Location Intelligence 101: A Guide for Retailers
Don’t make decisions without the data. We break down the reasons why location intelligence is essential for retailers looking to super-charge their strategy.
The last three years have not been kind to retail. A constant tide of circumstances beyond – for the most part – the direct control of the retail industry, has influenced footfall traffic, business rates, right through to the spend of consumers once they hit the high streets, retail parks and shopping centres. The tides are, however, receding – and by grasping the opportunities available in location data, retail leaders can make informed decisions that win them market advantage. As a leader in the location-based insights space, Huq is here to empower retail industry organisations with the strategic intelligence to create environments that attract more returning customers, and ultimately uptick sales. Think of us as your personal solution-based advisor. We tailor our approach to your business to drive improved sales results.
Let’s get into it.
In November 2023, the UK’s British Retail Consortium (BRC) – informed by destination data – observed that consumers are moving away from shopping around; less seduced by the lowest prices, and instead focus-purchasing and paying more to “buy less”. Consumers are adjusting to the inflation-driven cost of living crisis and are making strategic decisions when purchasing. Industry leaders, the BRC concluded, could do well to concentrate efforts on customer loyalty and reaching consumers earlier, to earn customer loyalty and get customers returning more frequently to spend more.
Understanding this shift in consumer behaviour wouldn’t be possible without consumer, location-based data. And this is where Huq comes in. We are the leading provider of rich and real-time geospatial data that can help leading retail strategists stay ahead of the curve, and even predict consumer behaviour to achieve a competitive advantage.
Our cutting-edge platform harnesses unrivalled, first hand and third-party global sources to deliver unrivalled insights to our clients. Our unique research data sets, summarised below, ensure you are capturing the right store performance metrics will inform site selection and store KPI evaluation. All delivered with up-to-date accuracy, in real-time.
Let’s dive in.
Footfall
Our footfall traffic insights can be tailored within our user-friendly, dashboard to provide hourly, daily, weekly, monthly and annual footfall data – right down to a specific location. We have historic location data going back over 5 years – enabling you to look at the curve of behaviour and determine trends. Learn how your local area is being visited and unlock how to best deploy location-based marketing, most accurate sales forecasting, and surface the potential for the best stores.
Density
Pinpoint the busiest regions in a nominated space. Understanding density of visitors highlights the underutilised areas of your space and opportunities for improved utilisation.This localised intelligence can be used to inform retail expansion strategies and geo-targeting the most optimum consumers.
Dwell
Once more, beyond footfall, it’s vital to understand how long individuals are spending in a given place and space. The propensity to shop and spend after all relies on consumers sticking around, and understanding dwell time-to-conversion presents a major advantage. Our dwell time data could be used to inspire retail spatial analysis strategies, as well as leading to customer behaviour and competitor location analysis – and even collaboration.
Catchment
By connecting visitors to geographic movement and – anonymised – demographic detail, retailers can better hone demographic segmentation for products and services. Here’s how you can distinguish which consumer demographics are attracted to some spaces more than others. The combined quantitative and qualitative scope of this data set will empower your operational, financial and marketing teams to create strategies for success.
Don’t take our word for it, we work with some of the market’s largest retailers and hospitality merchants who use our proprietary data insights to make informed strategic decisions that support better business. One such client is JD Sports, who utilised our Catchment Areas insights to measure the size and fit of consumer opportunity. This drives decisions when assessing new store locations – taking into account competitive influence intelligence and the potential impact on nearby outlets – so as not to cannibalise existing customer segments.
This is a significant step-change for JD Sports when comparing data to, say, more generalised drive-time catchment information. As Alastair Browne, Group Head of Site Research and Strategic Insight at JD Sports puts it, “Huq’s Catchment Insights allows JD to more accurately assess the impact of the wider retail catchment area of the sales potential of new store opportunities.”. With 900 store locations, and annual revenue of £10.12bn, Huq’s core products for retail are a staple, and invaluable, tool for JD Sports to remain competitively advantageous.
JD Sports’ CEO, sums it up even more simply…
Huq’s catchment analysis forms a key role in our new store approval process.”
How we work with you
Our customer success team works directly with you to ensure alignment with your aims and business objectives, providing a solid environment to create strong strategies and make game-changing decisions. We will support you to create compelling data-driven narratives that support your initiatives for stakeholders including Board, C-suite, internal, external partners and colleagues.
Huq is trusted by over 300 partners, including major retailers, news institutions, the top 5 real estate brands, over 100 Government organisations, and internationally esteemed university research teams. Our experience demonstrates you’re in safe hands when it comes to leveraging crucial cutting-edge technologies – made straightforward by our experienced and personable team.
For Store Planners of Franchisees
Imagine a world where uncertainty fades away, and every decision you make is backed by precision. Huq steps in as your partner, meticulously confirming the potential of new locations through both quantitative and qualitative success criteria. No longer will a location’s performance remain a mystery; Huq unravels the truth through side-by-side ranking with direct sales-informing metrics. Analysing trends across diverse timelines empowers you to discern correlations and take decisive actions with confidence. With a centralised view of all your locations, delve deeper into demographics and competitor capture rates, enabling unparalleled insights for your strategic planning.
For Market Planners and Strategy Leaders
In the realm of market expansion, Huq emerges as your indispensable ally, elevating your strategy with real-time insights to identify and monitor potential locations for exponential revenue growth. Gain an unparalleled advantage by being the pioneer in discovering burgeoning areas before your competitors, supported by Huq’s cutting-edge data. With precision, Huq crafts a curated list of high-quality expansion sites grounded in real-time data insights, ensuring every decision is underpinned by accuracy and trust. Benchmarking crucial KPIs becomes effortless, guiding your vital decisions with a firm foundation of reliable data. Huq isn’t just about expansion; it’s about understanding consumer behaviour intricacies, refining development projects through in-depth consumer movement analysis. Huq empowers you to boost sales predictions, seize lucrative opportunities, and sculpt an expansion strategy that leads the market.
For Optimisation and Portfolio Managers
Huq presents the gateway to unlocking the full potential of your existing portfolio, transcending traditional strategies to meticulously optimise and maximise your investments. Seamlessly identifying gaps and circumventing cannibalization, Huq’s data is built to help you ensure peak performance across your entire estate. It’s not just about identification; Huq delves deep into customer behaviours, distinguishing between successful and unsuccessful patterns to guide your decision-making. Picture a comprehensive ranking of potential locations, empowered by sales-informing metrics that validate your strategies against a myriad of metrics, guaranteeing confidence in every move. Huq doesn’t just stop at identification—it captures your target audience precisely where they are, enabling swift and assured action driven by real-time data. Don’t let opportunities slip away; Huq illuminates the metrics underlying store triumphs or setbacks, giving you the power to optimise and elevate your portfolio to unprecedented heights of success.
For Impact
Retailers must be increasingly demonstrative of Environmental, Social and Governance (ESG) commitments, and transparent to an ever-demanding consumer and colleague base. New and existing customers smell, see, and sense any deviation from authenticity. And they let retailers know their disapproval through their purchase power, spending with social conscience.
So, our advice?
Make the high-level business decisions easier with the right location, footfall, dwell and density, and catchment intelligence. Leaving you more time to concentrate on product, people, and planet.
Consider us a colleague and cheerleader – keen to see you put your best foot forward and stride on armed with the toolkit to take on the rest.
We would love to work with you – today – on your retail strategy, informing your leadership team with the insights that mean you can do what you do best. We’ll help you optimise and grow your customer base, and you can ensure colleagues are supported and driven by your company’s success.
So, make the right decisions with data as unique as your offering. Visit Retail – Huq Industries to book a demo, call us with your questions, and we look forward to meeting you.
They say the sky’s the limit. With Huq the ground is the launchpad.
Location Intelligence 101: A Guide for Real Estate
Pinpoint prime investments with data-driven decisions. We explain how location intelligence can unlock the keys to the right real estate – for investment and development that delivers.
In a market that is riddled with complexity – perceived and real – location intelligence helps real estate industry leaders gain vital competitive advantage and cut-through clarity. Huq understands this data more than anyone. Some of the challenges facing the real estate sector you’ll be familiar with include rising inflation and spiralling interest rates (now, thankfully coming down or at least stabilising), the long tail impact of Covid 19 on decentralisation, and – of course – regulatory factors.
Let’s get into it.
Post-Covid working, as an example, has led to a substantial flow of people and resources away from dense urban areas and into suburbs and even further afield. As ‘the local’ is experiencing a revival, the business district and so its property market – particularly commercial – faces a decrease in demand. How then does a portfolio property investor / developer choose the optimum space to purchase?
As ever, location intelligence and live demographic data is key. Real estate data insights have traditionally focused on conventional metrics like occupancy rates, rental fees paid by tenants, and local market trends. More recently however, there’s a growing appreciation of the power of non-traditional variables – like the growth and positioning of local pop ups and stores (think the proliferation of indie coffee shops), localised online reviews (Google, Yell, Trusted Reviews, and app-based Swarm – that was once Foursquare). It also pays to explore any influx into an area of businesses, retail, and hospitality; the latter would not open up if it wasn’t confident there’d be people willing to part with cash for their croissants, carrot cake, or Calamari.
Let’s look at Wimbledon town centre as a microcosm of this. Covid became the death knell for many of the brands associated with casual footfall in this south-west London town, better known for its serve than its shopping to be fair. Sure enough, its prime retail complex, Centre Court, became a ghost mall of boarded doors and white-misted windows. The Broadway high street also suffered terribly. However, post-Covid and – we’re certain – the result of a smart evaluation of localised intelligence, catchment demographics, and geospatial data, has led to an incredible property development investment (plaudits to Romulus, the group in question); and the christening of the new ‘Wimbledon Quarter’. There has been a disassociation of the old mall from its tennis tournament neighbour, and replacement with a new vibrant space for an economically mobile, and greener-leaning demographic to “connect, engage, and thrive”.
Gone are the brand staples, which are catered for either in retail parks, nearby towns, and a huge consumer pivot to online. In their stead is a bespoke wall-climbing franchise, an indoor golf entertainment and light food-driven enterprise, and a large seasonal pop-up area – currently hosting a modest ice rink, and crepes and Christmas gifts outlets.
Only intensive, but user intuitive, analysis of location data and demographics informs decision making to invest in the right kind of property development. We’re sure (even) more housing will follow.
This is but one example. There is also a widely reported growing ageing population in the UK, which in turn presents challenges for accommodation for this demographic – as multi-generations may have to live together, and care environments bulge and bend at the seams. This market is well worthy of exploring, to help deliver best in class real estate to build communities and support individuals and families – through dignity, independence and affordable housing.
How can you make location your competitive advantage?
We want to help ensure property site selection is low risk, repeatable, and data-driven.
These factors can be refined and improved by adding even more layers of location-based data, via Huq’s expertise and market-leading tools.
Let’s look at some examples:
Footfall
Which areas, centres, businesses get the most foot traffic, and which ones get the least? Which ones are on the up versus declining?
Density
This data can identify what kinds of stores’ customers visit a given area or district. Are there out-of-the-way venues that are popular also, that could be reached by a close drive or transport? These are all decisions forming values.
Dwell
How many people visit a business area? How long did they spend there? How does current foot traffic compare to last year or to 2021 and even before Covid? Which days are the most crowded? These are all key indicators for real estate investors that can support making sound, informed judgements – where premium investment is vital.
Catchment
By capturing geographic movement and – anonymised – demographic detail, developers and investors can see live and historic detail on demographic segmentation; aiding real estate market forecasting as to who these groups are and what they care about.
How we work with you
There are a myriad of ways Huq’s core location expertise could help identify successful investment strategies for property location optimisation, including:
For Investments
As we’ve talked about, areas visitors’ insights can power decisions and identify promising real estate site selection; and observe and capitalise on property investment trends.
For Marketing
Target the right stakeholders through real estate market insights.
For Competitive Benchmarking
See where you stand based on market intelligence, gleaned from location intelligence solutions.
For Housing and rental optimisation
Attracting tenants and finding the right vacant units through real estate market research.
We want to help ensure property site selection is low(er) risk: i.e., repeatable, and data-driven. These factors can be refined and improved by adding even more layers of location-based data, via Huq’s expertise and market-leading tools.
So, how does it work?
We are a dedicated and experienced team who first work to identify your needs, and will recommend the right Huq tools to get the intelligence you need. Huq works directly with you to ensure alignment with your Board, your business objectives, and aspirations. And our user-friendly and tailorable dashboard software lets you see the detail in the data and help join the dots.
You can rely on us to provide a supportive environment to make game-changing decisions, as we did with Aviva Investors.
As Jonathan Bayfield Head of UK Real Estate Research at Aviva Investors told us, Huq data
“Huq data helps [Aviva] to make better investment decisions and allows us to appropriately manage risk on behalf of our investor clients.
[For instance] Huq’s mobility data allows us to measure footfall, almost in real time, by submarket and by region.”
We are trusted by over 300 partners, including Aviva Investors, Colliers, CBRE, Cushman & Wakefield, not to mention major retailers, news institutions, and over 100 Government and university research teams.
Decision making is only as good as the data you put into it, and we’ve looked at how footfall, density, catchment, and dwell all add up to provide a real-time picture of a destination, and a place to call home.
We would love to engage our world class location intelligence suite, to help you make the right decisions when it comes to strategic and – ultimately profitable – property investment. We welcome the chance to support your real estate strategy, empowering you with the accuracy and reliability of real-time insights that will make the future come alive with possibility. Visit Real Estate – Huq Industries to book a demo, we’d love to talk and show you around.
They say the sky’s the limit. With Huq, destination data is destiny.
How KraftHeinz used Evidence for High-Frequency Demand Forecasting
How the third-largest food and beverage company in North America developed high-frequency demand forecasting across key market segments using Huq’s insights platform.
The Need
The Kraft Heinz Company is the third- largest food and beverage company in North America and the fifth-largest food and beverage company in the world, with eight $1 billion+ brands. With that scale of manufacturing and supply operations at stake, the company needs an accurate and detailed understanding of demand in its key markets and how that changes over time.
This intelligence allows KraftHeinz to plan efficiently and to minimise waste – especially as some of its products are perishable. Reuben Ayley, Head of Food Service Finance (International), plays a central role in this decision- making and came to Huq looking for solutions to help the company forecast demand across specific channels internationally, on a near-realtime basis.
The Solution
A large proportion of KraftHeinz’s Foodservice products are distributed and sold through bars, hotels, cafes and restaurants. In all of these places, the level of demand is determined by the customer footfall volume across those outlets. Huq’s global mobility data comes ready-enriched with place attributes, including place types. This makes it uniquely positioned to disambiguate trends across different types of outlet – or channels – and geographic markets.
Huq’s Customer Success and Engineering teams supported KraftHeinz during an initial discovery phase, helping them to structure outputs in the way that represented greatest value to them and made them readily actionable. Together they worked to group Huq’s native outlet types to match KraftHeinz’s own internal taxonomy, and experimented with different update intervals and aggregations to produce the most effective set of results.
Once the form and structure were agreed and verified on both sides, Huq scheduled a regular feed to deliver updates to Reuben’s team via an interactive dashboard.
The Results
Having access to in-store customer trends insights at this frequency and definition was a first for the International Finance team at KraftHeinz. It helped the company to plan their manufacturing and supply operations by accurately anticipating demand across different channels in markets ranging from Japan to the US to France. This new sensitivity to changing levels of demand has become a benchmark for planning internally. It is especially important now as the global market treads a path between pandemics, rising costs and changes in disposable income.
Evidence is crucial for KraftHeinz
Reuben Ayley, Head of Food Service Finance (International) said –
This data enables us to gain insight into a crucial aspect of our business that would otherwise not be possible. Using it enables us to anticipate demand and create more robust planning.”
Verifying In-store Footfall Accuracy Using Sales Performance Results
This article shows how mobility data can be used to accurately predict net sales results for consumer- driven businesses like Walmart, the leading US big box retailer.
The Objective
The goal is to extract results from Huq Industries’ Footfall and Dwell-time modules that are highly correlated with the net sales figures published by Walmart in its quarterly trading updates. This output can then be incorporated into downstream models and systems to inform research for analysts and investors.
Step by Step Guide
Step 1: Get Walmart net sales data
Walmart publishes its net sales data within its quarterly trading updates, which can be found on its Investor Relations webpage. Note that for the purposes of this analysis, use is made only of the ‘Walmart US’ net sales segment.
Step 2: Find Walmart store visits
Huq’s event-level mobility data serves as a proxy for consumer demand across Walmart’s US stores. This event-level data is pre-enriched by Huq Industries in a process that extends raw geo-spatial data to include point of interest (POI) attributes such as business name, type and location.
Extracting Walmart visit data is therefore made easy by filtering on the raw place name (place_name), the standardised name (brand_name), or indeed by ignoring the POI attributes and using the WiFi SSID observed by the mobile device (impression_ssid) to match Walmart-specific patterns.
Step 3: Extract Walmart store visits
One way to quantify demand across the Walmart estate using Huq’s enriched geo-spatial data would be to count the number of distinct mobile devices (ie. panelists) present at Walmart each day. This approach can be useful in many analyses but after much experimentation there is a second strategy that produces results that more closely reflects behavioural nuance – and this is related to dwell.
During the same enrichment process that supplies the point-of-interest attributes, an estimate of dwell is also calculated and added to the resource. These properties can be accessed and manipulated via the columns impression_dwell_lower_bounds and impression_dwell_upper_bounds, which represent the upper and lower estimate for visit duration. These are calculated using the cumulative elapsed time calculated by continuous observations of a mobile device in the same place.
For the purposes of this study however, it is beneficial to develop a measurement of dwell that is less strict. The strategy used in this exercise groups observations into visits where they occur within 65 minutes of each other – without requiring them to be continuous per se.
Step 4: Test and training datasets
Walmart provides seventeen quarters of historical results via its investor portal. These are split into two sets; one to use for our training set and the other to test our output against. The training set helps us to select the optimal combination of parameters from the signal candidates described in Step 6. How this is evaluated is explored in Step 7.
The first twelve rows are chosen for training, and the remaining five are retained for testing. Separating them chronologically avoids test information leaking into the training process and causing lookahead bias.
Step 5: Define rough signal form
At this point take the training set from Step 4 then prepare it by eliminating behavioural outliers and concretely defining our measure of ‘dwell’.
i. Preparing the data
It is very common to find elements of noise within a dataset, and Huq’s enriched ‘Events’ feed is no exception. Some characteristics may be derived from interference at the sensor level; some artefacts may be behavioural and completely natural. As our demand metric relates to dwell, it is necessary to eliminate data points that show excessively little or large dwell before applying it. Filtering the data in this way excludes facets such as Walmart employees or other false positives derived from the enrichment process. Our chosen strategy filters the detected dwell value by an upper threshold Du , a lower threshold Dl and also determines whether to filter on a daily or per-visit basis, Db.
ii. Transform dwell into ‘demand signal’
Let’s assume that dwell-time and spending money in- store is a non-linear relationship. Specifically, let’s suggest that there is a ‘normal’ level of dwell Bm and a ‘normal’ propensity for Walmart store visitors to spend, Bbase, both of which are constants.
We can then raise Bbase by the difference between the observed dwell value and the ‘normal’ value, Bm. To keep this value from exploding or vanishing, it is expedient to truncate the difference in the range of Ol to Ou before raising the power.
This can be summarised as follows:
iii. Normalise the data for panel growth
The size of Huq’s mobility panel changes over time as the number of apps supplying data increases, and apps’ own audience sizes fluctuate. As this study results in a time-series output, it is imperative to account for these changes in the normalised result so as to accurately represent the real trend. Similarly, it is also important to account for growth in the number of daily measurements observed per device using Huq’s measurement software in order to maintain a consistent view of ‘dwell’.
It may also help to consider how these characteristics vary geographically. The normalisation strategy employed in this exercise works by dividing the ‘demand signal’ observed across Walmart locations by the equivalent metric for the full US panel on equivalent day. This approach may be further improved by normalising on a localised basis to account for regional variations in data coverage, and by pre-filtering the data to remove individual app or panelist outliers.
iv. Respect seasonality in signal generation
Different week parts – weekdays, weekends and public holidays – have significance for in-store retail behaviour, and it is beneficial to recognise this in signal preparation. Accordingly, the normalised output is grouped using this classification, and is supplied to the model independently.
Step 6: Test and training datasets
The many possible combinations of parameters in Step 5 produce a huge number of candidates for signal representation, numbering 750K+. So, which candidate set offers the closest match to Walmart’s net sales values? A simple regression model (see Step 7) allows us to identify the best candidate set.
Step 7: Regression and validation
On the basis that we can expect longer dwell-times to lead to higher net sales results, a suitable model to use in this instance is non-negative least-squares regression as the inductive bias is well suited to this problem.
How do we know which signal output is best suited to net sales prediction? We’ll look for the result with the smallest mean absolute percentage error (MAPE), and use ‘leave-one-out cross validation’ to make best use of the limited supply of training data available in Walmart’s quarterly net sales figures archive.
The end result

The Pearson correlation between the output of the regression model and Walmart’s actual net sales figures on the (completely unseen) test set is ρ=0.85, with a MAPE of just 3.8%.
Conclusions
Using this parameter selection strategy it emerged that the optimal preparation steps and parameters are:
(i) remove dwell-time outliers, keeping daily device dwell values in the range of 0 to 160,
(ii) construct ‘demand signal’ by subtracting 30 from the daily dwell figure, and bound to the range of -12 to 60, then raise to the power of 1.03
(iii) normalise by counting 2hr-truncated timestamps across the full US dataset, where devices must have visited a non- residential location
Lastly, aggregate results by day and divide the ‘demand signal’ by this value.
Insight reliability is key
Senior Data Scientist, Large US Asset Manager said –
We have tested Huq’s footfall and dwell-time data in our forecasting models and found that it added significant benefits to the accuracy of our signal.”
Hourly Footfall
Hourly Footfall
When are we busiest?
Find out when the peak times are for your green spaces, town centres, shopping centres and retail parks. Use Hourly Footfall to track performance.
Knowing when people choose to visit tells us a lot about why they come
- Night Time Economy Manager,
District Council



What is Hourly Footfall?
Hourly Footfall is a measure of the number of unique visitors present at an area split out by hour of day and day of week.
Why use it?
Understanding when people visit informs how best to manage and maintain local spaces. Compare weekdays and weekparts to track trends in commuting patterns, leisure activity and the effect of your interventions. Retailers use Hourly Footfall to help optimise their retail estate portfolios.
- Daily hourly footfall reports
- View trend and daily results
- Get actual and indexed values
- Make year-on-year comparisons
- Any place, any size, anywhere
- Up to 4+ years' data history
- Benchmarking data available
- Full nationwide coverage
- Compare with multiple places
- Income demographic filters
- A zero-hardware solution
- No installation or maintenance
- Export results data as CSV
- Download live reports as PDF
- Fine-grained date filters
- Data accuracy validated
- Training & support included
- Used by 50+ UK councils
"What's the busiest day for footfall locally?
Economic Development Officer, County Council
"What's the optimal time for maintenance?
Parks & Open Spaces Manager, City Council
"When can we expect peak traffic flows?
Transport Planning Manager, District Council
No hardware. Instant setup. History included out of the box.
Frequent Updates
Monitor performance across the places and centres you manage in near real-time. Use high-frequency insights to plan and react at pace.
4yrs History
Huq provides up to 4yrs of monitoring history for every new location out of the box, making annual comparisons fast and easy.
Instant Setup
Get access to Huq's monitoring platform today! Instant setup. No hardware, cameras or any other infrastructure needed.
UK Coverage
All Huq's place monitoring products are available for any location in the UK and beyond. Any place, any size, anywhere - country wide.
Related products
Often bought together
Explore companion products from our insights platform!
Browse modules ➜



One-to-one customer success support built in
Huq's unique Customer Success offering provides hands-on training and support in reports creation for each and every one of its customers. Learn to interpret, visualise and talk about your data!
- Hands-on user training
- Custom report building
- Expert advice & support
Granular Catchment
Granular Catchment
Where do visitors come from?
Discover where visitors to places travel in from. This precision module offers the ability to quantify how many visitors come from each postcode district. Use Granular Catchment insights to enrich your footfall data!
This granular insight allows us to quantify how many visitors come which postcodes
- Visitor Insights Manager,
National Park Authority



What is Granular Catchment?
Granular Catchment is the first ever product that quantifies number of visitors to specific destinations according to where they travel from.
Why use it?
Use Granular Catchment to understand the impact of accessibility projects - ie. public transport improvements - on local and wider mobility. Explore the impact of events and interventions in terms of town centre appeal. Measure how seasonality affects how tourists visit an area.
- Export data as CSV
- Uses postcode district units
- Footfall insight enrichment
- Understand seasonal trends
- Measure accessibility projects
- Monthly reporting cycle
- Up to 4+ years' history
- Quantify tourism volumes
- Available for any town or centre
- Download live reports as PDF
- Hardware free solution
- Instant monitoring insight
- Full nationwide coverage
- Data accuracy validated
- Training & support included
- Year-on-year comparisons
- Used by 50+ UK councils
"Has increased marketing spend attracted visitors from further away this summer?
Economic Development Officer, County Council
"Since our transport improvements have we seen positive in accessibility?
Senior Transport Planner, County Council
"What's our conversion rate for visitors travelling from this location?
Store Planning Manager, National Multiple Retailer
No hardware. Instant setup. History included out of the box.
Weekly Updates
Monitor performance across the places and centres you manage in near real-time. Use high-frequency insights to plan and react at pace.
4yrs History
Huq provides up to 4yrs of monitoring history for every new location out of the box, making annual comparisons fast and easy.
Instant Setup
Get access to Huq's monitoring platform today! Instant setup. No hardware, cameras or any other infrastructure needed.
UK Coverage
All Huq's place monitoring products are available for any location in the UK and beyond. Any place, any size, anywhere - country wide.
Related products
Often bought together
Explore companion products from our insights platform!



One-to-one customer success support built in
Huq's unique Customer Success offering provides hands-on training and support in reports creation for each and every one of its customers. Learn to interpret, visualise and talk about your data!
- Hands-on user training
- Custom report building
- Expert advice & support
Footfall
Use footfall data to learn how many people visit places
Get the leading footfall counting system built for decision makers in Local Government, BIDs, Retail and Real-estate teams.
Footfall monitoring is the single most important insight we use to manage places
- Head of Economic Development,
County Council



Accurate Footfall Monitoring
How many people are in this place?
Learn how many unique visitors are present in the places you manage, and how that changes with time. Verified people counting methodology. No double counting!
- Daily footfall counts
- No hardware needed
- Available UK-wide
- Any place of any size
- Up to 4+ years' history
- Demographics included
Getting started is easy
Simply trace your places, and go!
Get instant footfall counting data for any place of any shape or size - UK wide. Use our specialist place tracing tools to define the area you want to cover and get accurate results today!



Get the free report
In 2021-22 UK Govt. DHLC made £56 million in funding available to UK councils.
Huq analysed footfall performance for centres UK-wide to rank the greatest winners during that period.
Start measuring footfall traffic today!
Step 1: Get a personal demo
Get a personalised demo with our team of experts
Step 2: Trace your places
Define the areas that you would like footfall data for
Step 3: Get monitoring!
No equipment, no installation. Start monitoring your places today!
Dwell
Use dwell-time to find how long people spend in places
Get accurate visitor dwell-time insights made for decision makers in Local Government, BIDs, Retail and Real-estate teams.
Dwell-time provides leading indicators on the performance of the local economy
- Head of Economic Development,
County Council



Dwell-time Monitoring
How long do visitors spend in this place?
Dwell-time is a measure of the average time that visitors spend within an area per trip. Get the output in minutes, updated everywhere on a daily basis!
- Daily dwell-time reports
- Results given in minutes
- Organise by day of week
- Group by hour of day
- Over 4 years' history
- Available nationwide!
Getting started is easy
Simply trace your places, and go!
Get instant visitor dwell-time data for any place of any shape or size - UK wide. Use our specialist place tracing tools to define the area you want to cover and get accurate results today!



Get the free report
In 2021-22 UK Govt. DHLC made £56 million in funding available to UK councils.
Huq analysed footfall performance for centres UK-wide to rank the greatest winners during that period.
Start measuring visitor dwell-time today!
Step 1: Get a personal demo
Get a personalised demo with our team of experts
Step 2: Trace your places
Define the areas that you would like dwell-time data for
Step 3: Get monitoring!
No equipment, no installation. Start monitoring your places today!
Density
Density Monitor
Discover local visitor hotspots
Find the most popular parts of towns, streets and green spaces with visitor density monitoring.
Density monitoring helps us find the most used parts of our towns
- Town Centre Manager,
Borough Council



What is Density Monitoring?
Density monitoring is a visualisation of pedestrian flows and hotspots across whole towns, streets and centres. Density maps are updated daily.
Why use it?
Determine the places that attract most visitors to the areas you manage. Find the most valuable retail opportunities for within a centre or street. Learn how best to manage and maintain parks and spaces based on usage.
- Daily density heatmap outputs
- Hotspot granularity to 10m
- Density score value provided
- Measurement of the full area
- Any place, any size, anywhere
- Up to 4+ years' data history
- Fine-grained date filters
- Compare with multiple places
- Download live reports as PDF
- A zero-hardware solution
- No installation or maintenance
- Full nationwide coverage
- Data accuracy validated
- Training & support included
- Year-on-year comparisons
"Have our changes brought people to new areas?
Town Centre Manager, Local District Council
"Where do different income groups spend time in our town?
Parks & Green Spaces Manager, County Councity
"Shall we open a store at this end of the road?
Estate Planning Manager, Multiple Retailer
No hardware. Instant setup. History included out of the box.
Weekly Updates
Monitor performance across the places and centres you manage in near real-time. Use high-frequency insights to plan and react at pace.
4yrs History
Huq provides up to 4yrs of monitoring history for every new location out of the box, making annual comparisons fast and easy.
Instant Setup
Get access to Huq's monitoring platform today! Instant setup. No hardware, cameras or any other infrastructure needed.
UK Coverage
All Huq's place monitoring products are available for any location in the UK and beyond. Any place, any size, anywhere - country wide.
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One-to-one customer success support built in
Huq's unique Customer Success offering provides hands-on training and support in reports creation for each and every one of its customers. Learn to interpret, visualise and talk about your data!
- Hands-on user training
- Custom report building
- Expert advice & support