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Dear Future

Copenhagen, Denmark

50-249Contact for ratesFounded 2005

About

Dear Future (formerly IIH Nordic, founded 2005) is a Copenhagen AI and data consultancy combining search, digital analytics and machine learning for Nordic and international brands.

Who They Work With

Consumer brands with first-party data already in the stack that want it turned into predictions the marketing team will actually use.

Based on 4 client engagements with a source URL · researched 9 Sept 2026

Our Take

This is the most measured portfolio in the Copenhagen roster. For Bonnier Publications, customer data from the CRM, Google Analytics and the newsletter platform was consolidated into BigQuery, a purchase-propensity model segmented 33.3 million users into five groups, and the segments were activated directly in search and display: 53 percent growth in digital subscription sales, 18 percent higher conversion, 327 million predictions generated.

The pattern repeats at smaller scale. Atrium's course-demand model predicts registrations three months out from web activity joined to CRM and booking data, returning 45 percent better marketing performance and two to three hours a day off manual monitoring. A clinically trained chatbot for the addiction treatment center Tjele produced 354 conversations and 25 qualified calls in three months, a 14 percent conversion, against telephone inquiries falling 20 to 30 percent.

The Pandora engagement is the honest counterweight: the client had already built a customer-lifetime-value model that its national marketing teams were not using, and the work was activation and roadmapping rather than modeling.

The weaker fit is a buyer who needs a model built from research rather than from commercial data already in the stack.

Key strengths

  • Outcomes are published with the mechanism attached—33.3 million users into five segments, 327 million predictions, 53 percent subscription growth for Bonnier Publications
  • The data path is named on each engagement: CRM, analytics and platform data consolidated into BigQuery before any model is trained
  • Twelve case studies, every one with a named client, spanning media, retail, healthcare and education

Good to know

  • The work sits on commercial first-party data—if your problem needs a model trained on something else, ask for that engagement specifically
  • The Pandora case is activation of a model the client already had; check which of your candidates' studies are modeling and which are adoption
  • Trading since 2005 under a former name and rebranded recently—confirm which team carried over and who would staff you
Gabor Kiss

Reviewed by Gabor Kiss

Founder & Curator, AIAgencies.eu · 9 Sept 2026

Based on the agency's publicly available portfolio. Own this agency? Claim your profile to provide additional context or request a review update.


How we evaluate agencies

Notable Clients

Every engagement documented in a published case study

Documented engagements: Bonnier Publications, Pandora, Atrium, and Behandlingscenter Tjele. All 4 carry a source URL on file.

Bonnier PublicationsFirst-party data consolidated into BigQuery, a purchase-propensity model segmenting 33.3 million users into five groups and activated in search and display: 53 percent growth in digital subscription sales, 18 percent higher conversion, 327 million predictionsSource
PandoraActivation of a customer-lifetime-value model the client's central business-intelligence team had already built but national marketing was not using; delivered as workshops and a prioritized roadmap across three horizonsSource
AtriumCourse-demand model predicting registrations three months ahead from web activity joined to CRM and booking data, surfaced as a daily action list: 45 percent better marketing performance, two to three hours a day off manual monitoringSource
Behandlingscenter TjeleChatbot trained on clinical knowledge for a private addiction treatment center: 354 conversations and 25 qualified calls in three months at a 14 percent chat-to-call conversion, against telephone inquiries down 20 to 30 percentSource

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