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Almanac by PassBy answers questions about physical retail store performance, drawing on aggregated, privacy-safe visit data rather than requiring someone to build a report from raw numbers first. A Neotask agent connected to this integration can be asked which locations are busiest, how many people visited a specific store, or how foot traffic compares across different cities and brands, and it returns an answer directly instead of pulling data from a separate analytics tool beforehand. This fits retail teams, brand managers, or real estate planners who want a read on store performance without waiting for a scheduled report to land in an inbox or learning a new dashboard just to answer a single question. Because the data is aggregated and privacy-safe rather than tied to individual shoppers, comparisons across brands and locations work without raising the concerns that come with tracking specific people, so the agent can answer a broad performance question the moment it comes up in conversation rather than routing the request to someone else first.
| get_store_visits | Returns visit counts for a specific store location over a stated period, using aggregated and privacy-safe data. |
| compare_foot_traffic | Compares foot traffic across multiple stores, cities, or brands so differences in performance are easier to see at a glance. |
| rank_busiest_locations | Identifies which locations have the highest visit volume, useful for spotting where attention or resources might be needed. |
| get_traffic_trends | Reports how visit patterns are changing over a given period, showing whether traffic is rising, falling, or holding steady. |
A regional manager asks Neotask which of five stores has been busiest this month, since scheduling decisions for the coming weeks depend partly on where traffic has actually been concentrated. The agent queries Almanac by PassBy, ranks the locations by visit volume, and flags one store running noticeably above the others compared to the same period last month. That store had not raised any staffing concerns on its own, so the manager would likely not have looked at it otherwise. Prompted by the numbers, the manager reviews whether the current staffing level there still makes sense given how much busier the location has become, and adjusts the schedule before the gap turns into longer wait times.
A brand considering a new storefront asks Neotask how its existing locations perform in a few different cities being considered for expansion. The agent pulls aggregated foot traffic comparisons across those cities through the integration, giving the team a concrete data point to weigh alongside rent and demographic information before choosing where to expand next. One city shows noticeably stronger visit patterns for the brand's existing nearby locations than the others under consideration, which was not obvious from demographic data alone. The team factors that into the final decision rather than choosing based on rent and population figures without any sense of how the brand actually performs there already.
Aggregated, privacy-safe visit data rather than information tied to individual shoppers, which means questions about overall traffic patterns can be answered without raising concerns about tracking specific people entering or leaving a store.
Yes, comparing foot traffic across cities and brands is part of what the integration supports, so a question about how one brand's locations perform against a competitor's in the same city can be answered directly.
Instant, since the integration is built to answer performance questions directly rather than requiring someone to generate a separate report first and wait for it to compile before getting a usable answer.
Both, since a question can ask about a single store's visit count over a specific period or compare performance across many locations at once, depending on what the person actually needs to know at the time.
The agent reports the number as it stands rather than smoothing it out or explaining away an anomaly on its own, so a spike or dip still gets surfaced for someone to investigate further if it seems worth a closer look.
Yes, since comparing existing foot traffic across cities or neighborhoods gives a concrete performance signal to weigh alongside rent, demographics, and other factors that typically go into a real estate or expansion decision.