Customer Awareness Stages

The level decides what an ad must do first.

Five awareness stages, from least to most aware

Take a brand selling knee sleeves. An unaware runner has never linked their knee pain to anything fixable. A problem-aware runner feels the pain and assumes it is permanent. A solution-aware runner knows sleeves and braces exist but has not chosen. A product-aware runner knows the brand and doubts it fits. A most-aware runner wants one and needs a reason to buy today.

Read the stage from what a person asks or does, not from who they are. Sort each comment, message or review by the second column, then run the test in the last.

Treat each reading as a hypothesis for the test to check.

Reviews come from buyers, so they hold almost nothing about what a stranger knew before seeing your ad. In one count of 20 reviews for a single brand, ten were about orders, delivery, subscriptions or service, 6 about the product, 3 about price and 1 about the company's direction. A review counted as about the product only if its main complaint or praise was the product itself. None of the excerpts described what the reviewer knew before buying. The excerpts were truncated and it is one brand, so this shows a direction, not a rate.

Collect from where cold audiences speak, which means comments on ads shown to people who do not know you, plus forum questions and search phrases.

Awareness stages get confused with the marketing funnel, with cold traffic and with market sophistication.

• Funnel. A funnel moves people through steps. Stages describe where an audience stands today, and a buyer can skip stages, for example by arriving on a friend's recommendation already product aware.
• Cold traffic. Cold means a person has not dealt with your brand. It says nothing about whether they know the category.
• Market sophistication. Schwartz's companion idea in the same book is how many similar claims the market has already heard. Awareness is about the buyer; sophistication is about the market.

Code your last 100 signals by stage, then test the stage with the most signals that has no ad written for it. If two tie, take the colder one, because a mismatched message costs most where people know least. This is a recommended method, not a published standard.

1. Gather 100 recent comments, messages, reviews and forum questions, each with the ad it came from. One hundred is a working minimum.
2. Code each with the table and drop any you cannot place. Have a second person code 30 of them. If they disagree on more than 10, merge the two neighboring stages they confuse.
3. Count signals per stage and list the stages with a live ad written for them.
4. Brief one ad from the table's test, using an ad creative brief template, and run it against your best current ad (the control) at equal budget with everything else held the same.
5. Pass: the stage-matched ad beats the control on cost per purchase. Run both ads until each has at least 50 purchases or seven days, whichever is later, and apply your stop rules (when to stop a Meta ad test). That threshold is a recommendation. For an unaware ad, check hook rate (the share of impressions that watch the first three seconds of a video ad) first. Then iterate on the winner (creative iteration).

A win shows the message worked, not that the audience sat at that stage.

We collect authorized comments, replies, reactions and business messages with the ad, placement and format they came from. We remove personal information and spam, cluster the themes, and have a person review them before anything is used. Our review mining groups feedback by intent, objection, question and desired outcome, ranks themes by frequency, relevance, recency, severity and testability, and turns the strongest into test cards. They feed our ranked weekly test plans and creative briefs, alongside ad-performance data, competitor activity and past ad learnings. Our comment analysis guide covers the workflow. To see it on your account and ask about Deepsolv pricing, book a demo with our founding team.