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Customer View

Get a comprehensive and unified view of the customer based on all available data sources.

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Data Mining

Discover robust and actionable patterns in your data with machine-learning algorithms.

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Customer Analytics

Monitor your customer base and the effect of your communication with dashboards.

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Predictive Analytics

Exploit robust patterns in customer behavior to create trigger-based, automated workflows.

our services

Customer View


A single view of the customer is the cornerstone of effective insight development and advanced data-driven execution.

First step is to identify all relevant customer data sources. These include, for example:

  • Basic customer information: id, name, zip code, email
  • Communication exposure with timestamps
  • Transactions
  • Website clicks
  • Call center interactions
  • Survey responses
  • Products and product hierarchies
  • Store locations

Data are transferred securely to Innohead's data platform, transformed and grouped into a single customer view.

We integrate data across all common systems and handle millions of records with minimal resource drain on your IT department.

Data Mining


Discover robust and actionable patterns in your data with machine-learning algorithms.


Innohead uses machine-learning algorithms to address questions such as:

  • What customer behaviors are predictive of near-term exit?
  • What is the probability that a given customer will react positively to a costly offer?
  • What characterizes a customer just before he becomes more valuable?
  • Which existing customers are the most promising leads for our new product?
  • What is the probability that a given customer will unsubscribe to our newsletter?

A data mining engagement starts with an introductory session identifying available data sources and initial hypotheses. Next, progressively more refined findings are presented and discussed - typically in the course of two workshops.

customer analytics

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Customer Analytics


To act on insight, customer data must be available to business systems in processed form. Innohead extracts a large number of features from customer data, which in turn are made available via a web-interface or uploaded to business execution systems. Examples of typical features:

  • Customer id
  • Time since last purchase (days)
  • Customer touched web page A (yes/no)
  • Spending last 3, 6, 12 months (amounts)
  • Percentage of total spend on product category A, B, C last 3, 6, 12 months
  • and more...

Such features are key building blocks for dialogue flows, customized website widgets and other interaction features. A dashboard is provided for monitoring the evolution of the customer base and the effectiveness of communication. Dashboards often include map elements.

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predictive analytics

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Predictive Analytics


Advanced personalization in communication and product offerings require up-to-date predictive analytics. Based on daily data updates, Innohead provides ongoing predictive services such as:

  • Lead prioritization
  • Recommendation engine
  • Response modeling
  • Sales potential
  • Churn probability or risk of lower sales

Scores are uploaded to business systems or provided as a web service for further integration. A dashboard is provided for monitoring system status and predictive performance.

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our team

Niels Stender


Founder, PhD Economics & Management
Email: niels@innohead.com
Phone: +45 21 26 88 20

Jacob Wellendorph Ejsing


Partner, MSc Economics & Finance
Email: jacob@innohead.com
Phone: +45 42 28 76 00

Lars Bojsen-Møller


Developer, MSc Computer Science
Email lars@innohead.com
Phone: +45 50 90 54 74

contact us

  • info@innohead.com
  • +45 36 96 05 80

Contact form

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Find us


Office Vesterbrogade 74
DK-1620 Copenhagen
Phone +45 36 96 05 80
CVR# 18 72 16 00
Email info@innohead.com
Parking Tullinsgade 7
DK-1618 Copenhagen

Business hours

Mon-Fri         09:00 - 17:00


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