Time-to-Review (TTR): Measuring the Delay After a Customer Experience
A review is public evidence created after a private customer experience. Time-to-Review, or TTR, measures the time between the two events.
In one line
Time-to-Review (TTR) is the elapsed time from the completion of a customer's experience to the publication of that customer's first attributable public review. It runs from the experience to the review. It is not the time from a review request to the review, and not the time a business takes to reply.
The calculation
TTR for one reviewing customer = creation time of the first confirmed public review − time the experience was completed
TTR is reported as the median number of days among verified reviewing customers in a defined cohort. The median is used because a few very late reviews would pull an average away from what most reviewers did.
If 30 customers in a completed-customer cohort published a matched review, calculate the elapsed days for each of the 30 and report the middle value. If that value is eight days, the headline reads: Median TTR: 8 days (30 verified reviewing customers). The example is illustrative and is not a benchmark.
Time-to-Review is not response time
Four events get confused: when the customer's experience was completed, when the business asked for feedback, when the customer published a review, and when the business replied to it. Each interval is useful and each has its own name.
| Interval | Starts | Ends |
|---|---|---|
| Time-to-Review (TTR) | Experience completed | First review published |
| Completion-to-Request Lag | Experience completed | Review request delivered |
| Request-to-Review Lag | Review request delivered | First review published |
| Review-Response Time | Review published | Business reply published |
The acronym is shared. In software engineering, time to review means how long a pull request waits for its first code review. The two measures have nothing in common but the letters.
A shorter TTR is not always an improvement
Customers need enough time to find out whether the product or service delivered what was promised. A prompt at checkout may be badly timed for a complex installation or a professional service that takes weeks to evaluate.
The best evidence is a pair of field experiments by Miyeon Jung, Sunghan Ryu, Sang Pil Han, and Daegon Cho, published in the Journal of Marketing in 2023. Working with an online travel marketplace and an online apparel marketplace in South Korea, they randomly assigned customers to receive a review reminder at different delays or no reminder at all. In the markets they studied, an immediate reminder lowered the likelihood of a review compared with sending none, and a delayed reminder raised it.
The finding does not mean every business should wait a fixed number of days. It means timing is an empirical question: measure it in the context of the experience being reviewed.
Read CRR and TTR together
TTR describes only the customers who reviewed. A business could show a median TTR of one day because five highly motivated customers posted quickly while almost everyone else stayed silent. Another could show 12 days and a much larger share of its customers reviewing. Customer-to-Review Rate answers how many. TTR answers how long, among those who did. Neither substitutes for the other.
Data-quality requirements
- A trustworthy completion timestamp. A customer with no recorded completion date is left out and the gap is disclosed. The date is never guessed.
- The review's creation time, not its latest edit. A review written on day 8 and edited on day 100 has a TTR of 8 days. Where a platform shows only a date, TTR is reported in whole days and says so.
- A defensible link between the customer and the review. Unmatched and anonymous reviews are not assigned to a customer by guesswork.
- Negative values are investigated. A review dated before the completion date usually means a wrong completion record or an earlier visit. It is not averaged in.
- Non-reviewers are not zeros. A customer who never reviewed has no observed review within the window. That customer has no TTR, and is not counted as zero days.
What a reported TTR carries
A complete report states the median in days, the number of verified reviewing customers, the cohort start and end dates, the observation window, the platforms included, and how experience completed was defined. The 25th and 75th percentiles show the spread when the sample is large enough to support them.
Where it sits in the Marketing Helix
The Post-Purchase Helix describes customers who keep moving after a transaction and sometimes become a source of information for future buyers. Its review window is a claim about timing. TTR turns one part of that timing into an observed quantity, which supports better questions about service readiness, request timing, friction, and customer choice. It does not establish why any particular customer wrote a review.
Prior usage and attribution
The interval between an experience and a review is not a new subject. Review platforms and researchers have studied when customers review, and the experiments cited above tested request timing directly. Those authors did not propose the name used here. The Marketing Helix is publishing a specific reporting definition: experience completion to first confirmed review, median, verified reviewers only. It does not claim to have originated the idea.
Sources
- Jung, M., Ryu, S., Han, S. P., and Cho, D. (2023). Ask for Reviews at the Right Time: Evidence from Two Field Experiments. Journal of Marketing, 87(4), 528-549.
- Jung, M., Ryu, S., Han, S. P., and Cho, D. (January 10, 2023). Asking for Customer Reviews at the Right Time: Sooner Is Not Always Better. American Marketing Association.
How many completed customers actually review?
Customer-to-Review Rate measures the share of a completed-customer cohort that publishes a verified review inside a fixed window. Read the Customer-to-Review Rate definition →