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Why is Identifying Customers a Huge Problem in Today’s Multichannel World?

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The Situation

Research by eBay Inc. has found that the average consumer will use as many as three to five devices or platforms in the course of making their buying decision and completing a purchase.


This tendency to hop from device to device during the decision-making process greatly increases the risk to retailers that a customer will, intentionally or otherwise, not complete a purchase.

The research also found that a quarter of online and mobile purchases are made by customers who could not have bought the products locally, with these purchases accounting for €9bn worth of sales in the UK alone in 2012. - eConsultancy


The Problem

You can only track shoppers across multiple devices or platforms if you can identify them on each device.

For example, if you have 20% identification (which might sound OK), the chance of following a shopper across three devices is 20% x 20% x 20% = 0.8%, which is useless.

But if you have 60% identification the chance of following a shopper across three devices is 60% x 60% x 60% = 21.6% which is still useful for remarketing.

So you need the best identification rate that you can get.

The Solution

It's not enough to require shoppers to login before they are tracked. You need a system, like Fresh Relevance, that combines multiple identification strategies, such as:

  1. anonymous tracking, so it stores customer history pre-login and merges it into their main history when they are identified
  2. email-to-web, so that when a customer clicks on a link in your marketing emails and arrives at your Website, they are instantly identified
  3. first party cookies - not third party as some solutions use - so your cookies work by default on mobile and you can recognize returning shoppers
  4. integration with pop-up registration forms
  5. and finally standard login at the checkout.

Do all that, and you can get identification rates above 50%, which will get you great remarketing results.

How To Do This With Fresh Relevance

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