This week’s newsletter is based on a longer strategy session I ran with Steffen Hedebrandt (CMO @ Dreamdata) around LinkedIn Ads strategies for 2026.
If you are a B2B marketer who wants to get more customers in your pipeline next year, grab the full session here 👇
Hey friend,
We’re nearly at the end of Q4 and this week felt like a good time to talk about one of the most misunderstood parts of running a successful marketing machine.
Patience.
Marketing budgets operate on timelines that don’t naturally align with how most marketing campaigns actually work.
That’s why I hate it when the plug gets pulled on a campaign too early. Campaigns that look like failures at day 90 can easily become your highest-ROI campaign by day 270 if they are given the time to do their thing, especially on LinkedIn.
When Dreamdata analyzed 220k+ B2B customer journeys, they found the average time from first LinkedIn ad impression to revenue was 320 days… almost a full year!
With marketing budgets getting pulled and pressure to fill your pipeline, here’s how to communicate marketing’s goals to the rest of the company and build your case 👇
Why Good Marketing Campaigns Die Early
I've seen this movie play out the same way dozens of times:
A company launches a demand generation campaign. Spends $15K/month on LinkedIn thought leadership ads. After 3 months, leadership asks "where are the SQLs?" and then, the budget gets cut and the campaign thrown in the bin.
In my experience, campaigns get canned for three reasons:
Expectations. Most companies set marketing KPIs based on what CFOs need (quarterly revenue targets), not on how buyers actually buy. This creates a mismatch between campaign reality and executive expectations.
Metrics. When we only report vanity metrics early (clicks, impressions) and pipeline late (SQLs, revenue), we create a credibility gap. Leadership sees numbers that look meaningless until suddenly revenue appears. By then, they've already decided the campaign doesn't work and pulled budget.
Revenue attribution. Without proper attribution, leadership can't see the connection between high engagement in Q1 and closed/won deals in Q3. So when Q3 pipeline arrives, they attribute it to whatever happened recently, not the campaign that planted seeds 6 months ago.
This is something marketers desperately have to fix to defend their work and get budget for future campaigns.
How To Tell A Compelling Marketing Story In Your Org
This is how I've kept campaigns alive (and budgets growing) even when pipeline takes 6-9 months to show up. The concept is dead simple:
Leading indicators are early signals that predict future pipeline
Lagging indicators are the actual results your boss cares about
When leadership sees leading indicators trending up, they have signals that the campaign is working—even before pipeline arrives. This confidence keeps the budget alive.
It's so important that before you start your campaigns and marketing experiments to have that conversation. Yes, we all want more revenue or more pipeline, but that's going to take three, six, nine months.
You also need those very leading indicators to show that the ship that you have set out is sailing towards the right direction.
The same principle applies to leading indicators. They're the early pain signals that predict the pipeline outcomes your leadership cares about.
Here's how to implement this strategy 👇
Step 1: Map Your Customer Journey Timeline
Before launching any campaign, map the full buyer journey with actual time estimates for each stage.
Use your attribution platform or CRM data to analyze closed/won deals from the past 12 months.
Filter for deals that came through your target channel (e.g., LinkedIn ads)
Identify time from first touch to first engagement, first engagement to meeting booked, meeting booked to SQL, SQL to closed/won
Calculate the median time for each stage (not average as median removes outliers)
Add it all up to get a realistic campaign timeline
A real customer journey of ours inside Dreamdata
For most B2B companies running demand gen on LinkedIn, you'll land somewhere between 180-320 days from first impression to revenue. Higher ACV deals or products in a crowded category can add even more time.
Step 2: Identify Your Leading Indicators
Find the metrics that show up early and will correlate to customers down the line.
Marketers (and I’m guilty of this as well) throw way too many numbers and acronyms at executives that they don't really understand. This puts you in a tricky position where executives just want to see everything going up and to the right instead of what’s impacting the bottom line.
Keep it to metrics like pipeline, CAC, branded search, and ICP company traffic, as you can frame those is as indicators of future pipeline.
In-platform signals to track:
Audience penetration rate. What % of your target audience has seen an ad? You want to aim for 80%+. Check this in Campaign Manager.
Frequency. How many times has your average user seen an ad? Target 12+ impressions within 90 days. An impression doesn't mean they actually saw it though. You need multiple exposures for it to stick.
Engagement rate. Beyond CTR, track engagement metrics across carousel swipes, video views, dwell time.
Off-platform signals to track in your attribution platform:
Booked meeting velocity. Meetings per week trending upward.
Brand search volume. Branded search queries increasing. Pull this from Google Search Console or a tool like MyTelescope.
ICP company traffic growth. Filter website traffic by accounts matching your ICP. I recommend using Dreamdata for this.
Your signals might be slightly different to ours, but these are great early indicators of how likely campaigns are to translate into revenue.
It can be really helpful looking at the engagement rate of those accounts that have still not reached MQL or SQL.
That can be a great audience for your SDR team to go after that have a super high engagement rate, but you may not be speaking to anybody on those accounts.
They're clearly in market, but they're also clearly not talking to you.
Step 3: Track Your Lagging Indicators
These are the metrics leadership actually cares about—revenue, pipeline, close rates. It’s important to communicate to leadership before any campaign that these can show up weeks, months or even years later 👇
Track these in your attribution platform:
CAC to ACV ratio. Customer acquisition cost vs. average contract value and how healthy the ratio is.
Influenced pipeline by channel. How much pipeline has this channel touched? This shows the full contribution, not just last-touch.
Influenced revenue by channel. Same as above, but for closed/won. Track this even if your marketing KPI is pipeline as execs care about revenue.
A snapshot of our influenced revenue broken down by channel in Dreamdata
Track these in your CRM:
Overall pipeline lift. Is total pipeline growing since campaign launch?
Average deal value. Are deals getting larger?
Close rate trend. Is win rate improving? Good demand gen should improve close rate by bringing in warmer leads.
This tracking creates loop between sales conversations and marketing metrics to show both are working.
Step 4: Communicate Wins To Leadership With Simple Reporting
The final part of the recipe is to create a reporting framework that shows both leading and lagging indicators on a timeline.
This is a framework we use internally at KlientBoost called Goal Pacing. The reason I love this is it not only aligns sales and marketing under core goals, but it also gets senior leaders on board with marketing’s efforts.
An example of a Goal Pacing graph I use to tell marketing’s story to internal leadership
I track two graphs that show my marketing’s team’s main KPIs—SQL volume and ICP traffic:
We set a baseline based on historic performance, and then we try to beat ourselves vs the previous quarter
We'll add a stretch goal depending on the campaigns running (e.g. 20-25% lift)
That’s it. I present these graphs to communicate to leadership how marketing is performing against its goals.
If you are in the blue, execs are going to be happy.
🌶 Extra Spice: Use AI Signals To Bridge Leading + Lagging Indicators
Marketers have talked about intent signals for years, but most of the time the recommendations offered on platforms turn out to be generic garbage.
Dreamdata’s AI signals are different. They tell you what is true buying intent for your company and weight them to signal if someone is moving down your pipeline and may be ready to buy.
I use these signals to build activation audiences based on high-intent buying signals for retargeting. For example, we put companies tagged as engaged into a list and target them with incentivized conversation ads to get them on a call.
Our AI signals inside Dreamdata
This is a really simple way to get engaged audiences in front of your sales team.
We know everything about every journey and what looks unique for you when you win accounts. It's not just a G2 category visit, but perhaps it's somebody looking at your security documentation. The things that happens in your data warehouse is completely unique to you.
Our AI scans all ongoing journeys to see if some of these journeys are showing behavior of somebody who's uniquely positioned to buy your specific product. It's not all the broad advice about intent data. It's actually what's true intent for your company.
This is exactly why proper attribution matters—you need to see the complete journey, not just the last click.
How Will You Tell Your Marketing Story In 2026?
I sound like a broken record but if you read this newsletter regularly, you’ll know I preach that only 5% of your target market is in-market and ready to buy. 95% of your audience is just not ready, no matter how good your paid and organic campaigns are.
Next time you're about to launch a campaign with a 6-12 month sales cycle, map out your leading and lagging indicators first. Communicate when each will appear to keep the budget alive long enough for it to work.
"Q2" makes sense for a CFO spreadsheet, but for a lot of marketing campaigns, it's not enough time for results (that the people who approve or deny the budget) care about.
And you know what? Tough 🤷♀️
This is the world marketers are playing in, so we need to get better at communicating when campaigns will light up attribution dashboards in green.
Be patient. But more importantly, communicate when to expect results so your leadership can be patient too.
Hope you've found this useful and I'll catch ya in the next one!
🤘
Patrick
P.S. If you're spending more than $25K/month on demand generation and struggling to justify the budget despite strong engagement metrics, we should talk. We help marketing teams build attribution models that connect early signals to revenue outcomes so you can keep campaigns alive long enough to work… just hit me up for a chat!
Want to talk about how to get more customers with LinkedIn Ads in 2026?
See what we can do for you 👉
