Eftsure is a SaaS specialist company which protects businesses of all sizes against every type of EFT Payment fraud.
- 8 .33% Click Through Rate (LinkedIn Engagement Rate)
- 5338 Outreach Messages
High Quality B2B Leads in 4 months
Introduction
Syte Marketing Case Study – eftsure
eftsure have a large potential audience of customers for whom their software provides a very important role in protecting against payment frauds of all types.
Payment fraud is particularly prevalent in industries where a lot of once-off payments take place (in particular the legal, manufacturing and automotive industries).
The challenge that existed was that these “perfect prospects” not only didn’t know that eftsure existed, they also didn’t know that a product/software like this existed to solve their problem.
They were very aware of their problem but weren’t aware of the fact that there was a solution in the market.
What Approach Did We Use to Solve Their Problem?
Because their customer was a “hard to reach” c-suite executive in most cases and their customer wasn’t the person actively searching for this solution, we used LinkedIn Ads to target and convert these prospects into leads.
What Audiences Did We Use?
Running generic LinkedIn ads to a large generic audience is never effective. We broke their audience down into “buckets” which fit into very niche segments.
Bucket #1:
CFO’s in legal niches.
Bucket #2:
People with Manager/VP seniorities and upwards working in the most impacted industries:
- Automotive.
- Manufacturing.
- Legal.
Bucket #3:
We used high data intent lists and audiences:
- Lookalikes of customers.
- Lookalikes of past leads.
- We were unable to use web-based audiences as the local presence didn’t have any current web traffic at that stage.
How Did We Increase CTR and Lead Conversion Rate?
Click through rate and lead conversion rate are always a function of relevance.
Although the software had a far-reaching appeal, it was important to break the campaign into a number of purposeful niches in order to craft our ad message copy to one which was super specific and hyper-targeted.
