The Personalization Spectrum – Match Your Strategy to Your Goals (Part 1)

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Ideas and Strategies for Real-Time Personalization
The Personalization Spectrum – Match Your Strategy to Your Goals (Part 1)

November 12, 2015 by

Personalization can take many forms, from presenting a welcome message based on the visitor’s source to providing a specific product recommendation based on a shopper’s unique tastes. While some types of personalization are basic, others are more advanced, but both can deliver significant value to the customer and to the business. The key is matching the strategy to the goal.

Just like a rainbow of colors, personalization can vary greatly across a spectrum. Sure, you can (and probably should) start with simple personalizations on your website and work your way up to more complex implementations; however, don’t leave one type behind for another. Develop and use the full spectrum of options for different situations. Whether for anonymous visitors or logged-in users, personalization is a proven, effective way to engage your audience and maximize marketing and customer experience ROI.

In this two-part blog series, I take a look at the different types of personalization across the spectrum, using B2C Retail and B2B Technology company examples throughout. In this first article, I examine two different types of rule-based personalization.  

Personalization Spectrum Graphic v111115 for blog

The Personalization Spectrum

Rule-based personalization

Rule-based personalization allows for manual creation and manipulation of business rules that are applied against groups or segments of visitors, based on a variety of information you can collect about them.

Broad segments – such as those based on geographic location, industry, referring source, visit number or pages viewed – can be used to divide your visitor base into say, four distinct segments and personalize accordingly. This also allows you to test site design and content elements, such as which hero image to use with different regions, or different content types based on the visitor’s industry. For example, an online apparel retailer can personalize by geo-location, showing everyone in a certain region the clothing and footwear appropriate for their climate. Or a B2B site that wants to help first-time visitors do their job better and faster would recognize the customer’s business type and orient the content they see around industry-specific case studies.

In other cases you’ll want to use more narrow segments, maybe several dozen. This can be done by multiplying your basic segments into many more and/or layering on the stage of the visitor’s relationship with your brand (e.g., first-time visitor or repeat purchaser) and their persona (e.g., whether they are a gift shopper, a business traveler or a website developer). For instance, the clothing merchant would recognize a repeat visitor from a state like Florida and point them to the “sun-lovers” sale merchandise. The B2B tech company site would recognize prospects that have already explored multiple pages of particular products, such as network servers, and promote a relevant white paper.  

Conclusion

Rule-based personalization techniques work well for communicating to key groups and running numerous campaigns, and the insights gleaned from testing different treatments and logic can be used to optimize your results. If you want to pursue more dynamic 1:1 personalization, where the content or experience varies from one visitor to the next, you need to employ an automated personalization approach. Read about algorithmic personalization in Part 2.

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