Product Research Experiment For Online Stores
Learn about a product research experiment using dropshipping and Shopify. Discover what we learned and how to reproduce our results for yourself.
The Product Research Experiment
The experiment was about discovering new product ideas with concrete data and analysis. We wanted to produce data to be used by our clients later on.
By creating an alternative brand and an online store, driving paid traffic, and optimizing sales funnel outside any established brand, allowed us to test with more variables and fewer restrictions.
Producing actionable data that can be replicated is crucial. While any research can be used to optimize businesses, research that is created with a single goal can be more beneficial for finding growth targets.
Actionable data is more valuable, and it provides opportunities for businesses to seek growth.
Always trying out innovative methods to discover hidden opportunities for businesses is a great idea for keeping ahead of the competition.
The Product research experiment Itself
Create a completely new brand from scratch and test product ideas with dropshipping and Shopify.
We created our new online store with Shopify, which cut down the time investment of the experiment to a minimum.
After the store was created, it was time to produce the traffic to test the online store and the chosen products.
The experiment was to last 30 days, including everything:
The experiment was about discovering product data, not about the profitability of the products.
- Discover original data for product ideas that have been proven by the market.
- Produce new marketing angles for our clients to be used later. The reasoning behind creating a marketing strategy for a new brand was to test completely new approaches without utilizing an established brand.
- To produce as much data as possible within the given budget.
- Testing dropshipping as a product research tool for new ideas.
- Improve and test new Shopify sales funnels.
- How would the experiment serve traditional keyword research?
- Discover a new way of creating data-driven product research.
Setting Up The Experiment
The setting up the experiment consisted of:
- Brand creation
- Online store creation
- Finding products
- Online advertisement strategy
- Installing web-analytics tools
The Creation of the Brand
A couple of rules we had with the brand were:
- Couldn’t compete with our client and not use any existing resources
- Everything had to be made from scratch.
- A unique approach to something very traditional
We started by brainstorming random ideas that would be fitting, and after deciding on the name and general look and feel of the brand, we continued.
Then we started setting up necessary email accounts, domains, and social media accounts for the brand. The necessary ad accounts for the experiment were created as well.
The Creation Of The Shopify Online Store
We chose Shopify as a platform as it’s fast to set up, reliable, and easy to set up for dropshipping in general. Our goal was to build a Shopify store from scratch to fully functional in only hours.
We wanted a legit online store, had the purpose of being online, and serve as a case study for later and wouldn’t cost a fortune in labor or initial starting costs.
We chose a free theme from Shopify, to cut down our cost, and to be honest, we only needed to showcase a couple of products with a simple landing page.
We created a simple landing page with Shopify Brooklyn theme and product content copy that would match our advertising later on.
It was time to connect the domains, emails, socials, and payment integrations (Paypal, Stripe) with Shopify.
The whole setup process only took a couple of hours, not including the copy, and other branding materials.
We sourced products from Aliexpress to match the original product ideas we had.
We wanted to test four different products in two categories that matched the ideas.
We used Oberlo to import the products from Aliexppress to our Shopify store and made a necessary copy, and image changes to make the product pages the best they could be.
We chose to use the plugin Oberlo, as it would make it simple to import and manage the dropshipping side of things.
The products had a couple of requirements:
- Had to match the original idea
- Had to have fast shipping for ePacket-countries
- A product that allowed ease of content creation
- Verified, and trustful supplier
- Over 100 sales a day and over 100 positive reviews
- Upward trend
Running the Product Research Experiment
Our product research marketing strategy was the following:
Facebook Ads were chosen because it has been proven to be a good source for paid traffic. It provided the playground for testing the validity of your product ideas.
Google shopping ads were also created because it was simple to start with since the product feed necessary could be created within Shopify very easily.
We allocated most of the budget for Facebook ads. After a while, we terminated Shopping ads, as we were more interested in the data Facebook ads could provide us, for this experiment.
Product Research with Facebook Ads
In phase one of the advertising, two main campaigns were created:
- We produced a general data collection campaign to run for only a couple of days. Its goal was to test different ad creatives. To have the best results, you would have to keep testing ad creatives at all times, but we decided to move on pretty quickly.
- Basic retargeting campaign – Retargeting users who interacted with the ad – or went up in the sales funnel.
After the initial thought process, we landed on four different interests for targeting that could work for the given products.
In the general campaign, we had four ad groups with each one testing three ad creatives, and a single interest.
The campaign goal was engagements to see which of the creatives would work the best for the rest of the experiment run time.
We tracked the following sales funnel and their metrics:
- View content
- Add To Cart
- Clicks and Clickthrough-rates
In the second phase of the advertising, a Conversion-based campaign IF enough data for lookalike creation was collected.
Phase Two Of The Product Research Facebook Ad Campaign
We had collected the minimum required amount of events to create a lookalike audience. Early on, the lookalike audiences could be tested.
The created lookalike audience was based on the data collected on the View Content – event. The campaign created included three ad groups with varying levels of lookalike audiences:
- 1% View Content
- 5% View Content
- 10% View content
We matched the ad groups with the best-performing ad creatives from the engagement campaign. The chosen creatives were the two best-performing ones. To the mix, we added a completely new ad creative.
The added ad creative performed the worst, and we scrapped quite soon after starting the campaign.
Unfortunately, we didn’t have enough time to reach our data collection goals. The use of lookalike audiences immediately improved results, though.
The campaign had to be canceled before the end of the 30-day mark.
Phase Three: Analytics And Results Of The Product Research Facebook Ads Campaign
The campaigns had collectively had the following results:
- 1 228 Clicks with a 2.79% CTR
- CPC 0.57
- ROAS 2.21
- Cost per Purchase: 24.72
- Purchases: 28
We weren’t happy with the overall results, but the break-even point was achieved when everything is considered. Our breakeven point for the chosen products was at ROAS 2.10.
Every purchase was achieved with cold traffic, and further optimization could achieve a higher ROAS.
The cold traffic would be warmer when utilizing data from these campaigns when we would eventually create a new campaign for clients with data from the experiment.
A solid and established brand with higher product quality, customer experience, and new online store sales funnel data would emerge with a successful campaign for their new product category.
We failed in not using Google Shopping to gain more data.
In the end, we received one good strategy to recreate in the future. Meaning, you can use low budget campaigns to extract impactful data for any business.
Concluding The Product Research Experiment
We reached many of the goals of the experiment as planned:
- We collected data for product ideas that have scalability in the market, at least on a lower scale.
- We found new marketing angles for the clients. The tested ad creative will be used in the later campaigns.
- We found out that the budget was insufficient to produce enough data to produce precise decisions but enough to tell which products have the most potential.
- New product ideas and a category were discovered. Optimizing them has the potential to be profitable in the future.
- The viability of Shopify as a platform was completely tested and proven successful.
- New ideas to improve conversions and online store sales funnel.
As part of larger keyword research, our product research experiment was successful as we found usable data.
Would we recommend this experiment to be used for product research?
While it produces tangible data for online stores, work needed to create the experiment might not be worth it for everyone, and not suitable for smaller online stores.
For smaller online stores, it would be better to understand their product demand on a surface level and track every bit of data they can while selling them and optimize them on-the-go.
For larger companies, the experiment might provide more valuable data than surface-level research. The strategy works well when looking into more riskier growth avenues for your company. When small percentages can make a difference, consider the strategy.
Engaio Digital is a digital growth company that discovers growth techniques for your business. Whether you’re looking into data-driven advertising or experimenting with new methods, Engaio Digital will provide the required assistance.