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Maxymiser’s Support for Personalization

July 18, 2013

How Maxymiser Creates Segments: This Maxymiser report identifies the customer attributes that have the most impact on conversion rates for specific offers. The Predicted Frequency Distribution shows how many visitors with a specific attribute are expected to view each of the offers. The first column, for example, shows that Offer1-Bath is predicted to be the offer most viewed by Sunday Visitors. The Most Relevant Attribute table shows conversion rates for the highest converting attributes.

How Maxymiser Creates Segments: This Maxymiser report identifies the customer attributes that have the most impact on conversion rates for specific offers. The Predicted Frequency Distribution shows how many visitors with a specific attribute are expected to view each of the offers. The first column, for example, shows that Offer1-Bath is predicted to be the offer most viewed by Sunday Visitors. The Most Relevant Attribute table shows conversion rates for the highest converting attributes.


Maxymiser is a digital marketing suite with solutions for optimization, testing and personalization. Products include MaxTEST, MaxSEGMENT, MaxPREDICT, MaxRECOMMEND, MaxSOCIAL, MaxMOBILE and MaxINSIGHT. These connect across a common UI and platform. The company was founded in 2006. It is headquartered in New York with offices in Chicago, Edinburgh, Dnipropetrovsk, Dusseldorf, London, Munich and San Francisco.

Customer interactions have a variety of contexts, and marketers find tactics must vary also. A customer at the Web site looking for a specific item is best served with great search and recommendations. An aimless customer at the web site might actually find some banners and offers helpful for giving purpose to his browsing. And marketers want to bring customers, typically using emails and ads as tactics for getting attention.

The more integrated the tools are for applying these tactics, the easier it is for marketers to do their jobs and the more consistent the experience is for the customer.

Maxymiser offers two methods for personalizing customer experiences and campaigns: automated behavioral targeting and product recommendations. These rely on Maxymiser’s comprehensive visitor profile, which I cover in another post. LINK

Automated behavioral targeting finds the most effective experience for customers in any context: aimless browsing, directed shopping, mobile, and email. Recommendations deliver the most effective product suggestions to shoppers seeking a goal.

Maxymiser’s automated behavioral targeting determines which customer and behavioral attributes are the most important in predicting results, creates segments, tests various experiences for each segment, and routes visitors to the appropriate experience. Marketers do not have to identify segments, design experiences, test, and optimize. The screenshot above shows results of automated segmentation and optimization.

Marketers can take the helm when they need to. For example, one might want to offer free shipping to customers located nearby. Maxymiser allows its clients to control or influence the customer experience by specifying rules that apply to customer segments and contexts. I reviewed Maxymiser’s UI and customer profile in earlier posts.

As a veteran of past personalization solutions I know that rules quickly multiply and become unruly, which is why automation is so important. It’s also the case that you can’t summon enough hands to manually optimize for the ever-moving target of customer interests. But when marketers need to control the customer experience, they can create rules that will apply narrowly or broadly, across touchpoints and lifecycle.

Maxymiser’s second tool is recommendations, which are based on customers’s interests. Recommendations can be inserted into any experience from any channel, and on any web page. Marketers use recommendations to help browsers and shoppers connect with attractive products, and also make emails and ads more engaging. Maxymiser’s recommendations are based on models that learn and predict visitor interest based on past actions. As with behavioral targeting, recommendations can be controlled, or constrained, by rules. For example, marketers may wish recommendations to be more or less expensive, or in the same category; or recent visitors must see the items viewed during the last session.

A combination of Maxymiser products supports these two personalization methods. The capabilities I’ve described require at least MaxTEST, MaxSEGMENT, MaxPREDICT, and MaxRECOMMEND.

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