reveals that 67% of organizations believe that less than half of their CRM data is accurate. That means most models are training on unreliable data, and adding AI will just complicate the matter.

Your company should focus on accurate CRM data, because the pipeline stages and forecasting affect everything downstream, including segmentation, list hygiene, lifecycle stages and automation practices.

This one may hurt a bit if you work on a team responsible for keeping records up to date. The core issue of improper forecasting has to do with incomplete data.

Landbase's research found the average B2B forecast misses by 25% and all the way up to 40%. And this result can solely be tied back to CRM records. In fact, deals that are manually kept up-to-date by reps and those that have rep confidence as a measurement are constantly the weakest ones.

Promises are made, and the board keeps questioning what is happening. And if marketing needs to stand a chance, the pressure is on sales to add the proper information so the confidence score are reliable.

There is one field in your HubSpot account that can help you out. The “Deal Stage Probability” field is currently sitting at a 100% fill-in rate because HubSpot fills it in based on the stages. In addition, the “Forecast Probability” field is not 100% filled in and requires a human interaction to be useful. The same is true for the “Manual Forecast Category” field.

Interestingly, “Last Activity Date” sits at 100% fill rate, which sounds like a healthy metric, but you need to put that in context with what is happening. For example, if someone logs a task, an email, or an internal note, it will mark it as “last activity.”

In other words, the auto-fills can show you that something is happening - when nothing that influences forecasting is happening. That’s where the 2.1% contact decay rate comes in.

Here are some ideas to battle this:

💗 Why Your Sales Forecast Is Wrong (And How to Fix It With Better Data) — Landbase's research ties the average 25 to 40% B2B forecast miss directly to incomplete CRM records rather than the forecasting model, and proposes weighting forecasts by data completeness rather than deal stage alone.

🧡 AI Sales Forecasting Accuracy: 2026 Benchmark Guide — Tomba's benchmark shows mature AI-assisted teams land inside a 5 to 10% error band while spreadsheet-driven teams sit at 20 percent or more, and flags missing contacts, duplicate accounts, and pipeline untouched for 30-plus days as the real accuracy killers, not the algorithm.

💛 Sales Forecasting: Complete Guide to Methods, Models, and Best Practices — Citing Validity's 2025 research, this guide notes 67% of organizations say less than half their CRM data is accurate, and that only 7% of companies hit 90%-plus forecast accuracy per Gartner.

💚 Sales Forecast Accuracy: B2B SaaS Benchmarks & Fix Plan — This breakdown sets elite quarterly variance at plus or minus 5 to 10% versus plus or minus 15 to 25% for most teams, and cites Gartner research showing fewer than half of sales leaders have high confidence in their own forecast numbers.

💙 Hybrid AI Sales Forecasts: 96% Accuracy Hits B2B In 2026 — Even as 81 to 89% of B2B sales orgs adopt AI forecasting tools per a Deloitte Digital report, teams still running static, poorly maintained CRMs are missing quota by 18 to 27%, which reinforces that the tool was never the bottleneck.

Give a Skydive agent an ongoing responsibility and they’ll handle it on schedule, every time.

Have them prep your morning report, research new leads, monitor customer feedback, or keep projects moving overnight. You wake up, the work is already done.

Make your first agent

If you’ve glanced through this newsletter and last week’s issue, you should hopefully now realize that the structure of the newsletter is changing. And I think that’s a good thing. Over the past couple of weeks, I’ve had clients and prospects of 44fjord ask me about the connections between sales and marketing. And you know what? They need to be more integrated than ever before. So, why not lead the charge with The Lifecycle Brief?

Also, 44fjord will be at UNBOUND in a few weeks in Boston. I’m looking to add to the team, so if you have experience working in Marketing Hub Pro/Enterprise and Sales Hub Pro/Enterprise, then I want to meet you! Reply to this email and let’s set up a coffee chat!

Regardless of how often you use HubSpot, your forecasting data will always be off if the data within your records is not maintained. In addition, there must be a feedback loop between marketing and sales. Forecasting often starts with “the model is wrong” when it should really start with data accuracy.

And the cost of not fixing this issue? Well, your team will be focusing on forecasts that are built on stale contact and deal data. And who wants that?