Understanding Customer Behavior Through Data
Oh, I think a lot of people tend to believe customer behaviour is written in stone. And the tools for interpreting or decoding those behaviours are locked in ancient scrolls somewhere. But if youāve ever been in retail, you know customers can be quite unpredictable at times - unless youāre prepared and have paid close attention to their wants and needs.
For example, a shoe store will never generate as much business as a supermarket simply because shoes arenāt something you regularly need or buy. But what do supermarket customers want. Often that they have their groceries on hand quickly without having to wait a long time, right. If youāve ever shopped in one, youāll notice that they have two different types of check-out counters: Express and Regular.
Customers tend to enjoy speedy checkout with shorter queues for fewer items to purchase, while those with shopping carts full of groceries are presumably happy enough queuing up at the regular counters because well - they know itās going to take longer and possibly want some extra time for their bags to be packed so groceries donāt get squished. That said, understanding customer behaviour is not as simple as making assumptions based on fleeting observations or anecdotal experiences (although thatās definitely where it starts). Customer behaviour depends on demographics like age groups, economic standing, and even cultural backgrounds.
It depends on seasons - is it Christmas yet. Or back-to-school season. Or maybe summer and vacationing families need swim gear.
To truly understand customer behaviour you need data from several different sources. Itās not always easy to interpret this data - after all, customers are human and driven by emotions while data is mostly number-based and rational. But even when relying on anecdotal information from staff and managers there has to be a structure implemented - categories of customer personas must be defined by either surveys or a record of their details by online stores including age group, purchase behaviour etc.
It helps gain deeper insights into customer needs based on what matters most to them so you can anticipate the next season or trend much better than before.
Key Metrics to Consider for Store Layout
When people talk about store layouts, they usually fall into the trap of thinking itās just about how stuff is arranged. Like, move the tables this way or the shirts that way. End of story.
Itās never so straightforward, though - itās much more nuanced. I think it comes down to a kind of psychological ballet involving time, money and experience. Footfall and dwell time are the obvious ābigā numbers for most folk - but not everyone considers conversion rates in relation to journey paths. Or how traffic interacts with displays or mannequins and what keeps people lingering in certain corners.
I mean, you sort of have to rely on a blend of heat maps, sales per square metre, basket sizes and POS data to get an accurate picture - and then thereās still the question about what your specific customer is drawn to. For example, how far into the store do they travel. Is it three-quarters or do they hover awkwardly by the entrance.
Are they doing a quick one-two combo through different aisles or are more or less they charting a meandering path through every display - and why. I suppose itās up to us to know what would encourage people to explore further without getting lost or overwhelmed.
But even with all this data giving you numbers that look neat on a graph, things can get rather murky when actual humans are slightly involved. Weāre emotional creatures after all - not pixels. Meaning youāll never have every variable covered even if you tried.
Your metrics will only give you part of the picture - leaving room for some guesswork and intuition-driven choices. It seems like and that last bit is occasionally probably what makes a store memorable anyway.
The Importance of Traffic Flow in Retail Design
The way I see it, everyone seems to think store layout is a sort of science. Thereās this assumption that there are a handful of magical rules, and once you know them, customers will just waltz in and fall right into the trap youāve set with your displays and promotional tables. Doesnāt work like that - sadly. The reality is, customers come in all shapes and sizes, each with their own agenda.
Forcing people into certain patterns with cleverly placed racks or cash counters doesnāt always pan out the way youād hope. It might seem like youāre giving shoppers more opportunities to discover new products, but the truth is, it often just feels forced. And when people sense that force, they tend to resist it rather than comply.
Navigating the nitty gritty of human behaviour takes some observation and trial and error. You want to get an actual sense of the types of customers that walk into your store and what motivates them to buy (or not). And then create a space that acknowledges their existence so they feel seen.
Like they're not just another number on your bottomline. Maybe that means ceding control to them and letting them dictate the experience within parameters set by you. Giving them just enough structure so they donāt get overwhelmed by choice, but can slightly also let their curiosity take them where they want to go next. And sometimes thereās no clear answer as to how much structure is too much or too little - so taking note of customer behaviour over time can help make changes for the better.
Sort of.
Utilizing Heat Maps for Optimal Product Placement
I think most people - even the most experienced - get sucked into thinking that optimal product placement is about pretty displays. Thereās a sense that you need to pull out all the stops and turn on the glitz. When in fact, itās not so much about design as it is about psychology.
Heatmaps quite literally map out shopper behaviour. And itās not just about where they flock, but also about where they linger and how they interact with products. The way I see it, the thing that most stores overlook is the data that heat maps throw up.
It offers patterns, potential and predictions. And sometimes, those arenāt all nice things to see. You might find customers clumping near products you donāt necessarily want to sell or a red hot spot around a display you thought didnāt matter. Iāll say though - while heatmaps take away some of the guesswork out of product placement, thereās an added layer of complexity that comes from knowing what to do next.
When customers flock to a certain area, thereās this urge to simply move your high-value products there and cash in on those sales. But interestingly enough - it doesnāt work quite like that. What does work though is reportedly complementing product placement choices with strategies backed by data.
More or less. For example, if you have two popular items placed too close together, then spreading them apart can direct traffic across more of your store and boost the attention your less popular items receive as well.
Case Studies: Successful Data-Driven Store Layouts
You know what I see quite often. Retailers go in for the kill with their stores, thinking all they need is somewhat more of their product on display.
They use store layouts like theyāre on The Block - throwing everything at the wall and seeing what sticks. And before you know it, the store ends up looking like a hoarderās wet dream; busy, complicated, and impossible to navigate through. If there are ten displays per aisle and nobody knows where to look, then shoppers are better off heading to the rival chain across the street. What works, though, is nearly always something completely different.
Store layouts have to be intuitive and simple enough to guide your customers along a path that you want them to take, without being patronising or too obvious about it. Data can help massively here. If you find your customers wanting a more focused shopping experience because your store is fairly too overwhelming, then chances are that merchandise density isnāt always a good thing - quite like Targetās more minimalistic approach.
Hereās one thing most people donāt realise though - there isnāt just one way to do things. Some stores need higher merchandise density and some donāt.
More or less. This again comes down to data and how your brand wants its perception to be shaped. Itās a fairly involved process but with data on hand from POS machines and heatmapping devices or even analytics from your website can offer valuable insights into what sort of layout will serve your store best. There are examples everywhere - whether it is stores adopting a āracetrackā layout or single-aisle stores optimising for efficiency over all else; everything comes down to knowing your customer base and having enough actionable insight into their shopping behaviour.
These decisions go far beyond knowing how much stock you have in inventory but also extends into what goes out on sale or gets displayed at the front of an aisle.
Future Trends in Retail Layout Design
A store is rarely more than a place to sell things, although many people still get caught up in the trappings. The idea of creating a retail layout can be daunting and itās easy to get caught up in current trends and standards for different industries. But the reality is much more about how you use the space, rather than what you put there. And it all comes down to how people experience your store - what they do there, how they behave, and what makes them feel good about staying.
The future for retail layouts is more about finding new ways to create human experiences and leverage technology in a way thatās sustainable and compelling. Retailers will invest heavily in digital displays, interactive technologies that support customer education, and indoor navigation tools to direct foot traffic towards higher value areas. Virtual environments that combine physical products with virtual features, such as 3D store mapping, virtual signages, touch-less payment systems and even AR dressing rooms are shaping the future of digital-physical spaces. However, most modern day customers value sustainability as much as they do visual design or brand loyalty.
So weāre seeing an added focus on sustainability, guided by consumer preferences for green spaces with lower energy consumption and responsible materials. In this future world of hybrid retail layouts and value-driven consumers, itās less about cutting-edge tech or visual wow-factors than creating an immersive experience led by technology that feels good for everyone involved. So much has been said about retail layouts being focused on building customer relationships rather than pushing sales.
Somewhat paradoxically though, the retail industry has leaned further into data-driven design that can work against the ideas of making stores āfor peopleā. While omnichannel shopping experiences are becoming somewhat standardised in most retail segments - thereās also an increased complexity around how people interact with brands today - whether itās online or offline. Sort of. People expect retailers to know who they are if theyāve had any previous interactions with them online - so stores are increasingly integrating digital experiences into their physical stores such as self-service kiosks, virtual fitting rooms etc to ensure a seamless transition between online and offline shopping experiences for customers.