The demand gen manager presented the plan with genuine excitement: "We're going to personalize everything."
She'd just come from a marketing conference where every session was about personalization. Dynamic content based on industry. Email sequences tailored to job title. Website experiences that change based on company size. AI-powered recommendations for every visitor.
The research backed it up. Seventy-two percent of consumers expect personalized experiences. Companies that excel at personalization generate 40% more revenue. Personalized emails improve click-through rates by 14% and conversions by 10%.
The plan was ambitious: segment our database into 47 different combinations of industry, company size, and job title. Build customized email nurture sequences for each segment. Create industry-specific landing pages. Implement dynamic website content that changes based on firmographic data.
Timeline: six months. Budget: $120K (mostly contractor costs for content creation). Expected outcome: 30-40% increase in pipeline from marketing campaigns.
I had concerns—this felt like a lot of complexity for marginal gains—but the data was compelling. We approved it.
Six months later, the results were in. And they were baffling.
The Numbers That Didn't Make Sense
The personalization project delivered exactly what it promised on engagement metrics:
Email Performance:
- Open rates: up 23% (from 22% to 27%)
- Click-through rates: up 18% (from 2.8% to 3.3%)
- Reply rates: up 31% (from 0.4% to 0.52%)
Landing Page Performance:
- Time on page: up 35%
- Scroll depth: up 28%
- Content downloads: up 19%
Every engagement metric improved. People were clearly responding to personalized content—they opened more emails, clicked more links, spent more time on pages.
But the metric that actually mattered—pipeline generation—went down.
Pipeline Metrics:
- Demo requests: down 12%
- Qualified opportunities: down 15%
- Closed/won deals: down 18%
We'd spent six months and $120K making our content more engaging and less effective.
The VP of Sales summarized it perfectly in the pipeline review: "I don't care if people are reading your emails. Are they buying our product? Because the answer appears to be no."
The Conference Call That Changed Everything
Desperate to understand what went wrong, I called a former colleague who'd built demand gen at a unicorn SaaS company. I explained the whole situation—the personalization project, the improved engagement, the declining pipeline.
She laughed. Not unkindly, but like she'd seen this movie before.
"You personalized the wrong things," she said.
"What do you mean? We personalized based on industry, company size, job title—all the standard segmentation dimensions."
"Exactly. Standard segmentation dimensions. Those aren't what B2B buyers care about."
She walked me through her framework:
What most B2B marketers personalize (but shouldn't):
- Industry-specific examples ("for healthcare companies" vs. "for financial services")
- Job-title-specific messaging ("for Directors of Marketing" vs. "for VPs of Marketing")
- Company-size-specific positioning ("for mid-market" vs. "for enterprise")
What B2B buyers actually care about (and should be personalized):
- Problem urgency (are they actively in pain or just casually researching?)
- Current state (what are they using today and why isn't it working?)
- Buying stage (awareness vs. evaluation vs. decision)
"You built 47 variations of content that all said basically the same thing with different industry examples," she said. "But you didn't change what actually matters—whether the content serves someone who's actively trying to buy versus someone who's just learning."
That's when I realized: we'd built demographic personalization when we needed behavioral personalization.
The Research Nobody Reads Carefully
After that call, I went back to the personalization research everyone cites. Turns out, the data says something different than how it's usually interpreted.
The Stat Everyone Quotes: "72% of consumers expect businesses to personalize experiences." (McKinsey)
What The Research Actually Shows: When you dig into what "personalization" means to consumers, it's not demographic customization. It's relevant content at the right time based on their actual behavior and needs.
The examples that drive the 40% revenue increase aren't "Dear Sarah" vs. "Dear Customer" or "For SaaS Companies" vs. "For FinTech Companies."
They're:
- Amazon showing products related to what you just viewed
- Netflix recommending shows based on what you actually watched
- Spotify creating playlists based on your listening behavior
All behavioral. None demographic.
The Stat Everyone Misses: "Seventy-seven percent of consumers have chosen, recommended, or paid more for a brand that provides a personalized service or experience." (Forrester)
But when you read the details, "personalized service" means:
- Remembering what I bought last time and making re-ordering easy
- Recognizing I'm a repeat customer and treating me accordingly
- Solving my specific problem instead of giving me generic advice
Again, behavioral. Not demographic.
The B2B marketing industry took research about behavioral personalization and implemented demographic personalization because it's easier to execute.
The 47 Segments That All Said the Same Thing
I did an audit of our 47 personalized email sequences. Here's what the first email looked like for three different segments:
Segment 1: Healthcare, Director of Marketing, 100-500 employees
Subject: How Healthcare Marketers Are Improving Win Rates
Hi ,
Healthcare companies like face unique challenges in competitive positioning. With complex regulatory requirements and multiple stakeholders, traditional battle cards often fall short.
[Rest of email about our competitive intelligence platform]
Segment 2: FinTech, VP of Product Marketing, 500-1000 employees
Subject: How FinTech PMMs Are Improving Win Rates
Hi ,
FinTech companies like face unique challenges in competitive positioning. With rapidly evolving features and aggressive competitors, traditional battle cards often fall short.
[Rest of email about our competitive intelligence platform]
Segment 3: SaaS, Director of Marketing, 100-500 employees
Subject: How SaaS Marketers Are Improving Win Rates
Hi ,
SaaS companies like face unique challenges in competitive positioning. With constant product updates and differentiation pressure, traditional battle cards often fall short.
[Rest of email about our competitive intelligence platform]
Do you see what happened? We changed the industry name and the "unique challenge" description. Everything else was identical.
Someone in healthcare doesn't care that we mentioned healthcare. They care whether we understand their actual problem.
Someone actively evaluating competitive intelligence platforms wants different content than someone who just learned that competitive intelligence platforms exist.
But all 47 segments got the same funnel, same message progression, same call-to-action timing—just with different industry Mad Libs.
What Actually Works: The Three-Tier Personalization Model
After the failed personalization project, we scrapped the 47 segments and rebuilt around three behavioral segments instead:
Tier 1: Problem Aware (not solution aware)
- Behavior: Reading educational content about competitive strategy, win/loss analysis
- Indication: They have the problem but don't know our category exists
- Content needed: Educational content about the category, why this problem requires a dedicated solution
- Example email: "Why spreadsheets fail at competitive intelligence (and what to use instead)"
Tier 2: Solution Aware (actively evaluating)
- Behavior: Downloaded comparison guides, visited pricing page, requested demo, asked specific product questions
- Indication: They're actively looking for a solution and evaluating options
- Content needed: Differentiation content, customer proof points, ROI justification
- Example email: "How [Similar Company] chose a competitive intelligence platform: 7 evaluation criteria that mattered"
Tier 3: Decision Stage (choosing between vendors)
- Behavior: Attended demo, trial user, comparing pricing, asked about implementation timelines
- Indication: They're making a final decision between 2-3 vendors
- Content needed: Decision support, risk mitigation, customer success stories, implementation plans
- Example email: "What to expect in your first 30 days: Implementation timeline and early wins"
Three segments instead of 47. But these segments actually represented different needs, not just different demographics.
The Results That Made the VP of Sales Happy
We rebuilt our email nurture program around the three-tier behavioral model. Same total content volume as before (we repurposed a lot of the industry-specific content we'd already created). But sequenced based on buying stage instead of demographics.
Three months later:
Email Performance:
- Open rates: 24% (down from 27% in the demographic personalization model, but still above baseline)
- Click-through rates: 3.1% (down slightly from 3.3%, but still strong)
- Reply rates: 0.48% (down slightly from 0.52%)
Engagement metrics were slightly lower than the demographic approach. People were marginally less excited to see their industry mentioned.
But pipeline metrics told a different story:
Pipeline Performance:
- Demo requests: up 34% from baseline (vs. down 12% in demographic model)
- Qualified opportunities: up 28% from baseline (vs. down 15% in demographic model)
- Closed/won deals: up 22% from baseline (vs. down 18% in demographic model)
Lower engagement, higher conversions.
Because we were sending the right content to people based on where they were in their buying journey, not based on what industry they worked in.
The Two Types of Personalization (and Why Everyone Builds the Wrong One)
Turns out there are two completely different approaches to personalization:
Demographic Personalization:
- Based on who someone is (industry, job title, company size)
- Easy to implement (append data from Clearbit, segment in marketing automation, swap out variables)
- Feels personalized to marketers (we worked hard on those 47 segments!)
- Doesn't actually change the content's relevance to the reader's current needs
Behavioral Personalization:
- Based on what someone has done (pages visited, content downloaded, features used, questions asked)
- Harder to implement (requires tracking behavior, interpreting intent, dynamically adjusting content journey)
- Feels less personalized to marketers (we're only using three segments!)
- Dramatically improves relevance because it serves content matched to the reader's actual needs right now
B2B marketing has optimized for demographic personalization because it's easier to execute and easier to report on ("we personalized for 47 segments!").
But B2B buyers care about behavioral personalization because it actually helps them solve their problem.
The gap between what marketers build and what buyers want—that's the personalization gap.
Why 72% of PMMs Get This Wrong
The statistic in the title comes from a 2024 study of product marketing teams at B2B companies: 72% of PMMs reported implementing personalization programs in the last two years.
When researchers dug into what "personalization" meant:
- 68% meant industry-specific messaging
- 52% meant job-title segmentation
- 41% meant company-size customization
- 19% meant behavioral segmentation based on buying stage
Almost three-quarters were personalizing based on demographics. Less than one-fifth were personalizing based on behavior.
The reason is simple: demographic personalization is easier.
You can append firmographic data from third-party providers. You can segment your database by these fields in minutes. You can create templates with merge tags and dynamic content blocks. You can report "we have 47 personalized segments" and it sounds impressive.
Behavioral personalization is harder.
You need to track what people actually do. You need to interpret that behavior to understand intent. You need to build content journeys that adapt based on signals. You need to report "we have three behavioral segments" and explain why that's better than 47 demographic segments.
Demographic personalization is a feature you can implement. Behavioral personalization is a strategy you have to commit to.
Most PMMs choose the feature.
What To Do Instead
If you're building or rebuilding your personalization strategy, start with behavior, not demographics:
Step 1: Map the buyer journey by stage, not by segment
Don't start with "we serve healthcare, fintech, and SaaS." Start with "buyers move through problem awareness → solution awareness → vendor evaluation → decision."
Step 2: Identify the behaviors that signal each stage
What does someone do when they're problem aware but not solution aware? (Reading educational content, searching for best practices, asking broad questions)
What does someone do when they're evaluating solutions? (Comparing features, attending demos, visiting pricing pages, downloading buyer guides)
Step 3: Build content for stages, not demographics
Instead of 47 industry-specific email sequences, build 3-4 stage-specific sequences.
For problem-aware prospects: educational content that introduces your category For solution-aware prospects: differentiation content that explains why you're better For decision-stage prospects: risk mitigation content that makes choosing you easier
Step 4: Use demographics as flavoring, not as foundation
Once you have stage-based content, you can add industry-specific examples or job-title-specific framing as variables. But the core content should serve the buying stage.
The difference: "Here's how to evaluate competitive intelligence platforms" with a healthcare example swapped in vs. "Here's competitive intelligence for healthcare companies" with generic evaluation criteria.
Same industry mention, completely different value proposition.
For PMM teams trying to track behavioral signals across web, product, and sales touchpoints to implement true behavioral personalization, platforms like Segment8 help connect buying stage indicators across systems—the foundation of personalization that actually converts.
The Uncomfortable Truth About Personalization
The B2B personalization trend is driven by vendors selling personalization technology, not by data showing that demographic personalization improves B2B buying outcomes.
The research about personalization improving revenue is real. But it's based on behavioral personalization (Amazon, Netflix, Spotify), not demographic personalization (industry-specific email templates).
B2B marketing took the wrong lesson from consumer personalization success and implemented the wrong type of personalization.
And 72% of PMMs are now running personalization programs that make their metrics look better and their pipeline worse.
The solution isn't to stop personalizing. It's to personalize for behavior instead of demographics.
Which requires admitting that "47 segments" sounds more impressive than "3 behavioral stages" but delivers worse results.
And that the personalization gap isn't about technology or data availability.
It's about whether you're personalizing for yourself (demographic personalization makes marketers feel productive) or for your buyers (behavioral personalization actually helps them buy).
Most of us are still choosing wrong.