General data driven marketing

Three stages in transitioning towards data driven marketing

When transitioning towards data driven marketing a company goes trough different stages both from technological, organisational and cultural perspective.

How an organisation can benefit from advanced attribution modelling

Attribution modelling remains a hot topic. Its difficult to implement and also to act on, we provide some advice here.

Attribution modelling

Data driven attribution down to keyword or ad-content level

Doing data driven attribution on keyword level can be very valuable as every keyword along converting customer journeys get conversion credits and a ROAS. Its one of the big benefits as it simplifies the analysis and saves so much time and money.

The two widely used data driven attribution models: Shapley value vs. markov model

Here I go into the differences between them. Markov model has the benefit that it takes into account the order of the events.

An example how to do attribution modelling in R

Here we go trough some code examples how one can do attribution modelling in R.

Data visualisations

How to get windsor.ai data into Microsoft Powerbi

How to connect PowerBI to windsor.ai and all marketing data platforms and attribution modelling.

Data Engineering and pipelines

Connect salesforce and google analytics with windsor.ai

How to track on qualified leads and closed revenue if the sales revenue is tracked in a CRM like salesforce.

Marketing platforms

Billiger.de and advanced customer journey analysis

Price comparison site can performance really well when looking at whole customer journey.

Connexity tags and advertising ROAS

Connexity ROAS easily visualised and attributed.

Appnexus, thetradedesk.com and Google Display and Video360

Windsor.ai integrations to the DSP platforms.

AWIN and other affiliate sites and multi-touch attribution

Affiliates like AWIN can perform really well with data driven attribution.

Tool Comparisons

Funnel.io vs segment.io

A quick comparison of funnel.io and segment.io

Fivetran vs stitchdata

Comparing the data-pipeline tools in a quick showdown.

Tableau vs qlik. vs. Looker.com

Comparing the three different visualisation tools.

Presentation library

Zürich Analytics Round-table presentation

A presentation Niklas gave at the Analytics Round table Zürich.

Marketing data research

TBD

Startups and Venturing

Frequent mistakes in corporate venturing

Some mistakes we are seeing when corporations attempt new ventures.

Some things we learned from a failed product launch

We wrote down some things from our failed product launch.