If you’re tired of blasting the same marketing message to everyone and getting nowhere, you’re not alone. This guide is for marketers and teams who want to actually reach the right people, not just “check the box” on audience segmentation. We’ll walk through how to segment audiences in Pfl for hyper-targeted campaigns—without the hype or hand-waving.
You’ll get actionable steps, a few honest warnings, and the stuff you actually need to know to make audience segmentation work—whether you’re new to Pfl or just sick of mediocre results.
Why Audience Segmentation (Still) Matters
Let’s be blunt: most campaigns underperform because they’re too generic. “Personalization” is thrown around a lot, but just dropping a name in an email isn’t enough. Segmentation—actually dividing your audience based on real, useful differences—lets you target people who might care, with messages that might work.
Pfl gives you some decent tools for this, but it’s not magic. You still have to think hard about who your audience is and why they’d care. That said, if you set things up right in Pfl, you can avoid the “spray and pray” disaster that eats up budgets and attention spans.
Step 1: Get Your Data In Order (Don’t Skip This)
Before you even touch Pfl’s segmentation features, make sure your data isn’t a dumpster fire. If your lists are full of duplicates, missing info, or old contacts, you’re setting yourself up to fail—no tool can fix bad data.
What to check: - Are your contacts current? If you haven’t cleaned your list in a year, start there. - Do you have the fields you need? (Think: industry, job title, location, purchase history—not just email and name.) - Are the fields labeled consistently? “State” vs “state/province” will trip things up. - Is your data imported properly into Pfl? If you’re syncing from a CRM, watch for mismatches.
Pro tip: Spend an hour fixing your list now. It’ll save you weeks of headaches down the road.
Step 2: Choose Segmentation Criteria That Actually Matter
Just because you can filter by every field doesn’t mean you should. Focus on criteria that make a difference in your campaign’s message or offer. Otherwise, you’re just slicing and dicing for no reason.
Common segmentation options in Pfl:
- Demographics: Location, job title, company size, industry.
- Behavioral: Past campaign engagement, event attendance, website visits.
- Purchase history: Existing customers vs. prospects, product types bought, deal size.
- Custom fields: Anything else you track, like sales stage, product interest, renewal date.
What works: Start with 2–3 meaningful segments. For example: - “HR managers in healthcare who opened our last campaign.” - “Customers who bought in the last 3 months but haven’t responded to follow-ups.”
What doesn’t: Segmenting just because you can. “All contacts in California” might be too broad if you sell nationwide. Micro-segments with 5 people each? Usually not worth the effort.
Step 3: Build Segments in Pfl (Without Overcomplicating)
Pfl’s audience segmentation tools are straightforward if your data is clean. Here’s how to use them without getting lost in the weeds.
1. Navigate to the Audience or Contacts section
- This is where you’ll find filters and the ability to create new segments.
- The exact menu might vary depending on your Pfl plan or UI version, but look for “Contacts,” “Audiences,” or “Segments.”
2. Use Filters to Define Your Segment
- Click “Add Filter” and select the criteria you decided on earlier.
- Stack filters to create more specific groups (e.g., Industry = Healthcare AND Job Title contains ‘Manager’).
3. Save Your Segment
- Give it a clear, specific name. “2024 Healthcare HR Engaged” is better than “List 1.”
- Pfl will usually let you save dynamic segments (auto-updating as data changes) or static lists. Dynamic is almost always better—unless you’re prepping a one-off campaign.
4. Test Your Segment
- Spot-check the list. Do the contacts actually fit your criteria?
- If it looks off, double-check your filters and source data.
Pro tip: Don’t create segments for every hypothetical use case. Start with your top 2–3, run campaigns, and refine based on what actually moves the needle.
Step 4: Match Your Message to Each Segment
No point in segmenting if the message stays the same. Here’s where the “hyper-targeted” part comes in.
For each segment, ask: - What problem do they care about most? - What objections or questions will they have? - What’s the one action I want them to take?
Examples: - For “New leads in tech,” focus on education and awareness. - For “Existing customers up for renewal,” focus on value and retention.
Don’t overthink it. One clear message per segment beats a dozen half-baked variations.
Step 5: Set Up and Launch Your Campaigns in Pfl
Now you’re ready to actually build your campaigns.
- Create a new campaign. Choose your segment as the audience.
- Customize content. Use merge fields for basic personalization, but rely on your segment-specific messaging for real impact.
- Preview and test. Send a test to yourself or a colleague. Make sure the segment-specific content shows up as intended.
- Schedule or launch. Don’t wait for perfect. Launch, then watch the results.
What to ignore: Don’t get bogged down in every fancy feature or integration. Focus on getting the right message to the right people. The rest is window dressing.
Step 6: Review Results and Adjust (Seriously, Don’t Skip This)
The best segmentation in the world won’t help if you don’t check what actually happened.
- Look at performance by segment. Did one group open/click/buy more than others?
- Ruthlessly cut what doesn’t work. If a segment underperforms, try a different message or scrap it.
- Iterate. Segmentation is never “done.” Adjust your criteria and messaging as you learn.
Pro tip: Don’t segment for segmentation’s sake. If you’re not seeing a real difference, simplify.
Quick Hits: What Works, What Doesn’t
What works: - Clean data and clear, simple segment definitions. - Messages tailored to each segment’s real needs. - Testing and iterating with actual results.
What doesn’t: - Over-segmentation (tiny lists, endless filters). - Relying on “personalization” without substance. - Ignoring results and repeating what didn’t work.
Keep It Simple (and Don’t Wait for Perfect)
Audience segmentation in Pfl isn’t rocket science, but it does take some upfront thought and a willingness to scrap what doesn’t work. Start simple, use data that’s actually useful, and keep your eye on what your audience actually wants. Iterate as you go—don’t let analysis paralysis keep you from hitting send.
You’ll get better results, less wasted time, and maybe even enjoy marketing again.