Some products naturally perform better on Meta. I talked about characteristics that make a product “pop” on Meta here.
Today, I’m going to talk about another important lever for increasing your brand’s total addressable market on Meta: designing into trends.
I know some of you just recoiled in horror. “I set trends, I don’t follow trends!”
Setting trends is for phase two of your brand’s growth. In phase one, you need to find white space in the market. A trend that everyone is offering isn’t necessarily whitespace, but providing a POV on that trend for your target audience is an extremely high leverage activity.
When I interned with the strategy team at Gap (I was an MBA intern, ok!), we used market intelligence data that summarized consumer credit card use. Those platforms provided insights that covered physical retail and eCom…and they cost six figures a year to use.
You don’t need to survey the entire US consumer market to design into trends for Meta. You only need to survey the eCommerce market. And there is a much more reasonably priced tool for doing that: Particl.
Particl gave me a month of free access to their platform and asked me to write about it if I found the tool valuable. I was honestly really impressed, especially as a former user of “enterprise” market research tools.
I’m going to outline how to use Particl to perform market research and shape your assortment in ways that will boost your ROAS on Meta.
I was not paid for this content (other than the free month with no obligation), I just feel like this information is valuable enough to share.
If you want to try this out for yourself, you can get 20% off your first month of Particl when you use the code ALEX at checkout.
Basic Trend Research
One question I get frequently from readers is “where do you go to find out what’s trending?”
If you read a lot of industry publications, subscribe to shopping blogs/newsletters, and spend time on IG/TikTok you can get a pretty good idea of what is trending in women’s fashion. Other categories are less thoroughly monetized, and therefore less legible.
Of course, personal intuition is error-prone, and also prone to blind spots. There are two ways to do trend research on Particl:
#1 Product Explorer
In the Product Explorer tab you can search for a product and see the sales volume of that product across all of the retailers that Particl tracks. Here is an example readout for ballet flats, with a price filter of $150-500:
One thing you’ll notice is that this search view isn’t perfect. Dresses are getting pulled into the results. Another thing you’ll notice is that multibrand retailers can dominate the search results (more on this later).
You can use this like Google keyword planner–search 10-20 different trend hypotheses and see which ones have the highest sales volume at your price point.
You can also scan the top 10-20 retailers for each trend and see if they align with your brand’s audience. That will give you a good idea if the trend is relevant to you.
Additionally, you can add the top selling styles in each trend to a moodboard, identify the design details that set the top sellers apart, and try to incorporate that into your design process.
Do you have to do this? No. If your vision is so strong that designs are constantly falling from your fingertips unprompted, then you don’t need to do this.
But if you’re feeling stuck, this can help you get unstuck. And if you desperately need more hits, this can help you improve your hit rate.
#2 Competitor Search
Another good way to get a broader feel for trends is to analyze the top sellers from multibrand retailers that sell to your target customer.
Let’s say you’re a footwear brand with prices that range from $250-500. You don’t currently sell to wholesalers, but one of your competitors in the same price point does.
First, you can use Particl to analyze where your competitor is doing the most sales volume in wholesale. Let’s say that you discover their top eCom account is Revolve.
You can look up Revolve in company explorer, drill into their product sales data and filter it by dress shoes. This will give you a visible snapshot of the top selling dress shoes–color, material, styling and price point:
You might have to go to Revolve’s website and look up some products where the image is missing.
It looks like this Tony Blanco Caprice Heel is a top seller in multiple colorways. Pointed toe slingbacks and strappy mid-heel sandals that look like 90s prom shoes are having a moment in the top 10.
Particl data isn’t limited to women’s fashion, or even fashion/apparel/accessories. Almost any product category you can think of is represented.
Evolving A Best Seller
Let’s say you’re a designer for Jenni Kayne. You need to develop another best selling sweater. The pressure is ON.
Again, some of you reading this are going to hate me, but the fastest way to develop a best seller is to iterate slightly on things that are selling well for other brands. I used to work as a designer for a “commercial” brand–this is what we did day in and day out.
To do this, you would apply the competitor research framework I outlined in the last section in two specific ways:
First: research best sellers from brands that are in a higher price category. If you’re Jenni Kayne, research best sellers from brands like Khaite, The Row, etc. Why take this approach? Designer brands often lead the market, so they’re a good source of new ideas.
It looks like Jenni Kayne literally did this. See JK’s Cooper (priced at $525) vs Khaite’s Scarlet (priced at $1,980). You do not have to be this derivative btw.
(“Fun” fact: the Khaite cardigan cost only $1,500 when Katie Holmes made it go viral in 2019.)
Second: you can use the trend explorer to validate different ideas you might have for iterating on a best seller. You can use this to validate different colorways, materials or other details.
Let’s say you had these ideas for “evolving” the Cooper:
- Release it in oxblood red
- Release a short sleeve version
- Release a cropped version
- Release a version with embellished buttons
You would search each of these in trend explorer and see which idea(s) have the most growth momentum.
Something to be aware of: trends that are too small/niche won’t be monitored, so you might have to broaden your search. For example, there were no results for “cropped sweater”, but I did see a consistent downward trend for “cropped”:
Now…how you implement this is up to you. Jenni Kayne’s core customers are Goop-adjacent yummy mummies. The cropped trend might be totally irrelevant to them OR they might finally be ready to test it out in this stage of the trend cycle.
You can enhance this analysis with the product search framework I outlined in the last section–analyze the relative sales volume of each potential “evolution” option.
Adding A New Product Category
Expanding into a new product category–say, an apparel brand that wants to add footwear–is a high risk, high reward proposition.
Two factors drive the risk:
- It’s hard to be really good at more than one product category, especially if those categories require distinct expertise.
- People rarely shop head to toe looks from a single source. The consumer has a different willingness to pay across categories. That can make it hard to price your assortment in a way that will enable cross-selling.
You can use Particl to de-risk this process a little bit, at least when it comes to risk factor number two. To do this, you want to validate the sales volume of your pricing strategy for the new category.
Let’s say that you sell women’s apparel priced $250-700 and you want to launch a line of shoes priced $500-750. You would list out two sets of competitors:
- Brands that sell women’s apparel and shoes with your desired pricing strategy (to find these, you can use Particl product search + price filters).
- Brands that sell women’s apparel priced $250-700 and shoes at any price point.
You would then use Particl competitor search to look up the following info for each competitor:
- Relative sales volume of apparel vs shoes
- Top selling AUR bands within each category
- Is shoe volume being driven by a diversity of styles, or one best seller?
If multiple business that match your pricing strategy have strong sales volume in shoes, and an apparel/shoes split that you find desirable, it is validation of your pricing strategy.
If the only brands with strong sales volume in shoes use a different pricing strategy, you might want to consider adopting the same.
If none of your comp brands do much volume in shoes, you might want to avoid it. Sometimes brands stock things online just to “make a statement”, or they make a misstep and correct it in future seasons.
Just to be clear: I’m not telling anyone that they MUST run the processes I outlined here. I’m simply offering it up because I think it will help a lot of my readers.
If this type of analysis would help your brand, you can get 20% off your first month of Particl when you use the code ALEX at checkout.
In next week’s member’s-only issue I’m going to share a kind of counterpoint to this analysis–how to manage a design-driven brand in a way that balances cash flow and creativity.
Click here to become a member.