Increased efficiency through machine learning

Creditplus benefits from increased efficiency through machine learning

Creditplus Bank significantly increased their conversions by introducing smart bidding and switching to data-driven attribution. In addition, they were able to better understand the relevance of ads on smartphones and to further optimise mobile clicks, despite lower mobile costs.

The goals

Efficient use of online marketing budgets
New customer acquisition & more conversions
Maintain mobile relevance

The approach

Implementation of conversion tracking
Implementation of smart bidding
Switch to data-driven attribution

The results

Smart bidding increased conversions by 19% and mobile conversions by 12%
Smart bidding reduced mobile CPA by 7%
After switching to data-driven attribution conversions increased by another 27%, and mobile conversions by 20%
Efficient acquisition of new customers thanks to automation and machine learning

The challenges of digitisation in the financial sector

Consumer loans has been the core competence for Creditplus Bank for many years and in these times of digitalisation they wanted to further generate growth in a sustainable way. Modern consumers are used to and expect to have their needs met immediately across a broad range of products and services. They expect the no less from their bank.

Digitally optimised processes drive Creditplus forwards

Creditplus responded to the new way of banking early and the loan inquiry process was quickly digitised for customers. The company also relied on innovative, digital solutions for online marketing - which is not necessarily the norm in the conservative banking industry. Creditplus worked together with Google and hurra.com™ to plan and implement time and cost saving measures across multiple channels.

“Our goal was to further improve our already well optimised Google Ads campaign and, above all, reduce CPA (Costs Per Action).”

Christoph Raue, Head of Marketing at Creditplus

In addition, Creditplus' marketing director focused on the potential and role of ads on smartphones for generating leads: Does it make sense to give the mobile segment a higher priority and more budget?

Data driven attribution assigns the right value to both last click and other touchpoints

Led by Google and supported by Hurra Communications GmbH, Creditplus Bank worked to further increase the efficiency of their campaigns. The manual bidding used up to this point could not adequately address the customer journey, as the model used only allocated value to the last click.

However, we knew that many customers use their mobile phone for research but complete the conversion on desktop. This is where data-driven attribution came in, considering and evaluating all clicks on the way to completion. This provided a more complete picture of the entire path and allowed for a realistic mobile share rating. Smart Bidding, the automated bidding process, responded in real time and adjusted bids automatically. Machine learning made bids more accurate, and every conversion cheaper.

What were the biggest challenges in the process?

“The biggest challenge for this project was to implement the changes cleanly so as not to impact the current performance” says Christoph Raue of Creditplus. To achieve this, the switch to automatic bid control was done in several stages.

The first step involved implementing Ads conversion tracking for Creditplus. This tracks what happens after a user clicks on an ad and what action was taken- e.g. customer activity such as call or order that is valuable to the business is performed. In the second step we switched to automated target CPA bidding. Bids were set to achieve as many conversions as possible within the defined CPA. These changes quickly had an impact.

“After implementing automated bidding conversions increased 19% while CPAs dropped 7% and mobile conversions increased 12%.”

Christoph Raue, Head of Marketing at Creditplus

After a two-to-three-month learning phase for the algorithms the third stage was implemented: Data-driven attribution (DDA). As a result, all touchpoints leading to the conversion were considered relevant. This meant that mobile clicks gained in importance: The switch to DDA increased mobile conversions by a further 20%. In contrast, mobile CPAs were reduced by 3%. Creditplus was now able to identify relevant conversion sources and better target their ads.

“Bidding methods based on data driven attribution enabled us to quickly and effectively identify audiences that were more relevant to us, and to address them successfully with advertising. As a result, it lead us to achieve higher quality leads.”

Christoph Raue, Head of Marketing at Creditplus

Automation as an efficiency driver

Hurra™ also benefits from the change in their daily routine: Being able to work along-side automation means they have more time to analyse and work on more strategic areas of optimisation. The only manual optimisation is to update target CPAs. “Automated Bidding is highly efficient and gives us more time to invest in creating new creative material and analysing performance,” said Marcel Schneider from Hurra™.

“Automated bidding saves time, which can be invested in analysing performance and scaling campaigns.”

Marcel Schneider, Agency Group Head at Hurra™

Reporting provides new insights into customers behaviour

Creditplus were very pleased with the results of bid automation: “We were particularly impressed by the machine learning technology. We could never have estimated the potential for optimisation in advance. It is amazing what is possible with such algorithms”, says Christoph Raue, Head of Marketing at Creditplus.

Raue especially appreciates the important insights gained for mobile: “Our hunch that mobile played a major role in the customer's decision-making process has now been substantiated based on clear data.”

“It's worth being brave and trying new things.”

Christoph Raue, Head of Marketing at Creditplus