Pixm Use Case

 

Pixm is the world’s first phishing protection using computer vision. Pixm uses cutting-edge computer vision technology to stop phishing attacks at the point of click through their browser extension. 

We were tasked with taking Pixm’s consumer product to market and delivering their first 2000 customers. 

The client

 

Pixm is the world’s first phishing protection using computer vision. Pixm uses cutting-edge computer vision technology to stop phishing attacks at the point of click through their browser extension. 

We were tasked with taking Pixm’s consumer product to market and delivering their first 2000 customers. 

When launching any new product into the market gaining your initial customers is always the biggest challenge. We also had to do this in a way that was scalable and could help the business achieve their growth goals. 

The Solution

As we were delivering a consumer product to market we knew we needed a platform that would allow us to reach a large scope of people. Because of this, we chose Facebook as our chosen platform. 

We also felt Facebook would be the ideal platform as Pixm was a product that anyone using the internet would find valuable – Nobody wants to get hacked. 

We began by running conversion ads to our landing and set up tracking to see what percentage of people clicked on the install button, which would direct them to the browser extension install page. 

We also set up tracking on the thank you page so we could see a funnel of:

  • People being sent to the landing page
  • People clicking through to the browser extension store
  • People who visited the thank you page

Once we had this funnel in place we could easily see how each step was performing and how we could improve. 

As Pixm was being launched into the market there was no existing customer base and we had to use the Facebook detailed targeting options in our ads. 

We started with 5 ad sets and had 1 targeting option per ad set, for example, people interested in privacy. This allowed us to see how each ad set was performing and adjust our targeting based on those which were performing best. 

We also ran a minimum of three ads per ad set so that we could split test the different ads to each audience. 

Results

 

There results over a 5 month period were:

  • 2000 users
  • $9 Install / Acquisition Cost
  • 20 – 25 new installs every day (pre-mobile version of the product)
  • Reduced cost per acquisition from $30 to  $9
  • Prevented 60+ hacks from occurring.