Instagram Fashion Sellers: Using Real-Time Data to Strengthen Profit Return
It is no secret that Instagram now boasts more than 800 million users, and is taking the retail and fashion world by storm. According to a report by L2, a company that analyses brands’ digital presence, 93% of fashion brands from Marc Jacobs to Topshop are now on Instagram, although they’ve been using it as a marketing and branding platform showcasing their goods instead of actually selling them directly.
An Instagram Fashion Seller’s strategically placed ad that leads potential customers to their main website via the “Shop Now” click.
Besides these brands, there is an entire market segment of independent fashion sellers that solely rely on Instagram to sell and market their wares.
From Instagram Fashion Sellers To Fashion-preneurs
One quick search of a hashtag on the popular photo-sharing app and you’ll find millions of posts by fashion sellers promoting everything from vintage shoes to bohemian dresses. The fashion-preneurs have been garnering business and marketing benefits on Instagram. They brilliantly use the platform as a way of showcasing their self-designed or self-manufactured clothes. With millions of followers rummaging through their feed daily, these sellers would be able to easily capture their potential customers with Insta-worthy pictures.
Potential customers would browse through, find something enticing, and initiate their desires to buy a product item via a comment or direct message. Sellers will then proceed to finalise purchases using a payment gateway service like Paypal or online banking. This phenomenon is common these days with the Instagram platform evolving into being more than just a photo-sharing app.
Due to low barriers of entry, Instagram is often the jump start point for many fashion brands.
“It’s really an incredibly powerful tool for people who don’t have investors or are small, taking baby steps just like me,” Paris 99 designer, Paris Starn, says of the platform.
Nowadays, fashion brands have moved on to invest in e-commerce businesses, displaying an entire warehouse of fashion in order of – categories, discounts, bestsellers, saved products – which could enhance their customers’ online shopping experiences. However, the influence of Instagram is retained to complement and attract millions of customers into e-commerce stores.
While being a low cost strategy with the lowest risk, it is also highly competitive. Hence, it is crucial for them to study and understand their market and target consumers.
How Do Instagram Fashion Sellers Study Their Market?
The success for these independent sellers relies on the depth and width of their product assortments. To procure weekly or monthly stock, they need to know the gap in the fashion industry that needs to be filled in order to introduce the right products for customers.
Browsing through one’s competitors’ feed and noticing which of their products are tagged will help in understanding the buying behavior of their customers. Influencers are also a way of tapping into ideas of what styles are current and trendy at a particular season. Internally, looking at past sales data could also be a way of projecting what customers would be looking for and the demands they will have for a product.
However, observing the market is no easy feat as the customer base for each fashion retailer is different. In addition, the social media space is a fickle-minded thing and may only provide a guesstimate and not an actual representation of what sells and what doesn’t at a certain time.
So how should Instagram fashion sellers maintain their relevance in the over-saturated digital arena?
By monitoring the activities that are made on those stores including the purchase behavior of their customers. With this first-hand knowledge, sellers on Instagram can then understand their own market position and plan ahead for their next batch of collections.
Checking out what the customers of MDS collections are buying and wearing through their tagged photos
Maximising ROI Using Real-Time Data
Those who rely solely on Instagram to promote their business may be at a slight disadvantage but nevertheless, they can still capitalise on their competitors with e-commerce stores. How?
Utilising the power of data. This will in turn help maximise their profit returns by determining:
- What products to stock up on
- How to price products
- Who their competitors are
To better illustrate, you are brand X and you want to see the market of Malaysia, specifically on dresses. You choose Zalora, Asia’s largest e-retailer in the region, as they are a dominant player in the industry. You also pick MDS, a smaller, but concentrated and refined fashion store that offers online and offline services.
What Products To Stock Up On?
Omnilytics is able to facilitate buying decisions by providing data such as:
- New-in products in the market
- Best-selling products in the market
- Least-selling products in the market
- Trend predictions from popular styles in the market
- Most stocked and best-selling colours in the market
- Best-selling sizes for any product
Newly stocked dresses from Zalora and MDS
Image Sources: Button Down Cami Maxi Dress (Something Borrowed, Zalora), Asymmetrical Ruffle Dress (Mango, Zalora), Lou 2/4 Calf Dress (Vero Moda, Zalora)
Image Sources: Cutout Ruffled Dress in Off White, Drawstring Ruffle Romper in Stripes, Erica Lace-Trimmed Dress in Black
The dresses above are just a few examples of the new arrivals for both retailers. Looking at new arrivals, in real-time, gives you the ability to gauge upcoming trends. Trends come and go fast, and a common mistake made amongst retailers is not knowing when to adopt trends into the cycle.
Sold out Dresses from Zalora and MDS
Image Sources: Paris Cape Sleeve Dress (Forever New, Zalora), Oyster Maxi Dress (Little Mistress, Zalora), Asymmetric Midi Dress (Lavish Alice, Zalora)
Image Sources: Contrast Overlay Dress in Grey, Nigella Ruffled Dress in Navy, Ruffled Mermaid Dress in Black
Be one step ahead in the industry by knowing first-hand on what’s available in the market. Knowing what sells well could help decide which styles have a higher sell-out guarantee. For example, the pink floral dress from Forever New (Zalora) was out-of-stock a total of three times, replenished four. The printed dress in navy from MDS, on the other hand, also faced three stock-outs, indicating a popular dress style among customers during the period.
How to Price Products?
Knowing the overall pricing architecture and strategy of market competitors would help in deciding on an appropriate product price, such as:
- Deciding on what is a good standard price markup for products based on the industry average.
- Understanding a product’s market rate and speculating if a higher price range could work.
- Strategising discounts based on how other competitors are pricing their products.
- Understanding the price points at which customers are willing to pay for a particular product.
Knowing the average pricing range for clothing categories in the market at any given timeline will assist in pricing decisions, and this could potentially increase profit margins. On average, the dresses sold in Zalora were priced between MYR 50-200, while the dresses from MDS were between MYR 50-150. It is also important to note that the analysis shown above included full and discounted prices.
Although both retailers carry more lower to mid-priced products, Zalora’s price points are slightly higher than MDS in this regard.
As Malaysians enjoy hunting for good shopping deals, discounts could be strategically placed after studying how other competitors discount their items, especially during the festive and sales season. Here, Zalora commonly discounted their products at the 50-54% range, while MDS had a higher range at 70-74%.
Omnilytics is able to provide data on the performance of market competitors, including:
- Number of product SKUs that are being stocked
- Sell-out rates
- Pricing strategy for all products
- Percentage of replenished products
- Percentage of discounted products
- Most common discount range
- Most popular clothing colours
Despite MDS not having a large number of SKU in-stock like Zalora, both MDS and Zalora had an almost similar sellout rate of a 51-58% range. The replenishment and discount rates can also be identified. Fashion sellers could select their industry competitors from Omnilytics and obtain the sellout average to understand their position in the market.
Drilling down further, knowing which colours went out-of-stock first can help decide what to stock up more of. For instance, the best-selling dresses in Zalora and MDS were black dresses followed by blue and white, with MDS customers preferring the latter colour.
The large pool of users who shop on Instagram could potentially attract more independent fashion sellers to introduce their business on the platform.
With increased saturation, knowing what’s new and what’s popular in the market will give these sellers a head-start and fair advantage when planning their stock, especially during festive seasons like Chinese New Year and Hari Raya. Moreover, understanding the pricing strategies of other market competitors could provide a benchmark on how to price their own products without sacrificing on profit margins.
Nonetheless, real-time data from Omnilytics is the future of retail intelligence, allowing fashion businesses – large or small – to make accurate business and marketing decisions and sustain their growth in the long run.
Eager to know how to expand your brand on Instagram and/or your e-commerce store? Drop us an email at firstname.lastname@example.org and we’ll be in touch!
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