Use your customers' geolocational preferences to grow your brand
Your customer is oh so specific about what she prefers within your product range so instead of being frustrated at how particular she is, let's understand and cater to her geo-locational preferences better by using data. This means increased conversion and brand growth, so why wouldn't you?!
I just love the amount of data we have available to us in fashion today and how in-depth our analysis can be as a result. Data-driven buying and planning has a huge impact on brand growth and profitability. This data is a resource that just waiting to be utilized.
Last time I shared an insight on how aspirational products can attract customers into your stores and online, but its the more accessible price points that generate the revenue for the business. Today I'll share how important it is to continually analyse and understand your customer's product preferences. This will enable you to fully captialise on the traffic and grow your brand from strength to strength.
Your customer has more preferences that you think!
What can be surprising is the diversity of customer preferences in your product range. We all know that different states, cities or even suburbs have preferences based on climate and price points. The importance of understanding your customers' geo-locational preferences can't be understated but it goes way beyond that, they have very different and very specific fashionability preferences too!
Her preferences vary depending on where she's located which is why we need data to better understand her. For example, Lorna Jane in Australia deployed the methodology of testing a product in small volumes to some of their flagship stores. If it was a hit, they would then send it out to all stores in large volumes. This is a fantastic way to understand how much to invest before you go ahead and order all those units.
But, when Lorna Jane expanded to the United States they thought testing in California meant you could send to other states if it was a winner, but quickly they found out that was not the case.
Lorna Jane now ranges very specifically to cater to the customer in each state and utilises data-driven testing to cater to those needs. It's this model that Zara has had such success over the years.
This is of course a significant amount of work, but absolutely worth all the effort. So if you're looking at your geographical preferences, definitely test before you invest!
So what customer preferences should you be testing for?
The hemisphere and seasonality aspect of product ranging goes without saying. Northern vs Southern hemisphere are always ranged for as almost complete opposites of one another throughout the year. Further to that, even within a hemisphere, there are microclimates to cater for, for example, sending more shorts and tees to Queensland and California vs Victoria and New York State.
So of course always follow the yearly trends and changes in seasonality by location.
Expanding on this you will need to data to cater to further important product preferences
1. Price Point preferences (as per my previous blog)
2. Colour preferences - as a simple example of this most Aussie fashion brands know to send Melbourne a higher contribution of black apparel because this colour performs so well there.
3. Fabric preferences - linen, wool, cotton, silk yes she wants specific fabrics in certain locations and this should tie in well with your price points as ideally, the one data point will validate the other.
4. Silhouette preferences - maxi dresses vs mini dresses, bodycon vs loose-fitting, cap sleeve vs sleeveless, plunge vs high necklines etc. This speaks directly to her fashion preferences and personal taste and these are data points we should know about our customer so we can decide how many maxi dresses to range and how many high neckline styles we need in our assortment for example.
5. Print Type - does she prefer plain, floral, geometric, tribal or even stiped designs?Tracking and analysing the performance these groups of print types can open a world of insights about your customer and her demand for your product range.
The above analysis requires a comparison of your supply (you product range and the units purchased) vs your customer's demand for it (sales performance).
To analyze your customers' demand always ensure that you are measuring this prior to any size fragmentation or discounting and while it has its full capacity to perform, meaning it has 1st position in-store or appears in new arrivals section etc.
Use the above data points to capitalise on your customers' fashion aesthetic preferences. This is key to growing your sales and your customer base. If you utilise your data to understand your customer better, you will be able to cater to her preferences more effectively. This data-driven approach will enable you to harness all the available growth lever's for your brand.