Understanding Data Types in Data Analytics

Year 2005 was arguably the most important year for data analytics.

In November 2005, Google launched their analytics service, after acquiring Urchin in April 2005.

Since then, data analytics has transformed the perspective of marketers around the globe.

Every time advertising ROI was discussed, below statement was quoted:

“Half the money I spend on advertising is wasted; the trouble is I don’t know which half.”

 

Marketing cloud players like Oracle, Adobe & IBM are positioning their data analytics platforms just to address the above problem.

With data impacting every aspect of business, CMO’s believe their role is no longer restricted to brand marketing.

(Also Read: RIP CMO, VIVA CDO )

To understand this  further, we must know the types of data sets relevant in digital marketing.

Marketing Data TYPES

 

Data Analytics - Marketing Data Types

Marketing Data Types in Data Analytics

 

Usually, it needs an understanding of your customer journey, but most of the above data sets are common for various customer journeys.

For simplification, I have divided it into 2 broad segments:

Audience Data Analytics or Advertising Data

 

This data is usually acquired through multiple marketing touch points and it is also the most complex of all to interpret.

Most of this data is used for making better & faster marketing decisions.

You can divide audience data into following:

Market Research Data / Survey Data 

 

This data is acquired using primary and secondary sources to understand:

  • market competition analysis
  • audience behaviour in a category
  • offline communication effectiveness

It is extremely valuable for designing your brand communication.

Social Media Analytics Data

 

As more adults acquire smartphones, they’re spending an increasing amount of their time on social media.

Also Read : Time Spent on Social Media – By Nielsen

Social Analytics Tools

Social data analytics tools offers a deep insights about the life and preferences of modern day digital audience in the form of following data sets:

  • Audience Interest – what are their likings and dis-likings etc.
  • Affinity / Behavioural Data – Content consumption behaviour
  • Category Conversations – what are they talking about or discussing?
  • Brand Sentiment – benchmarking sentiment against different competitors.
Search Analytics Data or Intent Data

 

While social data helps us to understand their content consumption behaviour, search data helps us understand current market trends and brand preference.

First, to fully understand search data and its impact, one must know how to use Google Trends (see below)

Second, SEO data can be obtained from either the google webmaster tool or your own Google Analytics account.

This data further helps you to find out:

  • Key audience searches in your category
  • Competition brand preference
  • Content ideas for blog and social media
Website Analytics Data

 

If planned well (Read this post by Avinash Kaushik) , this data type can offer the most in-depth amount of insights to any marketing team.

Any website analytics tool (like Google Analytics or Kiss Metrics) allows you to find out:

  • Quality of your assets (like blog) and content (videos)
  • Quality of your landing pages ( UI and UX )
  • Audience customer journeys
  • Conversion Attribution (if you are generating lead or e-commerce)
  • Digital Marketing Campaign Effectiveness
  • Key Traffic sources
  • Return on marketing Investment

Customer Data or CRM Data

 

This data is extremely sensitive from a digital privacy standpoint.

It is very important to capture this data in the right format and keep it updated & consistent.

Top CRM Tools

Top CRM Tools

The customer data is often stored inside a CRM tools ( see above  )

Modern CRM tools can captures and store the following information in an actionable manner:

  • Customer PII ( Personal Identifiable Information like Name, Gender, Email, Contact etc )
  • Purchase Data – Details of all the products / service purchased
  • Loyalty Data – contains details connected to any customer loyalty program customer has subscribed to.

Digital data analytics can offer very deep insights, but only if you plan your data priorities in advance and also choose the matching tools at each stage of your marketing.