Your tracker says most of the market knows your brand, yet sales are flat, and awareness alone cannot tell you why. The purchase funnel splits the path from first hearing of a brand to buying it again into stages, so you can see where people drop away. It is also the frame behind concept testing, since a new product idea or message usually exists to fix one weak stage. This guide covers the survey question for each stage, conversion between stages and a two-brand comparison.
Key takeaways
- The purchase funnel runs from awareness through familiarity, consideration, preference and purchase to loyalty.
- In brand tracking, each stage is a survey question, reported as a percentage of everyone in the target market.
- Conversion between stages diagnoses better than levels: 80% aware and 40% considering is a 50% conversion.
- Read conversion by wave and by segment, and check base sizes, because later stages rest on fewer respondents.
- A survey funnel covers the whole market, competitors included. Digital marketing funnel metrics see only your own traffic.
What are the stages of the purchase funnel?
Most versions of the purchase funnel use five or six stages. Each stage is a subset of the one before it, since you cannot consider a brand you have never heard of.
- Awareness. The person recognizes the brand name.
- Familiarity. They know something about what the brand offers.
- Consideration. They would seriously think about it for their next purchase.
- Preference. It is their first choice.
- Purchase. They have bought it within a set period.
- Loyalty or advocacy. They intend to buy it again, or would recommend it.
The classic AIDA model (attention, interest, desire, action) describes the same idea from the advertiser’s side. A brand funnel turns the purchase funnel into questions you can ask a sample every wave.
How does a brand funnel measure each stage?
Each stage gets one question, asked about every brand on the list. Here is a typical running-shoe set.
| Stage | Example question | Who counts |
|---|---|---|
| Awareness | ”Which of these brands have you heard of?” | Selected the brand |
| Familiarity | ”How well do you know each brand?” (well / a little / name only) | Well or a little |
| Consideration | ”Which would you seriously consider next time you buy running shoes?” | Selected the brand |
| Preference | ”Which one brand would you most like to buy next?” | Chose the brand |
| Purchase | ”Which have you bought in the past 12 months?” | Selected the brand |
| Loyalty | ”How likely are you to buy this brand again?” (5-point scale) | Top two boxes, purchasers only |
Ask each question only of people who passed the previous stage, or apply that filter when you code the data. Report every level as a share of all respondents, so every brand shares the same denominator.
Our guide to brand awareness tracking covers the awareness questions in detail. For purchase intent wording in a new-product test, see concept testing questions.
Why do conversion rates diagnose better than raw levels?
A level tells you how many people reached a stage. A conversion rate tells you how well the brand moves people to the next one:
Conversion = share at this stage ÷ share at the previous stage × 100
Levels mostly reflect size and history, so a large, established brand leads every stage. Conversion removes that head start and shows which step is the weak link for each brand. In multi-brand trackers, we often see teams chase awareness when the real leak in the purchase funnel sits two stages further down.
How do you compare two brands’ purchase funnels?
Here is an illustrative wave of 1,000 running-shoe buyers, with invented numbers. Brand A leads the category and Brand B is a challenger.
| Stage | Brand A | Brand B |
|---|---|---|
| Aware | 80% (800) | 45% (450) |
| Familiar | 60% (600) | 30% (300) |
| Consider | 40% (400) | 24% (240) |
| Prefer | 20% (200) | 15% (150) |
| Purchased (past 12 months) | 12% (120) | 9% (90) |
| Loyal | 8.4% (84) | 7.2% (72) |
On levels alone, Brand A wins every row. Now divide each stage by the one before.
| Step | Brand A | Brand B |
|---|---|---|
| Aware to familiar | 60 ÷ 80 = 75.0% | 30 ÷ 45 = 66.7% |
| Familiar to consider | 40 ÷ 60 = 66.7% | 24 ÷ 30 = 80.0% |
| Consider to prefer | 20 ÷ 40 = 50.0% | 15 ÷ 24 = 62.5% |
| Prefer to purchase | 12 ÷ 20 = 60.0% | 9 ÷ 15 = 60.0% |
| Purchase to loyal | 8.4 ÷ 12 = 70.0% | 7.2 ÷ 9 = 80.0% |
You can also skip a stage. Brand A’s awareness-to-consideration conversion is 40 ÷ 80 = 50.0%, while Brand B’s is 24 ÷ 45 = 53.3%, despite far lower awareness.
What does Brand A’s funnel suggest?
People know Brand A and what it offers, with 75% of the aware becoming familiar. The leak is consideration to preference: only half of those who would consider A make it their first choice, against 62.5% for B. That points to weak differentiation or a price that does not feel worth it, so the next step is to test reasons to choose A through message testing, not more reach.
What does Brand B’s funnel suggest?
Brand B’s problem is at the top: only 45% are aware, and two-thirds of those feel they know it. Once people are familiar, 80% would consider it and 80% of buyers intend to buy again, the best rates in the table. B’s growth lever is reach, and creative testing helps pick the ads most likely to build awareness among the right buyers.
Where are the two brands even?
Preference to purchase is 60% for both, so availability and shelf price do not separate them. If one rate fell here later, check distribution, stock or price first.
How do you track the purchase funnel by wave and segment?
The funnel is one block in a wider brand tracking program. Keep the questions, their order, the brand list and the sample definition identical every wave, and report conversions next to levels. If awareness rises but awareness-to-consideration falls, the campaign may be reaching less interested people.
Segments, such as heavy versus light buyers, show where a leak is concentrated. Watch the bases. Brand B’s prefer-to-purchase rate rests on 150 respondents, so its 95% margin of error is 1.96 × √(0.6 × 0.4 ÷ 150) = about 7.8 points. In a segment of 30 people, it grows to about 17.5 points.
Crosstabs with weighting and significance testing show which segment gaps are real. Between readouts, market and brand intelligence tracks consideration and competitors continuously, with what changed and why.
How is a consideration funnel different from marketing funnel metrics?
| Consideration funnel (survey) | Marketing funnel metrics (digital analytics) | |
|---|---|---|
| Source | Survey of the target market | Ad, web and ecommerce analytics |
| Who is counted | Everyone in the market | People who reached your ads or site |
| Competitors | Measured the same way | Not visible |
| Typical measures | Awareness, consideration, preference | Impressions, click-through, visits, conversion rate |
| Best for | Brand health and share of mind | Campaign and site optimization |
Use both. Digital metrics show how well you convert people who already found you. The survey-based purchase funnel shows how many never got that far, and which brands they chose instead.
What are the common mistakes with a brand funnel?
- Unfiltered stages. If consideration is asked of everyone, a brand can show more considerers than familiar people, and conversion tops 100%.
- Mixed bases. Reporting consideration among the aware for one brand and among all respondents for another makes the comparison meaningless.
- Over-reading small bases. Late stages and segments shrink fast. Test a gap before you act on it.
- Changing the questionnaire between waves. A new brand list, scale or question order creates movement that is not real.
Pull your last two waves, calculate each step’s conversion for your brand and two nearest competitors, and mark where you trail by the widest margin. That step decides what to test next: reach if the gap is at the top, a concept or message if it sits in consideration or preference. Marketing teams can keep brand health and campaign impact in one continuous read across trackers and market sources.