It’s no secret that brick and mortar retail outlets have faced a seemingly endless array of challenges over the past few years. The rise of e-commerce, compounded by the restrictions of the pandemic and the permanent changes to consumer habits this entailed, has left even the largest chains on the back foot – and so inaction in the face of these frustrations is not acceptable.
Thankfully there are solutions available, so long as those responsible for adapting retail spaces for long-term viability are making decisions based on data, not on instinct. With suitable analytics, architects and designers are now armed with insights that can predict foot traffic, optimize product placement, and even drive structural changes in store configuration. Here’s a look at how this is being applied, and what benefits it brings.
Implementing E-commerce Data for Physical Store Enhancements
As the line between online and offline shopping experiences continues to blur, with e-commerce sales hitting over $1.1 trillion in 2023, architects and designers can harness powerful web-derived analytics to refine and reinvent physical spaces. Particularly potent are insights derived from platforms like WooCommerce, which offer comprehensive data applicable to physical locations. Here’s how this leap can be made:
Foot Traffic Prediction
Using historical sales data and browsing patterns from an online store, architects can forecast busy periods and adjust store layouts accordingly. For instance, wider aisles might be beneficial during peak times to enhance customer flow.
This is significant because last year the 10 busiest days for retail accounted for 40% of all seasonal sales, which means there’s a real need to prepare properly so that the sudden influx of shoppers is not overwhelming. Both in-store and online experiences can suffer if systems and staff are swamped, so analytics is the lifeline in this context.
Product Placement Optimization
Heatmaps of click-through rates on e-commerce sites provide a visual representation of customer interest. Translating these heatmaps into physical spaces means placing high-interest items where they are most likely to attract attention – near the entrance or at eye level on shelves. In turn this can help with stock optimization, as you’ll know what’s hot, what’s not, and what to order.
Dynamic Layouts
By using a plugin to generate WooCommerce analytics reports, design teams can access real-time data that suggests when to rotate displays or reconfigure areas within a store based on seasonal trends or promotional activities.
It’s a case of knowing what your customers want, knowing when they want it, and knowing how to sell it to them efficiently – and while there are established ways of doing this in the physical retail sector, given that online sales are still climbing, and a new generation of digital-first consumers is emerging, it would be churlish to overlook the overlap of e-commerce analytics and in-store layout decisions.
Architectural Innovation Through In-Store Analytics
It’s not just online info which can influence in-store choices, as there is ample analytics tech that can go beyond mere sales tracking. It’s now possible to automate the collection of all sorts of data points at real-world retail locations, empowering architects to create environments that attract and also retain shoppers. Here are a few of the main ways this is done:
Entryway Analysis
The first 10 feet inside a store – often called the “decompression zone” – is where customers make crucial shopping decisions. Analytics can show how customers interact in this space, allowing architects to design more inviting entryways that enhance initial impressions.
There have been several studies into the science of the decompression zone and its impact on customer choices, with researchers concluding that it’s not enough to simply dump products in front of new arrivals and expect them to sell – you have to be more proactive and strategic in recommending them. It’s a case of not just following the herd, but using specific analysis to see whether or not tactics you try out are working.
Lighting and Atmosphere
Data on dwell times in specific sections can inform lighting designs. For example, brighter lights might be used in high-traffic areas to improve visibility and product appeal, which has been shown to increase time spent in-store significantly.
There’s also research into the impact of lighting color on store atmosphere, and thus dwell times. One study suggests that green lighting is the most appealing, while red lighting is most likely to move customers on quicker than intended – and overall soft-colored lighting is preferable to harsher tones.
Again, with analytics in play, you can make decisions on all of these points with hard evidence to back them up.
Interactive Elements
Incorporating technology like digital kiosks where analytics indicate high engagement areas helps maintain consumer interest. These interactive points can provide information, offer personalized discounts, or even serve as checkout stations.
This is a trend that’s very much gaining traction right now – with 84% of consumers exhibiting favorable opinions on kiosks in a recent survey from PYMNTS. So design changes to accommodate and highlight the availability of these should be prioritized if possible.
Final Thoughts
In short, it’s useful to start thinking of in-store experiences in much the same way as you would the online customer journey. If a site isn’t converting, using analytics to see why this is and rebuilding the underpinnings accordingly is wise. If a store is not attracting sufficient footfall, or not converting casual browsers into buyers, analytics can show where you’re going wrong, and point towards possible redesigns.
