Frequently asked questions

Workbench is an AI assistant that knows everything about your asset. Connect your footfall data, turnover, public reviews, competitor intelligence, spend patterns, and more, then ask questions in plain language and get answers, not dashboards. Think of it as an analyst who has read every data source about your property and is available instantly.

Leasing teams ask things like: which food and beverage brands are trending in our catchment but not yet in our mix? Marketing teams ask: how did my Christmas activation campaign perform? Asset managers ask: which of our tenants has the lowest sentiment score relative to its category average, and why? Ask it the way you would ask a colleague who had read every data source at once.

Most providers give you footfall counts and demographic tables, which describe who is nearby. Workbench is built on what people say about the places that are already trading there, and it gives you the answer layer on top: it connects the sources, identifies what is driving a change, and tells you what to do about it. Different question, different product.

Asset managers running a scheme, landlords and developers underwriting one, architects and master planners deciding a ground floor use mix, local authorities measuring high street health, and agencies briefing campaigns for a destination. There is a page for each of those at /benefits, covering the decision and the evidence behind it.

Drawing an area takes a couple of minutes. Collecting the places inside it runs in the background and finishes while you are still setting up. The analysis itself is the longer step, because it reads the underlying reviews rather than summarising a score, and you get an email when it is ready.

You draw it on a map. Not a radius around a pin and not a postcode district, but the actual boundary: one side of a street, a scheme and its immediate parade, a defined high street. Catchments rarely look like circles, and forcing them into one is where most area analysis starts going wrong.

The limit depends on your plan, and it exists because collection cost scales with the number of places inside the boundary rather than with the size of the polygon. A dense city centre and a retail park of the same square kilometre are very different jobs. If you need a larger boundary than your plan allows, we can raise it for your organisation.

Every place trading inside the boundary, with its category, rating, review count and location, and then the review text itself for those places. Reviews are collected across a rolling window of recent quarters with a per-quarter cap, so coverage is spread evenly over time instead of being dominated by whatever happened last month.

Yes, and comparing them is the point of several of the reports. Each area is a project in your workspace, and everybody in your organisation sees the same set. The free trial is limited to one project so you can see the whole flow before committing to anything.

Collection can be re-run for an area, and because the method is fixed rather than reinterpreted each time, the second run is comparable with the first. That matters more than freshness on its own: a number you can compare with the same number six months ago is worth more than a number that is merely recent.

We aggregate public review data, social media signals, brand tracking, location intelligence, and trend data, and you can connect your own footfall, turnover, and spend data. We layer AI analysis on top to turn it into answers rather than spreadsheets. We do not name our upstream providers publicly, and the analysis you get is our own work on top of them rather than a copy of anybody else's database.

Yes. Footfall, turnover and spend are the common ones, and they are most useful in combination with the public data rather than instead of it: your own numbers tell you what happened, the public data tends to explain why.

It says so. A category with two operators and eleven reviews between them cannot support a confident claim, and the reports mark differences resting on thin evidence as thin rather than presenting them as findings. An analysis that never says it does not know is not usable for a decision anyone has to defend.

A star rating is an average over years, weighted by whoever chose to rate. The written reviews are what people are saying now, and they name specific units, specific staff and specific problems. The two disagree more often than you would expect, and the text usually moves months before the average does. That is why the analysis reads the text.

Reviews are collected with a language preference set per organisation, and the analysis reads what is collected. If you work in a market where the reviews are predominantly in another language, tell us and we will set the collection up for it.

Seven standard ones: Area Analysis (what is in an area and what people say about it), Gap Analysis (your area against up to three others), Secret Shopper Report (one business, its real customer feedback turned into strengths and pain points), Tenant Fit Factsheet (a prospective tenant judged against your catchment), Social Media Profile Analysis (an account's audience, engagement and quality), Partnership Report (what a partnership is projected to be worth), and Sponsored Collaboration Impact (a pop-up or influencer roster modelled before you book it).

You choose. It compares the area you are in against up to three others from your own workspace, on mix, performance, customer voice, pricing and momentum, and it ends on a ranked list of gaps with the evidence behind each one. It will only ever compare projects inside your own organisation, and archived projects are excluded.

That is the Tenant Fit Factsheet. You give us the brand and the area, and it comes back with the local competitors, the customer experience picture, the audience, the pricing position and the category fit, on a page you can circulate to a landlord or a partner without walking them through it first.

Yes. Point Workbench at any competing centre and it reads the public reviews for what is trading there and surfaces what their customers say, with no manual research on your end. It is the same analysis you run on your own area, which is what makes the comparison meaningful.

No. The standard reports are the questions people ask most often, packaged so you do not have to phrase them. Everything else is a conversation: ask in your own words and it will use the same underlying data to answer.

Yes, that is by design. Every report is formatted to stand alone. You can forward a tenant fit analysis directly to a landlord or brand without needing to walk them through it. No platform access required on their end.

Reports export to PDF, and the charts and tables come with them. The intended use is that the export goes into a board pack or an investment paper as it is, rather than being retyped into a deck first.

Yes. The reports cite what they are drawing on rather than asserting conclusions, and the underlying places and reviews for an area are there to look at. If a finding cannot be traced back to something, it should not be in the report, and that is the standard we hold it to.

Both. You can run analysis on a single asset or query across your whole set of projects, for example asking which of your areas has the weakest customer sentiment this quarter and why.

Yes. Sign up, draw one area, and we collect the places inside it for free so you can see what is actually there. The full analysis costs more than the trial allowance holds, so at that point you raise a hand from inside the product and we pick it up. No call is required to get to that point.

Yes. You invite colleagues into your organisation and everyone sees the same projects and the same reports. Projects belong to the organisation, not to whoever created them, which is what stops the analysis leaving with the person who ran it.

The most common case is leasing: one well-matched tenant placement, or one avoided mistake, typically covers the annual cost. We can model the time saved versus manual research and share case study data from active clients.

For the public data, none. You draw an area and collection starts. Connecting your own footfall or turnover data is the only part that needs anything from your side, and it is optional and can wait until after you have seen the product working on the public data.

We analyse public reviews of businesses, which is commentary people chose to publish about a place. We are not tracking individuals, and we do not build profiles of visitors. Our full position is in the privacy policy at /privacy.

No. Projects, reports and any data you connect belong to your organisation and are scoped to it at the database level, not just hidden in the interface. A report you run is visible to your colleagues and to nobody else.

Export the reports you want before you go and they are yours to keep, as ordinary PDFs that do not need our platform to read. Ask us and we will delete the account data.