``````
granify_nodes.png

The Granify E-Commerce Blog

The Expected Value Of An Individual Visitor

What's the expected value of this anonymous individual visitor?

A visitor lands on your site. This is exciting! You try to match them up utilizing your CRM. They are unknown!

Many questions rush through your mind:

  1. Are they valuable?
  2. Have they bought with us before?
  3. Is this an opportunity to earn a "net-new" customer?
  4. How should they be treated?

All valid and important questions, and the way to tackle each is to start looking at the historical data. Our analytics tell us:


  • They came in through Organic Search directly to a Product Page using SKU specific keywords
  • They've been to the site 3 times in the past week
  • They've viewed the same product twice in the past 3 days
  • Their past sources came through (1) Paid Search and (2) Direct
  • They're using MacOS with the latest chrome version

If you run this segment in your analytics, you can back out the Expected Value based on every that has exactly matched these data points in sequential order. Let's say, based on this information, their Expected Value is $17.16 in their current state.

Next, they mouse over the product image for 3.8 seconds. Their Expected Value increases to $18.26. Then they click on the SKU-specific text, hit command-C and begin to accelerate their mouse and scroll speed towards the built-in browser search bar. Their Expected Value drops to $6.11. Are they price shopping? Should you take action? How do you know?

Based on their current state, there's a wide variety of potential behaviors, hesitations and actions the visitor could take. Each would change their Expected Value. Using historical data, you can determine their potential Expected Future Value(s) for each of these next potential moves. Likewise, you can also determine the probability that each potential behavior, hesitation or action will occur. Using this information, it's important to compare their Expected Value in their current state (Expected Present Value) versus their Expected Future Value. If their Expected Future Value exceeds the Expected Present Value, then it's best to wait and see what they do next. This is all done with the goal of maximizing their value.

granify_machine_learning_explainer_loop.gif

Now, what if you could do this in real-time, at scale, automatically for each individual shopper on your site? Would that be valuable? What if amongst those potential elements that are factored into the Expected Future Value, you could dynamically introduce nudges, contextual information, selective offers, selective upsells, etc. -- all with the goal of maximizing their Expected Value?

Hopefully this has given you something new to think about. I'm excited to announce we just recently launched Granify's new artificial intelligence engine which enables you to take advantage of maximizing each individual shopper's value while they shop in real-time. If you'd like to learn more, request a consultation with one of our conversion experts and we'll be in touch shortly.

Brady holds both an MBA and masters degree in Digital Marketing along with 7+ years driving rapid growth for startups. His work in digital marketing has been published in two university textbooks and his domain expertise is now utilized to drive Granify’s product to the next level.

 

SHARE THIS STORY | |

Looking for more? Our readers also liked...

Want weekly insights in to the world of e-commerce optimization?

Recent Posts

Search