1st Joy of a Retail Spring – Understanding Customer Behaviour
Make it your new year’s resolution to understand how your customer behaves inside your stores. In many ways having got them into your store you’ve done the hard part, and everything they do, and everything they buy now, is a bonus that cannot be ignored.
The key is understanding how your customer reacts to your store, your product display, your layout, your service and everything else that can convert a sale.
Understand what is working and what is not. Adapt and evolve to ensure the customer is behaving in every way that they should be on their way to purchase.
Measuring store traffic is just the beginning and merely the tip of the analytics iceberg.
In the modern world of retail understanding POS data only tells part of the story of how the customer is reacting with your store environment
Using technology to monitor and analyse physical customer behaviour fills in those knowledge gaps on traffic patterns, dwells, stops and sales conversion
POS tells us what is happening whilst behavioural analytics tells us “what could be happening!”
- how do my customers behave in my stores?
- what is their activity, were do my customers go to and when?
- where do my customers dwell and stop but not convert?
- where should I put my impulse products and best promotions?
- what causes attraction and engagement in my store delivery?
This is how we help…
Customer Behaviour Video Analytics
“How can I measure and understand customer behaviour KPIs such as traffic activity by areas, dwell, attraction and stop times, touch engagement and conversion?
Monitoring and analysis of customer movements and behaviour using video cameras located strategically throughout stores, which are linked to VMAnalytics software that can measure traffic, dwell, stop, and touch data, and combine it with traditional POS sales data.
- store-wide camera coverage measures customer traffic and dwell patterns
- customer journey funnels of traffic, dwell, stop and conversion set up and analysed for specific department/categories
- comparison of traffic & behaviour patterns across different store clusters
- setting up of clusters based on activity & behaviour and not geography
- monitoring of pattern variations over time – hours of day, days or week, week-days and weekends and trends over month
- implementation of “before & after” tests to measure the impact of change
- Understand visually and statistically the customer journeys through store layouts
- To plan store layouts, promotional activity, key categories in-line with traffic activity
- Identify and measure the conversion funnel from store entry to checkout by department, category and aisles
- Identify and prioritise the opportunities to improve the different stages of the conversion funnel for the store and the variety of departmental journeys
- To plan staff schedules and tasks in line with customer behaviour
- Interviews with HQ and store personnel to understand the store issues
- Visits to pilot stores and planning of video camera locations
- Study of the traditional sales KPI patterns and trends for pilot stores
- A programme of initial analysis to understand the general behaviour and to identify priority areas of KPI opportunity to analyse further
- Detailed priority analysis
- Planning implementation and monitoring of “before&after tests” to learn from actions
Aggressive actions (from a potentially long list):
- develop and implement changes in test stores – “before&after” actions
- changes based on priority opportunities to effect store KPIs
- work with “retail stakeholders” on a progressive plan of “before&after” actions
- measure, monitor, develop and implement “quick-wins” across the chain
For more information on how customer behaviour video analytics can help.
Please get in touch. We’ll be happy to help & advise…
+44 (0)7967 609849 email@example.com