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Swisscom: 38% more conversions for a multi-channel campaign with the help of Nexoya’s AI algorithms

Swisscom is the leading telecommunications, Internet and fixed network provider in Switzerland and offers IT products, as well as IT solutions for B2C & B2B. Headquarters are located in Bern, Switzerland.

Boosting marketing performance even further with machine learning

Swisscom’s B2B marketing department handles complex cross-channel marketing campaigns and executes them in a successful manner. Nevertheless, Swisscom was eager to find new, innovative ways to get even more out of their multi-channel marketing campaigns, by improving their marketing performance even further. The targeted goal was to increase lead generation for an event by getting more users to register for an upcoming event registration.

Main challenges for Swisscom:

  • Taking their complex campaign management to a new level.
  • Finding new, innovative ways to enhance the campaign performance by leveraging 1th party data such as Oracle Eloqua information, to optimize their campaigns.
  • Getting more value out of marketing budgets without spending more.
  • Integration and testing of AI-technologies into digital marketing processes.

The key objective was to find out how machine learning could boost the efficiency of already advanced and complex multi-channel marketing performance in a way that wouldn’t be possible otherwise.

Thanks to Nexoya`s machine learning algorithms, we were able to improve the conversions of our multi-channel social media campaigns by up to 38% in only 3 weeks, that’s stunning.”

– Milos Radovic – Head of Marketing Strategy & Development at Swisscom.

Smart marketing budget allocations with Nexoya

The main solution provided by Nexoya is multi-channel campaign budget allocations based on machine learning algorithms. Weekly optimization sessions were held jointly with Swisscom, the media-agency and Nexoya, where budget allocation suggestions from Nexoya were discussed and then implemented for each ad across the channels.

The overall goals were:

  • Take into consideration hard conversions from 1th party data (such as Oracle Eloqua) for optimization.
  • Increase conversions from existing marketing budgets without increasing the costs.
  • Get acquainted with smart budget allocations based on machine learning algorithms.

More conversions thanks to machine learning

Thanks to Nexoya’s campaign optimization feature, Swisscom was able to spend their budget more efficiently. By using AI to predict trends for relevant metrics such as Cost per Thousand Impressions (CPM), Cost per Click (CPC) and Cost per Acquisition (CPA), the optimal budget allocation for each channel and campaign was identified and proposed to the team – a challenge that’s nearly impossible to achieve without AI technology.

As a result, by implementing the budget change suggestions from Nexoya’s machine learning experts, Swisscom was able to maximize the overall effectiveness of their digital multi-channel campaigns. Moreover, the increase in conversions was not the only positive impact that was achieved. The overall investment per event-registration (CPA) was also reduced significantly.

By implementing budget allocation advice from Nexoya, we were able to get significantly more conversions for our multi-channel campaign in just a couple of weeks; a great new way to improve our return.

Emanuel Schwarz – Marketing Communication Manager at Swisscom.

Main benefits for Swisscom:

  • No guesswork when it comes to decision-making.
  • High-quality predictions thanks to Nexoya’s machine learning algorithms.
  • Up to 38% more conversions in just 3 weeks.
  • More efficient marketing budget allocation.

Emanuel Schwarz, Marketing Communication Manager at Swisscom, saw Nexoya as the perfect partner to collaborate with. He was eager to discover how Swisscom’s already successful and advanced marketing execution and performance could get even better thanks to Nexoya’s bespoke machine learning solution.

Company

Swisscom

Industry

IT

Headquarters

Bern, Switzerland

Size

19,100 employees

Type

Corporation

Optimized channels:

Adobe Analytics, Google Ads, Twitter, LinkedIn, Facebook, Instagram, Oracle Eloqua

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