Affinect Research
·
Original visitor data
·
2026

From first visit
to second.

What 239,633 first-time recorded Wi-Fi visitors reveal about return behavior, and why recognizing a guest once is not the same as earning another visit.
Research cohort: January–June 2026
90-day follow-up verified
Observational analysis

239,633

First-time recorded Wi-Fi visitors

21.7%

Recorded a return within 90 days

27

Manually selected F&B-associated groups

A first visit is evidence that someone chose to try a business. It is not evidence that they will choose it again. To examine what happens after that initial interaction, Affinect analyzed first-time recorded Wi-Fi visitors across a manually selected group of F&B-related businesses.

Among 239,633 first-time visitors recorded between January 1 and June 30, 2026, 52,030 had a subsequent qualifying Wi-Fi visit within 90 days. That represents 21.7% of the cohort. The remaining 78.3% had no recorded return within the observation window.

This is a finding about observable Wi-Fi visit behavior, not a claim about all customer visits or a measure of whether any technology caused people to return. That distinction is central to reading the research correctly.

Most first-time visitors did not record a return within 90 days

Every member of the cohort had a complete 90-day follow-up period, including when the follow-up extended beyond June 30. Cumulative recorded return rates rose from 11.3% within seven days to 21.7% within 90 days.

Cumulative recorded return rate

Share of the 239,633 first-time visitors with at least one subsequent qualifying Wi-Fi visit

11.3%
17.6%
20.0%
21.7%
Chart scale: 0–25%. Rates are cumulative, not separate groups. Source: Affinect internal return-rate analysis, January–June 2026 first-time visitor cohort.
52,030
Recorded at least one return within 90 days
187,603
Had no recorded Wi-Fi return within 90 days
The commercial question is not only how many guests first appear. It is how many can be recognized again, and over what period.

Return behavior is concentrated early, but not exclusively in the first month

Of the entire cohort, 11.3% recorded a first return within seven days. A further 6.3 percentage points first returned between days 8 and 30; another 2.4 points between days 31 and 60; and 1.7 points between days 61 and 90. Differences use rounded headline rates.

Timing of the first recorded return

Percentage of the full first-time visitor cohort, shown in mutually exclusive intervals

Days 1–7 · 11.3% Days 8–30 · 6.3% Days 31–60 · 2.4% Days 61–90 · 1.7% No return · 78.3%
Intervals are calculated as differences between cumulative return rates. Percentages may differ slightly from the exact count-based figures because published rates are rounded to one decimal place.

Among the 52,030 people who recorded a return within 90 days, 42,155 had already returned by day 30. In this observed sample, that means approximately 81% of 90-day returners had returned within the first month. This is a descriptive finding, not evidence that a universal 30-day marketing sequence is optimal.

What these findings mean for hospitality operators

For restaurants and cafés, the first customer visit is often the easiest to celebrate and the hardest to evaluate later. Launch activity, curiosity, location and convenience may all generate initial traffic. But how many of those guests become a regular part of demand is a separate question.

The Affinect results suggest three useful disciplines for operators.

Distinguish initial visits from repeat behavior

Gross visits can increase while the share of identifiable guests who return remains weak. A new venue should establish how it will recognize first-time visitors, subject to appropriate privacy and consent practices, and track their subsequent observable visits.

Track the return window, not just the database size

Counts of customer profiles measure reach into the identifiable audience. They do not tell an operator whether new visitors become repeat visitors. Cohort-based 7-, 30-, 60- and 90-day measurements make that distinction explicit.

Avoid confusing recognition with permission to market

A recorded Wi-Fi identity does not automatically mean a person opted into promotional email, WhatsApp or SMS. Recognizing visits, holding usable contact information and possessing valid channel-specific marketing permission are different measures and should be reported separately.

What this study does not establish

The data should not be interpreted as a restaurant customer retention benchmark. It covers 27 manually selected F&B-associated groups, not an independently sampled population of restaurants. Some groups have multiple venues or mixed activities. Results are pooled at the group level, meaning a recorded return could occur at another participating venue in the same group.

Likewise, this is Wi-Fi-observed behavior. A person may physically revisit a venue without connecting to guest Wi-Fi. The percentage with no recorded return therefore must not be described as the percentage who never came back. Multiple Wi-Fi sessions on the same day are counted as one visit in this analysis.

Finally, the study does not measure transaction value, profitability, marketing exposure, loyalty redemption or incremental visits caused by communications. It cannot establish that collecting guest data or using Affinect improves return rates. Those outcomes require additional analysis with appropriate comparison groups.

A practical measurement approach from day one

A business does not need an elaborate loyalty program to begin learning about its guests. It needs a measurement setup that can be maintained during ordinary service.

  • Before opening: choose an unobtrusive identification path, define data ownership, confirm consent wording, and assign responsibility for reviewing guest metrics.
  • During the first month: measure first-time identified visitors, record visit quality and gather feedback without assuming every guest should receive a discount.
  • During months two and three: examine first-to-second recorded returns at consistent intervals, compare suitable guest cohorts and test relevant follow-up only where permission allows.
  • By month six: decide whether loyalty, offers or additional channels solve a demonstrated problem, rather than installing them solely because they are available.

These steps improve an operator's ability to observe and act on guest behavior. They do not substitute for product quality, service consistency, value or location, all of which affect why people return.

Methodology and limitations

Data source
Affinect internal anonymized, aggregated guest Wi-Fi visit analytics. No individual, customer or group records are included in this publication.
Sample
239,633 first-time recorded visitors across 27 manually selected F&B-associated groups. The selection is purposeful rather than statistically representative; the sample may include groups with mixed hospitality or leisure activities.
Cohort entry
Each included visitor's first recorded qualifying Wi-Fi visit occurred between January 1 and June 30, 2026.
Return event
A subsequent qualifying Wi-Fi visit by the same recognized visitor. Multiple connections on the same calendar day count as one visit.
Recognition scope
Group-level. A subsequent visit to another venue within the same group counts as a return. Cross-venue behavior is understood to represent only a very small share of the population, but its exact contribution was not measured in this analysis.
Follow-up
The Affinect data team verified that every member of the cohort had the full 90 days for subsequent visit observation, even when the window extended past the cohort end date.
Reporting
Cumulative return counts: 26,968 within 7 days; 42,155 within 30; 47,946 within 60; 52,030 within 90. Percentages are rounded to one decimal place.
Limits
Wi-Fi connection is not a proxy for all physical visits or purchases. The analysis does not demonstrate causal uplift from CRM, messaging or loyalty activity. Loyalty-recorded visits are not included.

Source: Affinect internal first-visit cohort report (January 1–June 30, 2026), manually curated F&B-associated group sample. Methodological definitions and 90-day completeness verified by the Affinect data team, October 2026.

Research conclusion

Recognizing a first visit is the starting point, not the result.

The data documents a measurable gap between first-time recorded Wi-Fi visits and subsequent observed visits. For hospitality teams, the practical case is to establish reliable guest recognition and cohort measurement early, then make decisions using actual behavior rather than assuming opening traffic will become repeat demand.

See how Affinect turns recognized guest visits into measurable return behavior.

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