Beginning Predictive Personalization for Ecommerce

Predictive personalization in eCommerce (and multi-channel retail) refers to how a user’s experience on a website is personalized using predictive technology, machine learning (ML) and artificial intelligence (AI).

The rapid evolution of AI has resulted in some powerful personalization tools for online retail. It allows us to pull data from our own customers, social media, market research and more.

This data can be used to identify trends or fill in the blanks of the demographics we don’t know. It can inspire new ideas, innovation, or even new products that consumers are sure to love. Accenture predicts personalization could increase profitability by as much as 38 percent by 2035.

Ecommerce Examples include:

  • Product recommendations
  • Personalized homepage banners
  • Pop-ups triggered by visitor’s actions
  • Personalized product recommendations
  • Personalized ads and marketing content in emails
  • Predictive autoresponders, which are a special type of an autoresponder that not only includes content but also predicts the content that is more likely to convert.
  • Dynamic pricing algorithms

A predictive personalization engine is able to help even the smallest online retailers to understand patterns in their data. For it to work, you need data points that allow you to predict who your target customer is, what they’re concerned about and ultimately, what will make them purchase. That information can come from their behaviour on your website, or the behaviour of other visitors with a similar consumer profile.

Once you know which predictive results you’re looking for, AI can identify data patterns that indicate who is most likely to make a purchase. You’ll customize and analyze and customize some more, as you drill down into engagement patterns and tease out your specific products. From there, you can automate product recommendations with the best chance of converting, just like Amazon or Netflix.

AI-driven Predictive Personalization Ecommerce Examples

Tools & Teams

As you’ve probably guessed, there is a perpetual learning curve involved and much of it will be best left to data scientists or other specialists, unless you intend to learn it yourself. Either way, you’ll need to start building a team with more than the skill set required. They’ll also need to have a passion for data analysis and the instincts to know how best to use it for eCommerce.

Evaluate AI-driven personalization tools by:

  • Predictive competencies
  • Easy-to-use interface
  • Reporting capabilities
  • Ease of implementation

BigCommerce offers this quick checklist on how to begin using predictive personalization for eCommerce:

  • Start small and grow at your own pace. Don’t worry about auditing the organization and hiring your first C-level AI leader out of the gate.
  • Find a good partner who can take you from data collection through to a well-defined strategy, and then into action.
  • Learn from that partner to build your own competency over time.

Predictive Personalization is Becoming Standard

Like many sales & marketing strategies, predictive personalization is being facilitated by simplified automation tools and services that make it available to any size business. Consequently, it is becoming necessary to use these tactics, or risk being left behind by your competitors.

“Companies are moving at a fast pace toward data-driven automation and machine learning in practice, in strategic and targeted parts of the customer journey,” Elizabeth Gallagher, Chief Revenue Officer at Lineate told MarTech Advisor. “I believe, therefore, that more brands will be getting personalization right at the most important parts of the funnel, and will see the impact of this in conversions and revenue.”

How to Nail it With Predictive Personalization

The following infographic summarizes some of the above personalization pointers.

Predictive Personalization Infographic

Provided by Perzonalization

??? Are you using predictive personalization to optimize eCommerce sales? Please share your questions or experience in the comments below.

You may also be interested in reading:
Ecommerce Report: Customer Experience Can Make or Break You
2020 Multi-Source Report: The Canadian Online Shopper
Tap Into the Exploding Canadian eCommerce Market

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Assistant Editor at | Website | + posts

Marie has an M.Sc. in Marketing and a certificate from the Ryerson Digital Media program. She's enrolled in one course or another most of the time and is always in the middle of a new business book (or three). Marie enjoys writing, traveling and volunteering at local events & trade shows.

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