How to use retail data to enhance business profits: increase conversion ratio, average transaction value and number of items per transaction in just three months.
Many retailers collect people counts, but few use the information to its full potential. Here’s why they are missing out on easy opportunities to grow sales.
It’s not the number of people going into the store on which they need to focus, but what the potential customers do when they get there.
Converting more browsers into customers, increasing the amount they spend and upping the number of items they buy can massively increase sales from the shop visitors they already have. This is achievable in just three months.
Step 1 – Collect the Data
The first step is to install a video counting system and collect data on, for example,
- Number of people entering the store
- The most popular areas visited by shoppers
- Conversion rate
- Average transaction value
- Average number of items in a shopping basket
- Average shopping time
- Time until first contact between staff and customer
- Any significant differences in values between different days of the week or hours or the day
Some Initial Data
Step 2 – Analysis
What do the figures tell us? Which can be the easiest improved? A quick glance to experienced eyes shows that both average shopping time and staff contact with customers are very low and should be easy to improve.
Step 3 – Improvements and Implementation
Average shopping time can be improved by better signs and, most importantly, good service. Focusing on the data – getting the staff to interact more with customers will bring about a longer average shopping time and increases in the key parameters of conversion rate, average transaction value and number of items per basket will follow.
Of course, the staff will have to buy into the process but incentives for raising the values over which they have direct control – like average shopping time and number of interactions between staff and shoppers – have good results. Focusing on the small details brings great improvements in the big picture.
Step 4 – Monitoring
Have the changes worked? What do the figures say now?
Data after Three Months
Step 5 – Repeat from Step 2
By now the improvements in sales will be clear and it’s not long until the people counting system has more than paid for itself. But there will be other opportunities to grow sales. The system provides continual improvements over time.
An increase in conversion rate of 2% may not sound like a lot, but it actually resulted in a 30% increase in sales. Let me explain.
An average of 404 people visited the store each day.
An 8.1% conversion rate of 404 gives 33 people buying something.
After the improvements, conversion rate rose to 10.1%.
10.1% of 404 gives 41 people buying something – 8 more people per day.
Assuming that the amount spent per person remained the same, that gives a 24% increase in sales (8/33).
But people on average spent €2 more. So the takings jumped from
33 people spending €42 per day – €1386 to
41 people spending €44 per day – €1804
This means that the improvements resulted in an extra €418 a day being spent in the store: which is a massive 30% increase in sales.
More and more museums are installing people counting systems to track their visitors and learn…
- Current occupancy levels: which rooms are busiest at the moment?
- Which exhibits captured people’s attention, and which were neglected?
- Where visitors lost interest and left?
- How many people visited in total, how many of these went to every floor and how many went every room?
- How long people looked at each exhibit?
- Peak visitor times?
- Queuing times?
The real-time counts for each area means that the museum can allocate extra security guards or other staff to that exhibit. Items are more often damaged or stolen in busy rooms with few personnel on duty.
Many museums are funded by governments, and receive their funding according to how many visitors they get. Video people counting gives a true number of visitors, rather than basing the footfall figure on the number of tickets allocated (for example when a bus-load of children get in under one group ticket).
The information collected also enables museums to adapt floor layouts to increase visitor satisfaction and encourage repeat visits.
The data is not just useful for enhancing the visitor experience, they system can be used to increase sales in the museum shop.
A small increase in sales conversion leads to a significant increase in sales, even when no other factors are changed.
- Suppose your store had 200 visitors a day. Of these 200 only 20 actually buy something. Your sales conversion is 20/200: 10%.
- Suppose also that the average spend of these 20 shoppers was £30. Total take for a day would then be £600.
If you could increase your conversion by just 1 percentage point, to 11%, how would the figures look then?
- 22 people would buy each day (11% x 200 = 22)
- They would spend 22 x £30 = £660
- Increase in sales is £60/£600 = 10%
In our example, with all other things remaining equal, an increase in sales conversion of 1 percentage point gives a 10% increase in sales.
Sales conversion is one of the most useful metrics available. It is easily measured simply by connecting the people counts to the point-of-sale system.
Some stores even track their conversion rates in real-time, so dips can be immediately flagged up and dealt with.
Three Ways to Increase Conversion Rate
- Increase Average Shopping Time
- Increase staff interaction with shoppers
- Improve signage in the store
The effectiveness of all of these can be measured. Small improvements lead to big financial gains.
Is a 1% increase in sales conversion realistic? It’s actually a very low figure. We recently helped a European retail chain improve sales conversion by 25% in just three months.
Without pedestrian footfall counts, councils and town centre managers are in the dark as to precisely how a town centre is being used. Measuring footfall lets them accurately assess the impact of development initiatives on people’s movements and provides key data to inform future decisions aimed at improving the centre.
The pedestrian counts also help determine the potential for new retail stores, providing evidence for prospective businesses moving into the area. Similarly, the footfall data helps determine the level of rents which can be charged.
Comparison of changes in footfall levels and pedestrian movements over time shows whether a town centre is improving or losing trade. The rich data identifies any areas that might be declining and shows where investment may need to be targeted: an early-warning to stop the situation getting worse.
Traditionally footfall has been measured by people manually counting pedestrians. Now though, automatic pedestrian counters can be counting all day, every day – giving accurate data at a much cheaper cost.
The sort of data you can expect includes year-on-year trends, changes relative to the previous month, the busiest day of the month, the busiest time of the day and comparison of footfall in different areas.
Footfall measures a town centre’s ability to satisfy customer and visitor needs and expectations.
So much for why to measure pedestrian footfall. How do you do it?
The Pedestrian Footfall Counting Technology
CCTV cameras are mounted above the street to track peoples’ movements. Smart people counters connected to the cameras record how many pedestrians pass through camera’s vision. Authorised people can view the footfall information they need over the internet, in real-time if necessary. Local video analytics minimises bandwidth use.
The system architecture means counts for different areas and towns can be seen together as they happen. When viewed over time you get a clear picture of the performance of the town centre.
There are no limits to the size of the system, simply connect as many cameras and counters as you require.
Wide areas are covered by using two or more cameras. The smart footfall counting units know when a person moves from the vision of one camera to another, so people aren’t counted twice.
Data can be saved in a choice of formats, including MySql which is easily integrated into existing database systems. So the town centre counts could be viewed alongside, for example, counts of vehicles entering car parks.
Tried and tested in the harshest of weather, the pedestrian footfall counters are over 98% accurate even in the busiest situations.
During installation you can easily verify the counts simply by watching the video back and seeing the footfall counts increase as pedestrians walk by. The counts are bi-directional – separate totals of people going both up and down the street in your chosen timeframe. This can might be every quarter-of-an-hour or ever hour, for example.
After installation, there are no ongoing monthly or quarterly charges. We are always happy to help though, should you need any technical support.
For more information telephone Retail Sensing on +44 (0)161 839 6437 or e-mail: email@example.com.
The pressures on retailers to cut costs are huge. One way of doing this is to reduce staff numbers. But is this cost-effective?
Retail profits depend on attracting people into the store and converting them into customers. When people visit the shop, there are many factors to converting the traffic into sales, not least the right products at the right prices. But retailers also need enough staff to ensure a good shopping experience, whether it’s by helping people find what they are looking for, providing advice on products, suggesting alternatives or giving a quick check-out.
To ensure that the staff are effectively allocated, managers need to know when are their peak shopping times and busiest footfall. A retail traffic counter shows an hourly break-down of the counts for the whole day.
Store labour is generally the second largest expense for retailers. Understanding store traffic patterns means retailers can identify key selling periods. This lets them allocate appropriate numbers of staff at busy periods, and choose to have their best staff members on the floor at these times. It also means that staff are not employed in secondary activities, such as tidying or restocking, at busy times.
A people counting system will empower retailers to decide whether cutting staff levels will make them more, or less, profitable.