B2B Lead Generation
Our client offers a credit card processing platform for businesses. Working with mobile terminals, standard readers, and even POS systems, They provides solutions for businesses of all sizes and needs.
The Performance Proof
Takeover date: January 2017
Challenges & Goals
We noticed several challenges when we began working with this client. There main goal was to reduce back-end CPA numbers while maintaining or increasing their lead flow and customer generation. Additionally, we helped overcome the issue of merging the data between their CRM system & Google Ads to analyze queries by sales, not just leads.
Approach, Strategy & Solution
We flagged our initial tasks as improving data readability and robustness, as well as creating extra data point connections that would lead to smarter spend allocations and optimizations. We developed a document that combined CRM data to campaign and keyword level platform data, which let us track leads and signed deals back to the proper source. In order to develop this process, we had to make sure we had the proper UTM parameters passed into the CRM. After we were able to achieve this, we moved to track site enter URLs to form fills, and were able to accumulate data by campaign, ad group, and even keyword when necessary.
Call data tracking was our next area of improvement. When we began working with them, call data was not being used effectively; there were a lot of inefficiencies in the setup, with the only extractable information being the site source of the calls. We dove deep into the call data and found several additional pieces of information that facilitated the creation of a link to the site source along with the keyword or creative that drove the call. More importantly, this link allowed us to track the outcome of the lead through the whole application and approval process, which was something the client was previously unable to do.
With new reporting in place, we were able to tackle the back-end CPA as well as front-end leads and CPLs. We began with a restructure that would maximize efficiency and work well with our new reporting set-up. Spend was directed to the campaigns and channels that showed the best performance in the back-end, and it was clear that low CPL from the platforms did not always correlate to a low back-end CPA. The structure we decided for the client was based on keyword category as well as device. The categories were based on the service that the keywords related to, such as Credit Card Terminals, Merchant Services, Mobile Card Readers, and more. The campaigns were also broken out even further by keyword match type.
As always with a new structure, we set bids manually and optimized based on in-platform lead cost as well as back-end CPA data from the leads that were generated. This optimization strategy gradually reduced both CPL and CPA. A few months later, we ran tests with TCPA, or in our case, TCPL bidding. Considerable success drove us to introduce several portfolio bidding strategies aimed at lumping together campaigns by CPL and allowing us to adjust with faster results. Once we hit more consistent and stable stretches, this strategy began to significantly increase performance. We eventually cut CPL by close to 50%, surpassing the client’s CPA goals.
Another important ingredient for success were our consistent negative keyword pulls. After launching restructured campaigns, we went through search terms every couple of days in search of irrelevant queries, along with queries that were good, but too expensive for the results they generated. Maintaining this practice helped us not only eliminate tens of thousands of dollars of wasteful spend but also prevented the client from hundreds of thousands worth of uneconomical future spend.
With our shopping campaigns, our main goals were the same as search. Improving CVR and CPL in the platform, while also achieving lower back-end CPAs. In terms of structure, we built and implemented it as three campaigns with multiple ad groups. This type of advanced structure is effective for clients such as NBC, which offer a variety of product types/brands. Arranging products by ad group gave us tighter control over queries, bidding, and budget. It also gives us the advantage of having product-specific negative lists. The goal was to secure multiple slots and dominate the ad space for higher profitability categories, such as terminals followed by other products groups (POS, mobile readers). Feed quality and correct bidding with the use of back-end data were key for achieving multiple slots. With both reports combined, we managed to decrease CPL and CPAL across the board.