How to segment and target B2B audiences using Appinio advanced filters

So you need to reach the right business decision-makers, not just anyone with a LinkedIn profile and a company email. Targeting B2B audiences is tricky—job titles are vague, industries overlap, and half your “CXOs” are just folks who checked a box. If you’re here, you probably want to use Appinio to actually talk to people who make real decisions at real companies, not waste your research budget on the wrong crowd.

This guide is for people who want to cut through the noise and use Appinio’s advanced filters to build B2B audiences that, you know, actually match their target market. I’ll walk you through what matters, what’s mostly hype, and how to avoid common screwups.

Step 1: Get Clear on Who You’re Actually Targeting

Before you even log into Appinio, get specific. “B2B decision-makers” is uselessly broad. Write a sentence or two about your ideal respondent:

  • What’s their job function? (e.g., IT manager, procurement lead)
  • What level of seniority? (manager, director, VP)
  • What size of company? (startup, mid-market, enterprise)
  • What industry or sector?
  • Where are they based?

You’ll use these criteria to set up your advanced filters. If you’re fuzzier than this, you’ll end up with a junk sample.

Pro tip: Don’t just copy what sales or marketing says. Double-check: are you after people who sign purchase orders, or just influence decisions? They’re not always the same.

Step 2: Map Your Criteria to Appinio’s Advanced Filters

Appinio gives you a bunch of demographic and firmographic filters. Some are useful, some are just window dressing.

Here’s what you get:

  • Job Title/Function: Usually a dropdown or search. Remember, job titles are a mess. “IT Manager” at a 10-person company is not “IT Manager” at a Fortune 500.
  • Seniority Level: Sometimes by title, sometimes by years of experience. Be careful; not everyone picks their title honestly.
  • Company Size: Filter by employee count or revenue. Go for employee count—it’s less fuzzy.
  • Industry: Standardized lists (SIC, NAICS, or custom). Some categories are too broad (e.g., “Technology” covers everything from SaaS to IT recycling).
  • Location: Country, region, sometimes city.

What works well:
- Company size and country filters are usually accurate.
- Job function is decent, but don’t get too granular. “Procurement” works; “Head of SaaS Vendor Management” won’t.

What’s shaky:
- Job titles, especially C-level, get abused. Lots of “CEOs” of tiny consultancies. - Industry can be vague; check what categories mean in Appinio’s dataset.

Step 3: Layer Your Filters—But Don’t Go Overboard

People think more filters = better targeting. In reality, too many filters and suddenly you’re looking for a unicorn, and your survey will never finish.

Here’s how to build a practical audience:

  1. Start wide, then narrow.
    Set your must-haves first: company size, country, basic job function.

  2. Add one or two “nice to have” filters.
    Maybe industry, or a seniority band.

  3. Check your estimated audience size.
    Appinio will show you how many people match. If it’s under 100, relax your criteria or you’ll be waiting forever (or paying through the nose).

Pro tip:
If your audience is too small, drop the least-important filter. You can always screen later in the survey.

Step 4: Use Screening Questions to Weed Out Fakes

Filters only get you so far. People can misclick or misrepresent themselves. The real trick is a good screener question at the start of your survey.

Examples:

  • “Which of the following best describes your role in purchasing software for your company?”

  • Answers: I make final decisions / I recommend / I have no role

  • “How many employees work at your company?”

  • Answers: 1-10, 11-50, etc. (Check against filter)

  • “Which best describes your industry?”

  • Use your own language, not Appinio’s.

Kick out anyone who doesn’t match your target. Yes, this means you’ll pay for some “screened-out” responses, but it’s worth it to avoid junk data.

What doesn’t work:
- Letting people self-select with “Are you a decision-maker?” Most will say yes, even if they’re not.

Step 5: Double-Check Your Audience Before Launching

Before you hit go, review your audience summary in Appinio:

  • Are you hitting the right mix of company sizes and industries?
  • Is there enough sample size to finish your survey in a reasonable time?
  • Did you accidentally exclude half your market by being too precise?

If you can, run a small pilot (say, 10-20 responses) and actually look at the data. Are these the people you want? If not, tweak the filters and try again.

Pro tip:
If you see lots of one-person “companies” or people with suspiciously vague job titles, tighten your company size filter or add a screener about their role.

Step 6: Use Custom Filters (if you have access)—But Be Realistic

Appinio sometimes lets you use custom filters: things like tech stack, annual budget, or even specific certifications.

Be realistic:

  • If your target is “IT Directors who use SAP and spend over $500k/year,” you might get a handful, but don’t expect hundreds. Niche = slow and expensive.
  • Always check with Appinio support about feasibility if you’re getting fancy.

What works:
- Custom filters for broad categories (e.g., “uses cloud software”) can work. - Super-niche combinations almost always disappoint.

Step 7: Ignore Vanity Filters and Hype

Some platforms love to advertise quirky filters—“Innovation Mindset,” “Digital Transformation Leader,” etc. These are marketing fluff. Stick to criteria you can actually check or screen for.

Don’t waste time on: - Personality filters - “Decision-making style” - Anything that sounds like it came from a slide deck

If it doesn’t map to a real-world attribute or you can’t verify it with a screener, skip it.

Step 8: Monitor and Adjust

After launch, keep an eye on your respondent pool. If you’re seeing odd patterns—like lots of low-quality responses or weird company distributions—pause and adjust your filters.

  • Ask Appinio support for help if something looks off.
  • It’s better to tweak early than to realize at the end your data’s junk.

A Few Final Tips

  • Be specific, not picky. You want the right people, but you also want enough of them to finish your research.
  • Screeners matter more than filters. Spend time on good screener questions; they’re your last line of defense.
  • Test before you scale. Always run a pilot batch and check the results.
  • Don’t believe the hype. If a filter sounds vague or too good to be true, it probably is.

Keep it simple: get clear on your audience, use the filters that matter, and don’t obsess over every fancy targeting option. The best B2B research comes from iterating, not from chasing perfect segmentation on the first try. Good luck—and don’t be afraid to adjust as you go.