Fintech Client Case Study

Fintech Client

Improving lead quality and cutting costs while maintaining lead volume

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Client Background

Client is a SaaS finance partner that provides financing to startup founders. Client has worked with JDM since 2022, leveraging our paid search, paid social, and SEO services.

 

Challenge

Client sought a stronger partner to help proactively improve the performance of their paid campaigns. The challenge was capturing quality leads at a more efficient cost. The goal was to improve quality without compromising quantity.

JDM Approach

In order to drive immediate improvements towards the lead quality and efficiency goals, we implemented a number of immediate strategic and technical changes to the client’s existing ad campaigns. In parallel, we designed a full account overhaul on both Google Ads and LinkedIn Ads. Our goal was to make changes that would result in immediate improvement in the short term, coupled with a structure that would lend itself well to long-term testing.

Results

Strategy

Google Search Campaigns Overhaul

Our new structure and ads were built to reflect client’s goals: high-quality leads and lower costs. To do this, we made a few significant changes:
  1. We broke out campaigns by keyword match type to best utilize Google’s machine learning capabilities. This allowed us to maintain strategic levers and keep a close eye on performance.
  2. Within the new campaigns, we recategorized existing keywords and recommended new keywords to ensure the search traffic captured was the most relevant possible.
  3. We created and implemented all new ads speaking to the technicality and specificity of client’s ICP, providing another layer of natural lead filtering.

In the days following this overhaul, we kept diligent watch over the search traffic and performance of these campaigns, making regular negative keyword additions and other key optimizations.

Optimizing Down Funnel On LinkedIn with Offline Conversion Tracking

When it comes to lead quality, data strategy is paramount. Ad platforms like LinkedIn have powerful algorithms designed to show the right ads to the right people at the right time. With that said, we wanted to ensure Client’s LinkedIn ads were able to optimize not just to leads, but to leads that generated high-value activity down their sales funnel. 

In order to do this, we worked with the client team to set up a connection between HubSpot and LinkedIn, allowing the LinkedIn ads algorithm to better understand which leads generated long-term value. Now, instead of measuring LinkedIn success at the lead level, we were able to work with data further down the sales funnel, resulting in higher-quality leads.

Cost Per MQL Results

The Results

After launching these main initiatives immediately upon beginning work with client, we achieved the following results in the first 6 weeks with no drop in volume:
  • Cost Per Marketing Qualified Lead (MQL) improved by 64%
  • Cost Per Sales Qualified Lead (SQL) improved by 65%
  • Cost Per Deal improved by 70%

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