Market validation is the process of determining if your product is of interest to a target market.
But why do you need market validation? Building a polished product, even if it seems simple, requires investing a significant amount of time and often money. Unless you have sales experience in your startup’s industry, you are definitely working with a lot of in-built assumptions about who your customers really are, what problems actually bother them, and what solutions will appeal to them.
No matter how brilliant your idea or product is, your business is doomed for failure if you don’t build the right product for the right market.
So before you jump to build your product, you must validate the key assumptions you are making. At the end of your market validation you will be in a much better position to choose the next step for your startup – whether it is to build the product exactly as planned, or to tweak the product or marketing strategy, or to look for a new idea.
If your validaiton is positive, one of the benefits of market validation is that you are likely to come up with qualified leads, trial users or early adopters for your final product. It will help you refine the target persona of your customer which will in-turn help with your positioning and branding.
For a startup with an idea that is yet to achieve product-market fit, market validation should be your top priority.
In this article I will detail the process I followed to validate a B2C e-commerce idea for an apparel startup using Facebook ads and without manufacturing any units. The idea was to sell sustainable clothing made out of recycled plastic to Indian consumers who are environmentally conscious.
I came across this idea at an entrepreneur meetup I attended in 2019. Environmental issues in India are of great concern to me, and when I learned of a way I could do something about it as an entrepreneur I grabbed the opportunity.
There were 2 main assumptions to be validated. The target market – there are a good number of environmentally conscious Indian consumers for whom plastic waste is a problem. And the value hypothesis – these consumers would value a recycled T-shirt made out of plastic as a good solution to the problem.
Step 1 – Research
Secondary market research is done by looking at existing data available on the target market. You can easily do this starting with Google by reading media articles, researching competitors, reading government data, etc.
As part of my secondary market research, I found a handful of small businesses that were into sustainability in India. There are e-commerce websites for eco-friendly products, waste management companies, eco-friendly packaging companies, and even some apparel brands making clothing from upcycled materials.
There is an emerging trend of Indian apparel brands targeting young working adults that are primarily sold through e-commerce. I wanted to target a similar audience and distribution, and so I chose an e-commerce business model.
Step 2 – Build
I learnt to use the design tool Canva, and hired a UX design consultant by reaching out directly on LinkedIn and a fashion design consultant through some networking at events. I also tried Fiverr for t-shirt designing and do not recommend it as the platform is not suited for a long-term project commitment. Within a couple of weeks I created the first concept for the product I had in mind and its positioning.
Step 3 – Measure
Primary Market Research is market research you conduct yourself by directly interacting with prospective customers. Some common methods of primary research are interviews and surveys.
At this point, I had a vaguely defined target market – young working Indians in metro cities who were environmentally conscious and were interested in discovering new Indian brands.
I expect most of this target market to exist on Facebook, so I decided to use Facebook ads to conduct my market research.
Campaign 1 – Estimating Customer Acquisition Cost
I started my campaign by cutting straight to the chase – I wanted to arrive at the customer acquisition cost (CAC) of a potential customer through Facebook ads for the current product.
I set a sale price point of Rs. 1500 based on secondary research conducted earlier and seeing some premium brands positioned at this price-point. I estimated the cost of product to be around Rs. 600 by talking to some manufacturers, including packaging and shipping. The goal of this campaign was to achieve a CAC within Rs. 200, so that the gross profit margin was around 50%.
When you run a Facebook ad, you can fine tune the targeting of the ad to great detail. Since apparel is very gender specific, I decided to run 2 separate ads for male and female audiences. Below is a snapshot of the audience filter applied to the male audience.
To ensure my audience was more likely to be working, I used the Education Level filter and filtered people who minimally had a college degree. I further filtered the audience for likely e-commerce shoppers of Indian brands by using the interest filter LBB, Delhi and behavior filter Engaged Shoppers. At the time of this campaign, I could not find a good proxy interest to filter this audience based on environmental awareness.
For the ad itself, I used this ad creative.
I created a variant of the ad for each t-shirt color I was validating, and for each gender. Each ad variant would lead to a separate landing page that was optimized for that variant, i.e. females who were shown the yellow t-shirt ad were taken to a landing page for the female yellow t-shirt. The ads objective was set to conversions, with a small budget of Rs. 1000 per gender for a duration of 3 days. A conversion was defined as every time a user clicks on Add to Cart in the landing page.
Campaign 1 – Results
Below are snapshots of 3 tables with the results of this campaign.
Link Clicks are a measure of clicks on our ad’s CTA (call-to-action button) that would lead to our landing page. Clicks (All) is a measure of all interactions on the ad – link clicks, comments, shares and likes. Reach refers to the number of unique people who saw the ad, whereas Impressions count the total number of times the ad was shown to people. When ads are shown multiple times to the same person, the Frequency increases. CTR (Link Click), or click through rate, is the percentage of all the times people were shown the ad and clicked on it to visit the landing page. Similarly CTR (All) is the percentage of all the times people were shown the ad and interacted with it. Finally CPC (Link Click), or cost per click, is the average cost for each click on the call to action button and CPC (All) is the average cost for any interaction with the ad.
The first thing that stood out from the results was that of 103 people who clicked the CTA button and visited the website, only 4 went on to click Add to Cart. This Add to Cart rate of 3.88% was much lower than expected, and ideally should have been at least 10%. Either the target audience was off, or the landing page did not demostrate sufficient value to the customer.
Only 2 product variants were added to cart – the female yellow t-shirt and the male green t-shirt. A possible reason could be that these colors are more unique in the market which justifies the premium value. The green male t-shirt had the lowest conversion cost at Rs. 93.77 / Add to Cart. Using a reference drop off rate of 20% from Add to Cart to Transaction, the result suggests at best we would be paying around Rs. 468.85 to acquire a paying customer.
The most alarming observation was that the most common color clicked on was black, yet no one converted. This suggests that a large percentage of this market did not see sufficient value in the product landing page to convert. Whether or not the issue was pricing, it seemed to suggest that this market was holding back from purchasing our recycled clothing.
Campaign 2 – Optimizing Target Market
Effective marketing depends on 3 factors – choosing the right target audience and placement, crafting a great ad copy, and finally having a product that brings real value to the customer.
One of the scopes for optimizing Campaign 1 was the target market. At the time of Campaign 1, I could not find a good way to filter an Indian audience that was interested in sustainability or environmental causes. Not all pages’ fans can be targeted through Facebook ads.
By spending some more time on Facebook Audience Insights, I noticed a correlation between the interest Plastic recycling and a Facebook page for Recycle India that was highly relevant. The size of this audience was not as big as the previous audience, but I was more interested in whether it would convert better. So here is what my updated audience looked like.
I was curious to first see how much the problem resonated with this audience. So I did not add an age or gender filter, and created this generic ad creative.
Since my objective was to get leads, I used Facebook’s lead ads. Facebook lets you collect leads and run a survey within the Facebook platform itself using an Instant Form, without having to take the user to your landing page. I used this feature to collect some data on preferred clothing brands. Once the form was submitted, the lead could optionally visit my landing page.
The objective of this campaign was to collect 100 leads who are interested in solving the problem, find out their clothing preferences, and determine the cost to acquire these leads.
Campaign 2 – Results
This campaign had significantly more interactions than the previous one, as can be seen from the CTR (All) of 4.21% vs. 1.53% for Campaign 1. Another observation from the result is that the target audience is skewed towards young adults in the age group of 18-34. However as audience age goes up, they are more likely to engage with the post as is shown by the increase in CTR. So perhaps the sweet spot for the target audience age group is somewhere in the middle, around 25-34 – not too young that they do not care enough about the problem, and not too old that the market size is too small.
The average cost to get a survey response was Rs. 8.42, which is an interesting data point for conducting surveys on Facebook.
Campaign 3 – Testing for Product-Market Fit
With a new target market and some data on the clothing they prefer, I decided to simplify the product and test the core value proposition. It turned out to be quite cost-effective to generate leads for people who have a problem with waste management. The question I needed to answer was – do people interested in solving the waste problem see a recycled t-shirt made of plastic as a solution?
For this final campaign I conducted an A/B split test on Facebook. The target audience was the same as Campaign 2, split by gender. The ads used were the highest performing male and female ads by CTR – which turned out to be the green t-shirt for males, and the black t-shirt for females. I chose CTR instead of conversions as I was looking for maximum engagement.
For my A/B test, I wanted to compare how much the target audience values recycled polyester clothing over organic cotton clothing. I chose this comparison as my research suggested organic cotton fabric was the closest competitor in the Indian market for sustainable clothing.
This is what my recycled polyester ad looked like:
And this is what my organic cotton ad looked like:
The ad was setup with the conversions objective. The goal of the campaign was to figure out whether the target audience valued recycled polyester clothing that helps solve the waste problem over cotton clothing that is made organically.
Campaign 3 – Results
For females looking at the Add to Cart conversion results we can clearly see that recycled polyester performed significantly better, outperforming organic cotton 8 to 1. We achieved the lowest Add To Cart cost of Rs. 62.5 with this group compared to Rs. 93.77 for the male green t-shirt in Campaign 1. Also recollect that the female black t-shirt did not have any conversions in Campaign 1. The change in target audience and tweak in ad copy significantly improved results here.
For males we did not get any Add to Cart conversions for recycled polyester and only 1 for organic cotton. Compared to Campaign 1, it looks like the new male target audience did not value the t-shirt as much as the audience in Campaign 1.
Another interesting observation is the reach for females is about 30% lesser than males for the same ad budget, suggesting that this female audience is more expensive to target.
Let’s take a look at the engagement performance of each ad.
Looking at Clicks (All) and CTR (All) which is a measure of overall engagement with the ad, recycled polyester performs significantly better than Organic Cotton, especially among males. Males had engaged with the recycled polyester ad almost twice as much as the organic cotton ad, whereas females showed a 27% increase in engagement.
Looking at the Link Clicks performance which is a better measure of the value of the t-shirt to the user, it appears that both genders were interested in our recycled polyester t-shirts almost the same as organic cotton t-shirts. Women showed significantly more interest in both t-shirts compared to men, as can be seen from the higher CTRs and link clicks. When you look at the conversion rate of landing page views to Add to Cart, out of 80 females who viewed our recycled polyester landing page, 8 converted for a conversion rate of 10%.
Step 4 – Learn
Overall the data seems to suggest that waste management as a cause does increase engagement across both genders for an eco-conscious Indian audience. Both genders don’t show a greater preference for recycled over organic clothing, however women attach significantly more value to the recycled clothing. Women also attach a greater value to our product regardless of whether it is recycled or organic.
For men, the product or market needs to pivot to add more value.
T-shirt design, pricing or target audience are some options for the pivot. Further market validation is required after pivoting.
With a CTR (Link Clicks) of 4.37% and a conversion rate of 10% from Landing Page View to Add to Cart, the data suggests that a recycled t-shirt as a product offers significant value to the young eco-conscious woman in India.
But how many units would we need to sell per month to make a decent return? And is the market size big enough for us to convert so many customers?
Looking at a benchmark e-commerce conversion funnel for apparel, it takes almost 5 Add to Carts for 1 Transaction, which means we would need to spend Rs. 312.5 (5 x 62.5) to acquire 1 paying female customer. Assuming a manufacturing, packaging and shipping cost of Rs. 600, and the sale price of Rs. 1500, you can expect to make a profit of around Rs. 587.5 which is approximately a 39% gross profit margin.
Online apparel stores have a much higher return rate as compared to retail stores, typically around 20% for a good performing one. Factoring a return and exchange shipping cost of around Rs. 100, this would bring down the gross profit margin to around 38%. Here is how our gross profits would grow with the number of units sold:
|Units||Gross Profits (in INR)|
In order to sell enough units to become a viable business, the target market must be sufficiently large. With a 10% conversion rate from Landing Page View to Add to Cart, and a CTR (Link Click) of 4.37%, we would need a target audience size of around 2,28,833 people to sell 1000 units. However the target audience in Campaign 3 for women has just 93,000 people (as reported by Facebook), and hence will limit the total units that I can sell.
Once the sales gets saturated for this target audience, the next challenge would be to resell to existing customers. New products combined with email marketing, social media, discount offers, retargeting ads, etc. can be used to target existing customers and increase the CLV (customer lifetime value) of the customer. The impact of these on the business model is beyond the scope of this article.
Cost of this validation experiment
Here is the breakup of the monetary costs incurred for this experiment.
|Item||Cost (in INR)|
|UX design consulting||12,744|
|Fashion design consulting||13,500|
|SSL + Web Hosting||FREE|
In terms of time to conduct this validation, I took around 2 months in total. Most of the time was spent designing and building the website and t-shirts. Each campaign was run for an average of 2 days.
Limitations of this validation experiment
- Choice of platform – What if Facebook / Instagram is not the best place to find eco-conscious shoppers? I have made the assumption that this is highly unlikely, given that I was targetting young e-commerce shoppers.
- Choice of target audience – Was there a different market segment apart from people who showed an interest in plastic recycling who would have performed better? Trekkers, runners and travellers were other audiences that interested me, but I never tested these due to budget and time constraints.
- Choice of marketing strategy – The Facebook ads I ran maybe more cost-effective when retargeting a warm audience. However, by targeting a cold audience who are unaware of my brand and product, it does help establish a great baseline for all of my metrics. I have seen other Indian apparel startups use Google ads, email marketing and social media to find and retain customers.
- Duration of campaigns – Due to budget constraints I did not run some of the campaigns for a longer duration, which might have shown different results.
- Ad creative improvements – I am assuming my ad copy and photos were good enough for evaluating product-market fit. There is definitely a scope for improvement by using video content to market apparel.
One of the biggest costs of any digital business model are the digital marketing costs. In this article we shared data on 3 real marketing campaigns that were used to validate an idea for an e-commerce apparel startup in India.
We compared the experimental data with industry benchmarks to identify if we had a product-market fit. For a product that showed promise, we estimated whether the market size needed to make the business viable was large enough.
As the next steps to this market validation, I see 3 things that need to be done. The first is to improve the product, making it appeal to men at least as much as it appeals to women, so that the target market size becomes much larger.
The second is to factor CLV and expected sales volumes into the business model using published benchmark industry data or by consulting with an existing e-commerce apparel business. This will help establish a baseline growth model for the business.
And the third is to evaluate alternate marketing strategies such as social media content marketing or influencer marketing to reduce marketing costs and improve the bottom line.
Whatever step I take next, this market validation has already saved me lots of time and money by not building a product that does not have a viable market.