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How To Use Customer Behavior Data To Drive Revenue (Like Amazon, Netflix & Google)

Updated: May 15, 2019

Credit from Gary DeAsi

Look no further than Amazon, Netflix and Google—all of whom have built their entire respective empires around a nucleus of customer behavior data and analytics.

In a digital world where customer-centricity, personalization, and customer experience separate the winners from the losers, it’s no coincidence that these companies thrive. Before long, it will grow increasingly difficult to compete in any industry for those who are too slow to follow in their customer-centric, behavioral data-driven footsteps.

And yet, it’s amazing how many organizations still only take advantage of a mere fraction of the behavioral data at their fingertips.

There’s a good chance that this includes yours. If so, here’s the good news…

You don’t need to be an internet giant in order to leverage the power of behavioral customer data and analytics to take your business to the next level.

In fact, with the right knowledge and tools, any organization can do it. B2B, B2C, regardless of industry or size.

In this post, I’ll bring you up to speed on why customer behavior data is so important today, how it can be used to drive results, and why every company needs to adopt this approach.

Why Is Customer Behavior Data So Important Today?

Before the digital age, back when traditional one-way mass marketing communication was not only still a thing, but the only thing, personalization and customer experience didn’t really matter so much.

Back then, companies could get away with segmenting customers using primarily demographic and firmographic traits such as age, gender, income, ethnicity, occupation, industry, company size, geographic location etc.

In other words, focusing exclusively on the who.

Of course, there’s no arguing the importance of understanding who your customers are. Today, developing customer personas and ideal customer profiles are undoubtedly vital practices for understanding our target customers and for effective customer journey mapping.

But in the customer-centric world we live in today, just understanding “who” your customers are doesn’t cut it.

As Netflix’s VP of Product Innovation, Todd Yellin, pointed out in an interview with Mashable a few years ago:

“It really doesn’t matter if you are a 60-year-old woman or a 20-year-old man because a 20-year-old man can watch Say Yes To The Dress and a 60-year-old woman could watch Hellboy.” Todd Yellin, VP of Product Innovation at Netflix

As a 30-year-old male die hard Downton Abbey fan, this quote certainly rings true for me.

But I think it does a good job of summarizing the important point at hand, which is that:

You can’t possibly make assumptions on individual customers’ interests, needs, wants or values based purely upon who they are, or any “personal” you’ve assigned to them based only on demographic or qualitative characteristics.

Instead, companies like Amazon, Netflix and Google know that the key to understanding their customers can lie more in what they do; that quantitative insights revealed through their behaviors can paint a much more accurate picture of what their customers want and need, and how and when to best deliver it to them.

Use Customer Behavior Data to Deliver Personalized Customer Experiences

When you think about the Amazon, Netflix and Google customer experience, the first thing that probably comes to mind is their prolific use of personal recommendations.

Fueled almost entirely by customer behavior data, their advanced recommendation engine algorithms are designed to serve customers dynamically personalized content and product suggestions based upon each customer’s past behavior.

Just how effective are these customer behavior-based recommendation engines?

Here are a couple quick stats to get an idea:

  • 75% of Netflix viewer activity is driven by recommendation

  • 35% of Amazon’s sales are generated through their recommendation engine

  • Netflix’s recommendation system saves the company an estimated $1Billion per year through reduced churn

I’d say it’s working out pretty well for them.

But as insanely effective as it is, personalization is just one (incredibly lucrative) use case for how these digital age titans are using behavioral customer data and analytics.

Today, leading companies are increasingly thinking in terms of end-to-end customer journeys. They’re using data to understand and segment customers by their behavior to improve customer experience and deliver real business value, as I’ll discuss in more detail next.

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In emerging countries, mobile payments in stores are increasing, with Vietnam seeing the biggest increase to 61% in a period of one year, followed by the Middle East (45%). In general, Asian countries are more likely to adopt this behaviour more quickly than Western countries. Read more in PwC’s Global Consumer Insights Survey 2019, which assesses behaviour, habits and expectations of over 21,000 online consumers in 27 territories.

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