HOW TO DISCOVER THE HIDDEN VALUE IN YOUR CUSTOMER DATA?

HOW TO DISCOVER THE HIDDEN VALUE IN YOUR CUSTOMER DATA?

As the field of analytics turns more and more predictive, emphasis on using data moves to discovering unknown landscapes. But moving beyond the obvious to completely understand your customers’ journey is a very complex step. How can you derive patterns from countless data sources to optimize customer experience and create a competitive advantage?

CREATING A 360-DEGREE CUSTOMER VIEW

Companies today are focusing on creating a 360-degree customer view. To do so, the first step is to have your data collection up and running, making sure that you can deliver data to a centralized environment, from which it can be used for further processing. In many cases, this environment is a data warehouse. In an ideal situation, all data from online channels, CRM technology, campaigns, call centers and order management is structured an gathered there to draw the best possible conclusions for optimization. However, this comes with many challenges to collect “good data” related to the volume, velocity, variety and veracity of data. We previously highlighted the struggle to stream web data to a data warehouse, but in the entire ETL process, there are many more. Luckily, one factor that has disappeared from the list of challenges is costs of data storage. That has become very affordable.

DISCOVERING HIDDEN VALUE

Nevertheless, if you manage to deliver all your data to a centralized environment, where do you start if you want to find patterns and insights to outperform the competition? In other words: how can you discover the hidden value in your customer data? The traditional approach is to put analysts and data scientists to work. They define a hypothesis based on the events they think are important. For instance: which events lead to churn or conversion. And then they start collecting data to see if factors like income and the event are correlated. To really validate their hypotheses, often an iterative process, may last long time. In practice analysts and data scientists spend up to 70 or 80% of their time on data preparation.

DIMENSIONS OF DATA

With the internet of things and web data, vast amounts of data are being added to those of traditional sources, making data processing even more complex and running the risk of not seeing the wood for the trees. Especially when this data is poorly structured or customers are high up in the conversion funnel and many variables have to be taken into account. The more dimensions the data has, the more complex it gets to obtain insights, making it very hard to create substantial business value.

FUNDAMENT FOR DATA ANALYTICS AND DATA DISCOVERY

As in practically every data challenge before, smart technology can make your life easier. There are discovery platforms available to recognize patterns in vast amounts of data. These can identify the most important variables that need further research to determine their business relevance. Analysts and data scientists can use this information to perform business analysis and determine the actual value of these variables in the customer journey as a whole. However, for these platforms to reach their maximum potential, you need to have the right infrastructure in place. This has to cope with the volume and velocity of the data you are collecting. Also, you have to be able to connect all relevant databases to create your 360-degree customer view.

APPROACH

So to discover the hidden value of your customer data, here’s the way to go:

  1. Make sure you can collect data from all relevant sources
  2. Store this data in an environment powerful enough to process it and with no limitation when it comes to storage capacity
  3. Run a discovery platform that can determine which variables have most effect on the important events of your customer journey.
  4. Make a predictive model to foresee which visitors will match this variables

Take actions to optimize this customer journey and reduce churn or improve conversion

FEEL FREE TO CONNECT with Ronald van Loon (LION) on Linkedin, Twitter and YouTube.


JOIN A FREE WEBINAR TO LEARN MORE

To give you more insight on how you can put this approach into practice, Adversitement’s Ronald van Loon will host a free webinar about this topic, titled Discover the hidden value in your customer data. In this webinar, Ronald and Joep Fennema, Data Scientist at Teradata will:

  • Discuss several case studies
  • Elaborate on the challenges
  • Define the impact for organizations and professionals responsible for online sales and customer retention
  • Show how a new approach and technology can solve these challenges
  • Discuss the result for organizations

 

 

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Stephen Furlong

Delivering Enterprise Cloud, Data Science, Machine Learning capabilities

8y

Nice piece Ronald. From working with many customers on the 360 journey, one of the biggest sources of friction is in the data movement. More specifically, the expensive and brittle ETL used to feed the relational EDW can lead to a 360 quagmire. I recommend that my customers use an Operational Data Store using a NoSQL database. Ingest the data AS-IS from all data sources (structured, semi-structured, any-structure) at massive scale. This allows us to reduce the data movement friction, so we can spend our cycles on the more important analytics/inferences. Not a trivial technology ask, but databases such as MarkLogic do just this and provide built-in analytics via a sophisticated search capability. Thanks for the thought provoking piece.

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Kevin Petrie

Vice President of Research at BARC

8y

Ronald, thanks for these insights. Another valuable dimension of managing data is optimizing its placement across platforms. Many enterprises continue to rely upon EDWs for structured data analytics, but struggle with its growth. We find the most successful organizations identify cold EDW data and move it to Hadoop, freeing up valuable EDW cycles and creating new analytics opportunities in Hadoop. @KevinPetrieTech Www.attunity.com

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very insightful article !!

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