Customers.com Technologies

How, When & Where Customers Want Personalized Recommendations

By Patty Seybold

As technologies evolve, so do customers’ needs and desires. In the 30+ years that we’ve been chronicling customer-critical technologies, we’ve witnessed an amazing shift in the degree to which marketers, merchandisers, and advertisers can target offers and deliver truly personalized recommendations.

Personalized Recommendations Often Delight! Today, there are amazing (and affordable) technology services that e-marketers can use to personalize the recommendations that we see on their web pages, in the emails they send us, in mobile apps we use, in the SMS messages we receive, and at the point of sale. When well-tuned, these personalized recommendation engines provide amazingly relevant suggestions, offers, and promotions.

When Do You Want Personalized Recommendations. In general, we’ve found that customers react positively to highly relevant and personalized ads. But hate it when they receive irrelevant pop ups at inopportune times. The “when” part of the equation is relatively easy. When we’re looking, shopping, and searching, we’re open to personalized, relevant recommendations. But when we’re engaged in another task, we hate being bothered with offers and recommendations, no matter how personalized they are. But there are times when it’s OK to recommend things to us—e.g., when we’re relaxing, browsing, hanging out, at leisure.

Adobe Recommendations Delivers Personalized Actionable Content

By Sue Aldrich

About a quarter of Adobe’s revenues ($1 billion out of $4 billion) come from its digital marketing solutions. Adobe’s Digital Marketing Suite provides digital marketers with multi-channel, cross-lifecycle marketing and customer experience management tools. The chances are that if you’ve been on the Web or if you’ve used a mobile app today, you’ve already received one or more Adobe-based personalized recommendations.

Personalized cross-device marketing is strategic to Adobe. In November 2011, Adobe announced that it was re-focusing on digital media and digital marketing.

Adobe’s Digital Media Strategy
Adobe’s digital media strategy helps content creators develop and deliver rich content to run on any digital device. As part of that strategy, Adobe has shifted away from Flash and embraced HTML5 and launched the Adobe Creative Cloud for SaaS-provisioning of all the relevant tools that digital designers and developers need, as well as project rooms for sharing work in progress.

Adobe’s Digital Marketing Strategy
Adobe’s digital marketing strategy helps marketers maximize the impact of their digital experiences across devices and media types throughout the entire customer lifecycle. Key to that strategy are the rich tools that Adobe now has for tracking and monitoring customer experience across devices, and for delivery of personalized actionable content, e.g., recommendations to users when and where they will most value them.

This week, Sue Aldrich provides an in-depth review of two of Adobe’s strategic solutions for delivering personalized recommendations: Adobe Recommendations and AdobeTest&Target.

Need Personalized Recommendations? Peerius May Be Your Solution

By Sue Aldrich

If you sell products and/or deliver content online or via mobile phone, there’s usually a big benefit to being able to provide personalized recommendations tailored to each site visitor. Automated personalized recommendations can double or quadruple the click-through rate on your site, increase the number of products each customer buys, and increase the frequency with which they return to buy again. For the content owner—whether a merchant selling products, a publisher presenting articles, or a marketer presenting offers—recommendation technology means delivering the most attractive item in those few seconds before you lose your audience’s attention.

Web site owners worldwide have yearned for recommendations ever since Amazon started telling us that “people who bought this also bought that” and today tell us “52 percent of people who looked at this bought that; 26 percent bought this other thing.” A decade ago marketers had to spend a great deal to implement recommendations on their sites. Today, recommendation engines can be had for some hundreds of dollars a month and can be implemented in a few days. Don’t you just love SaaS?

Applying Best Practices in Targeted Merchandising

It’s now possible to provide really specific recommendations and offers to customers visiting your web sites and/or landing pages. Cloud-based services abound that will let you get up and running in record time with little upfront investment. If you know a lot about the people visiting your site, you can provide exquisitely personalized recommendations based on their transaction history and profile information and social media activity. But, if the visitor appears anonymously, and hasn’t registered on your site and/or hasn’t logged in, you can’t provide personalized recommendations, but you can provide targeted ones—based on a lot of information that you can infer about that person. This is the art of targeted merchandising.

Targeted merchandising selects content (including products and offers) for consumers based on traits such as consumer context or behavior, or based on rules set by merchandisers. The targeted consumer is anonymous. The consumer is most often identified by web browser cookies and an associated identification number. Without registration, it is unlikely the profile will contain user information such as name and address, so consumer anonymity is usually retained.

Tuning targeted merchandising correctly for your business and your customers is tricky. One online retailer may discover that their customers respond best when recommendations are place to the right; another finds that putting them on the left yields better results. How many recommendations are too many for your customers?

We’ve researched and come up with best practices that you can apply to your targeted merchandising efforts, whatever technology you are using: we bring you three best practices concepts and eight principles for applying them that are solid and time tested.

Success with Best Practices for Targeted Merchandising

Unlocking the Power of Recommendation Engines
By Susan E. Aldrich, Senior Consultant/Analyst, Patricia Seybold Group, October 27, 2011

Revisiting the Requirements for Evaluating Recommendation Technology

Once again, our expert on merchandising and recommendations, Sue Aldrich, looks at the decisions and criteria you should consider before implementing a recommendations solution. As she advises, choosing a vendor wisely is always better than choosing often. And to aid you in that effort, she offers insights into how recommendations are crucial to effective targeting and personalization, how recommendations are best used, and what the requirements are for the marketers, merchandisers, editors, business analysts and other business people managing the recommendations, as well as for the end-customers who receive the recommendations.

As we move forward, Sue will use this updated framework for evaluating recommendation solutions< as she analyzes the major offerings in the market.

You can use this framework to gain an overview of the functionality that makes a difference in the quality of the personalized and targeted recommendations you deliver by email, on your web site, and on mobile devices. It’s also an extremely valuable tool for those of you evaluating recommendation solutions on your own so that you do choose wisely.

Recommendation Evaluation Framework, Version 2
Evaluating Solutions for Personalization and Recommendations
By Susan E. Aldrich, Sr. VP and Sr. Consultant, September 22, 2011

Recommendation Engines' Quarterly Update

Whether you are responsible for customer experience, online strategy, mobile strategy, marketing, or another customer-impacting part of your organization, you're no doubt aware of some of the ways in which recommendation technology is used to personalize content and offers. There are many suppliers of recommendation solutions to choose from. Susan Aldrich has written detailed reviews of many of these offerings. She follows the top North American and European players in this growing market.

The best way we've found to provide an overview of who’s doing what in a highly competitive marketspace is to provide periodic snapshots of all of the players in the form of a market recap. Who are the key players? What industries do they serve? Who are their customers? What capabilities do they offer? How are they doing? What strategic changes have them made recently? Here's our 2011 Recap covering eight of the top players in this space:

• Adobe
• Avail
• Baynote
• iGoDigital
• Locayta
• MyBuys
• PredictiveIntent
• Strands

What's particularly interesting about all of these players is that their software is typically sold as a service you can integrate into your systems relatively quickly. The results are usually quick, easy to see, and easy to measure, typically resulting in a triple-digit uplift in conversion rates within a few weeks.

Recommendation Solution Market Recap: 1Q2011
Mobile, UI, and Algorithm Enhancements Lead the Product News
By Susan E. Aldrich, Senior VP, and Charles R. Plaisted, Contributing Editor, August 4, 2011

SaaS Has Shaped the Leading Recommendations Solutions

By Ronni Marshak

In her insightful rating of what she considers to be the top five recommendations solutions on the market today, Sue Aldrich evaluates Avail, Baynote, Certona, Omniture, and RichRelevance in the following categories:

• Recommendation efficacy

• Geography, language, and target markets

• Recommendation types and structures

• Marketer’s control over recommendations

• Support in applying recommendations

• Company and product viability

But she points out that for all the vendors, SaaS has shaped the solutions by driving the focus towards business benefits and support for business goals, minimizing the importance of product maturity. As she states, “With SaaS, the burden of managing the reliability and availability of the service doesn’t fall on your shoulders. Bug fixes are instantaneous; they don’t require your efforts in distribution and installation. For recommendations solutions delivered via SaaS, maturity isn’t so much a matter of reliability as feature richness. We don’t see a downside in choosing a young solution if it contains the features and the client care that you need. We’ve watched these companies make major enhancements in just the past 12 months via continuous improvement unhampered by the packaging and release cycles of on-premise solutions.”

Thus, the SaaS model is goodness for Recommendations customers, who are not technologist, but marketers. Sue states, “The SaaS model allows vendors to approach business people (typically marketing executives), rather than IT, to make the sale. The focus of the sales conversation is business benefits and support for business people; technology and support for IT come into the discussion much later, often not until after the marketing team

has made its decision.” This allows the people who will be using the solutions to improve sales conversions to focus on the other features each of these leaders offer to select the product that is most appropriate for them and their customer base.

Read Sue's analysis:

Comparative Rating of Five Recommendations Solutions

Analysis of Relative Merits of Avail, Baynote, Certona, Omniture, and RichRelevance
By Susan E. Aldrich, Sr. VP and Sr. Consultant, March 31, 2011

Aldrich Review of Certona Resonance Recommendations

Last week, we published the sixth evaluation of a recommendation engine, product, or service. You can use these engines to improve both the sales effectiveness and the personalized relevance of the offers you make to customers who visit your Web site, and/or with whom you interact via email. Many of these offerings, like Certona's Resonance, are SaaS offerings. So they're low overhead and easy to integrate. You see results quickly.

Susan Aldrich has evaluated Avail, Baynote, Loomia, Omniture (from Adobe), RichRelevance, and, last week, she provides an in-depth evaluation of Certona’s Resonance. All of these evaluations are compared against Sue’s Recommendation Engine Evaluation Framework—a framework you can use to do your own evaluations.

You'll find the Resonance Recommendations service running on over 250 Web sites, including Guess, Lillian Vernon, Personal Creations, Petco, Redcats USA, and Staples.

Certona Resonance Recommendations
Automated Optimization Balanced with Granular Control
By Susan E. Aldrich, Sr. VP and Sr. Consultant, September 30, 2010