About Us
We focus on what’s called ‘Leverage Marketing’ – this is quick, easy to implement changes that makes a huge impact.
WHAT IS AN EXAMPLE OF LEVERAGED MARKETING?
Increasing match rate on Facebook/Google and making the algorithms ‘work again’ to reduce ad costs – the average match rate on FB/Google is 25%, We get get to 95% and above.
Using identity resolution to turn website visitors into leads which can be easily re-marketed to via email, sms to 3-4 sales.
Case Studies
National Personal Financing Company
Problem
Client had not been able to consistently, or profitably, scale across Google Display and Discovery channels
Audiences
Similar audiences
Managed Spend $100,00
(increased after initial results)
Time
45 days
Platforms/Channels
Google Display, Google Discovery
Target Benchmark
Roas = 1
Results
Preformance 45 Days
National Auto Insurance Advertiser
Problem
Client needed to find additional scale at as good or better than current ROAS
Audiences
Retargeting and Lookalike audiences
Managed Spend $30,00
(increased after initial results)
Time
30 days
Platforms/Channels
Target Benchmark
Retargeting ROAS = 1.52
Lookalikes ROAS = 0.52
*Client targets these initial metrics with expectation that LTV (much higher than 1.00) will follow proportionately
Results
Test period preformance (30 days)
A key dynamic to our company is that as the machine learning engine processes more data, it gets smarter in measuring intent. This leads to performance that continues to improve with time. The below is a graph illustrating the increase in ROAS during the test period. By the end of the test, daily ROAS was 100-400% above the benchmark.
Large B2B Advertiser (> $170 million in funding)
Problem
Client looked to effectively increase the numbers of leads and “Requests for Demo” for its services
Audiences
Audience Expansion
Managed Spend $30,00
(increased after initial results)
Time
60 days
Platforms/Channels
The Trade Desk
Results
Preformance 45 Days
TEST PERIOD PERFORMANCE (CONTINUED):
Stakeholder feedback:
“Hi Team, Here is what got me excited. If you look at the attached screenshot, they identified nearly 40% of users who would convert even before they converted and let us influence them with ads.”
“…using an overlay on our best performing campaign this outperformed the performance of our own organic traffic by 27%.”
– VP, Advertising (internal update to management)
TEST PERIOD PERFORMANCE (CONTINUED):
Audiences outperformed all traffic in key engagement metrics:
National eCommerce Company
Problem
Client looked to effectively increase the numbers of leads and “Requests for Demo” for its services
Audiences
Current customers + lookalike audiences
Time
90 days
Platforms/Channels
Facebook / Google
Goal
Increase efficiency and effectiveness of conversions to build a consistent, profitable ROAS with current customers and and expanded audience alike
Results
TEST PERIOD PERFORMANCE (90 DAYS):
After setting up, the machine learning quickly got to work, determining that 36% of the ad spend was being spent on fraudulent bot traffic. Once removed from the targeting pool, along with a focus on the pre-conversion lookalike audiences, we were able to increase conversion rate by 49%.
Since the machine learning continues to improve over time, by 6 months their audience size and engagement had doubled, and by 12 months, we had grown their conversions by 229%, resulting in an organizational record for sales.
National Media Purchasing Group
Problem
Inefficient ad campaigns and targeting had put the media group in jeopardy of losing a top account
Audiences
In-market audiences for their key client
Time
6 Months
Platforms/Channels
Facebook / Google Platforms
Goal
Identify and push custom audiences into existing paid campaigns to increase conversion rates and reduce cost per conversion
Results
Preformance 6 Months
After the 6-month period of continuous machine learning optimization, the client showed these results to their key account, gaining a renewal for another 6 months.
Financial Lead Generation Company
Problem
The highly-skilled paid ads team needed a way to quickly expand the volume of high-quality leads and reduce cost-per-acquisition across new platforms
Audiences
Lookalike audiences to current customers
Time
3 Weeks
Platforms/Channels
Facebook, Google
Goal
Prove the efficacy and power of the tool in an extremely condensed period to earn a long-term relationship
Results
TEST PERIOD PERFORMANCE (3 WEEKS)
This efficiency and increase in lead conversions resulted in the client selling more refinance leads at a higher rate. The higher rate is due to the increase in quality of the leads. Within 3 weeks, we segmented the high-value prospects, tracked their behavior and delivered the right messages, at the right moments. Based on the campaign improvement over such a short period, now, the campaigns only compete against themselves week-over-week.
Mortgage Loan Company
Problem
A large mortgage loan company had strong performing SEM campaigns, but felt they’d hit a plateau with their efforts
Audiences
Intent-based AdWords audiences
Time
3 Weeks
Platforms/Channels
Google AdWords
Goal
Leverage the MMAI tool to segment any bots or unlikely buyers from the targeting list to increase efficiency of current efforts
Results
TEST PERIOD PERFORMANCE (3 WEEKS)
We easily and quickly segmented bots from real people. Then, these bots were added in real-time to Exclude lists in Google AdWords to make sure no new ad budget is ever spent on these bots again.
The newfound 36% of their ad budget (now that it was no longer targeting bots) was properly allocated to high-value segments that are ready to purchase a home. This brought 12 new purchase loans which equal an incremental $52,600 in revenue after only 3 weeks of implementing the solution.
