There are a very limited number of marketing channels available for gaining new customers when you are running an eCommerce brand. Currently, the only two ways to get some traffic to your store are either influencers or Facebook Ads (SEO was a viable option before giants like Amazon flooded search engines).
As you might expect, these two channels are pretty saturated or concentrated. Influencer marketing went from macro to micro to now nano-influencers as their price increased with time. On the other hand, Facebook Ads CPC/CPM is steadily increasing year over year, reflecting in Facebook’s revenue growth.
I decided to revamp my strategy and escape the never-ending competitive battle on social media. The key? Instagram email scrapers.
While scrolling through some of my competitors’ Instagram followers and noticed that none of them followed my account. I also noticed that a lot of them (I’d say 30%) had their contact email in their bio.
My eyes widened, my mouth opened and my heart stopped for a second.
I immediately opened a spreadsheet and started copy-pasting emails along with any other data point I could find. Name, username, biography, and in some cases even private phone numbers.
As I was visiting and extracting data from hundreds of profiles I was already thinking of ways how I would use the data. But all my joy stopped with an Instagram popup saying I cannot visit another profile for 30 days.
I've lost the first battle!
I’m a graduated android developer so I’ve decided to automate the data gathering process with Python.
Bought a lot of Instagram profiles that will do the scraping part (through the unofficial Instagram API). Proxies for remaining undetected and started building my user database.
If there’s someone eager to build an Instagram scraper, use this Github Repo.
While the development took a lot of time (and money) I got five thousand emails from people that follow my competitors ie, highly potential customers!
I couldn’t wait another minute, so I immediately wrote my first cold email and send a huge blast to all of them.
The results? 🥁 🥁 🥁
Terrible! Only 0.04% visited my online store!! I was furious.
While I wasn’t sure why the results were so terrible, it was obvious to me that I’ve extracted emails from the wrong people! So, I started googling and found tons of Instagram scraping tools.
I used a tool called Inmainmanager that and the process was almost as difficult as building the tool myself all over. A lot of proxies, accounts, installations.
But I managed to collect more than four thousand emails and went back to creating another blast.
The results?
Pretty much the same…
After a lot of research, I found out something obvious (but still shocking).
The biggest reasons why my campaigns flopped:
Luckily, my domain from where I was sending emails to all of these people didn’t end up in spam. If I did, any new email I would send would only be found in SPAM!
I randomly found this Instagram email scraper service that has identified this problem and offers validated email data with additional targeting options on top of regular scraping.
Every email that they scraped from my competitors’ audience got validated so I can only email real people.
They also segmented the data based on location (don’t know how they do it but worked awesomely), gender, and keywords users had in their bio.
Here’s the exact strategy that got me to 300k in MRR.
The validated/targeted lists I started getting were absolute gold. Started getting better click-through rates and a lot of new customers.
While the cold emails were clearly working I wanted to take it a step further.
I’ve previously used my customer email list as Custom Audiences in Facebook Ads. But, I remembered that they don’t actually ask you to verify that the list is from an audience that opted in (customers, subscribers, etc). So, I imported the emails scraped from Instagram into Facebook Ads.
Can you imagine running ads ONLY on people that follow your competitor? Or people that have used specific hashtags in their posts that are relevant to your business?
At one point we had a 12x return on ads spend!
So the process I used was this.