Introduction to Nonline Analytics – True Multi Channel Analytics

Contrary to popular belief, marketing especially in the developed world is neither purely online nor purely offline, it is nonline.

In nonline marketing we do not prioritise online marketing channels/touchpoints over offline marketing channels/touchpoints and vice versa, as customers can go back and forth between the two depending upon:

# The stage they are in their purchase cycle.

# The type of product/service they are purchasing.

# Value of the purchase. For example, not many feel comfortable making a high-value purchase from a mobile device.

# Their comfort level with technology. Some people prefer making a purchase online, some offline.

# The type of tools and technology available to them. For example not every person has got access to high-speed broadband. So their purchase behaviour is going to be different.

In a nonline marketing world, a custom purchase journey is very different and often complicated. Customers go back and forth between digital and non-digital channels to make an informed purchasing decision:

nonline-marketing

Form the chart above we can conclude that customer purchase behaviour is not linear.

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If you are a multi-channel retailer with both online and offline presence, then you should execute “nonline” marketing campaigns and measure the effectiveness of such campaigns.

A nonline marketing campaign is created and executed, taking both online and offline exposure/touchpoints into account.

True multi-channel analytics is nonline analytics.

When we talk about nonline analytics, we do not measure just the online customer purchase journey or just the offline customer journey but we measure the overall customer journey which includes exposure to both online and offline marketing channels/touchpoints.

So we no longer run marketing campaigns just to boost online sales or just to boost offline sales. We run campaigns with the aim to increase both online and offline sales and improve customer experience across digital and non-digital channels.

In a nonline marketing world, we cannot afford to ignore the online impact of offline campaigns and offline impact of online campaigns.

We need to take overall impact into account in order to improve ROI across marketing channels.

Why you should care about nonline analytics?

Since customers’ behaviour is usually not linear, their conversion path can include a series of interactions (exposures) with dozens of marketing channels (both online and offline channels).

This makes their purchase journey very hard to understand.

If you do not take into account the role of various online and offline channels in creating conversions then you won’t be able to understand your customers’ actual purchase journey and more likely attribute conversions to the wrong marketing channel and lose money.

In a nonline marketing world, no channel is solely responsible for creating conversions. Different channels work together to create conversions.

The role of the primary key in nonline analytics

The primary key is a term used in database management systems. It is used to uniquely identify each record in a table.

In the context of nonline analytics, the primary key is used to connect and merge online and offline marketing data. By merging such data you can measure the impact of offline campaigns on online campaigns and vice versa.

Without a primary key, you cannot do effective nonline analytics because there will be no way to tie online visits/conversions to a stimulus (thing or event that evoked activity) from an offline campaign and vice versa.

You can use vanity URLs, promo codes, coupon codes, surveys, etc as the primary key.

If a vendor/consultant promises to do nonline analytics for you then ask him one simple question:  “What will be your primary key”.

If he cannot answer this question, then he does not know, what he is talking about. 

Attribution Modelling in Google Analytics and Beyond
Attribution Modelling in Google Ads and Facebook

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  • Learn to implement attribution modelling in your organisation
  • Understand the customer purchase journey across devices
  • Determine the most effective marketing channels for investment

 Click book covers to find out more

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  17. Conversion Types Explained in Google Analytics Attribution
  18. Attribution Channels Explained in Google Analytics Attribution
  19. Differences Between Google Attribution & Multi-Channel Funnel Reports
  20. Introduction to TV Attribution in Google Analytics Attribution 360
  21. Conversion Credit Distribution for Attribution Models in Google Analytics
  22. Conversion Paths Report Explained in Google Analytics Attribution
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  39. Conversion Time & Interaction Time Explained in Google Analytics Attribution
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Attribution modelling is the process of determining the most effective marketing channels for investment. This book has been written to help you implement attribution modelling. It will teach you how to leverage the knowledge of attribution modelling in order to allocate marketing budget and understand buying behaviour.

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This book has been written to help you implement attribution modelling in Google Ads (Google AdWords) and Facebook. It will teach you, how to leverage the knowledge of attribution modelling in order to understand the customer purchasing journey and determine the most effective marketing channels for investment.

About the Author

Himanshu Sharma

  • Founder, OptimizeSmart.com
  • Over 15 years of experience in digital analytics and marketing
  • Author of four best-selling books on digital analytics and conversion optimization
  • Nominated for Digital Analytics Association Awards for Excellence
  • Runs one of the most popular blogs in the world on digital analytics
  • Consultant to countless small and big businesses over the decade