Drive improvement across your entire retail network
Via our easy to install retail traffic sensors, our clients are able to count not just the volume of people entering the store, but accurately measure shopfront and fitting room conversion rates too.
Our innovative sensor paired with the Kepler Retail Analytics dashboard, allows you to monitor and optimise individual store performance in real time.
Australian designed and manufactured traffic sensor
The Kepler Analytics Retail People Counter is an Australian designed and manufactured traffic sensor that is invisible to retail foot traffic, offers no disruption to store operations, and can be installed and calibrated in less than 3 hours on average*.
The Sensor provides business intelligence grade data on a range of customer behaviour measures and sales drivers.
How much difference can a data driven, store operations and sales optimisation system make?
Within the Kepler Analytics system, you can monitor individual stores, regions, or custom store groups directly from our mobile app as well as the desktop dashboard. A real time sales data integration allows you to forecast which stores are unlikely to achieve daily targets and address areas that need operational improvements before the retail day ends.
We believe that knowledge is power
Which is why we’ve developed a Kepler Toolkit to help provide deeper insights and drive improvement across your entire retail network.
Store Operations
Supercharge team productivity on an individual level with real-time sales conversion behaviour reinforcement.
Shape rosters to capture forecasted customer demand powered by a global postcode / centre level event calendar.
Optimise service levels to minimise bounce rates and maximise dwell times and sales conversion.
Boost customer satisfaction with automatic feedback, team coaching and directly linking to tangible dollar outcomes.
Merchandise
Optimise merchandising strategy to capture under-served customer profiles who aren’t converting into sales.
Drill down into preferences by customer profiles, and predict response to price, promotions, category and cross-merchandising changes.
Use demand forecasting based on store level customer profile breakdown to optimise stock levels.
Reallocate clearance stock to the stores with matching customer profiles to maximise sell-through rate.
Marketing
Bring more customers into stores by converting more email / Google / Facebook / Website online views into store visitation.
Hold advertising channels accountable and increase effectiveness of the promotional calendar by calculating traffic contribution of above-the-line campaigns.
Property
Challenge occupancy cost using actual passers-by traffic volume and multi-year trend by location / landlord.
Compare traffic volume performance of different landlords or property groups.
New location assessment using actual site traffic and customer profiles.