give suggestions, get more sales: how web recommendations ... · of tag lines, creative variants...
TRANSCRIPT
![Page 1: Give Suggestions, Get More Sales: How Web Recommendations ... · of tag lines, creative variants and more. In reality, [it’s]…about making the experience relevant to the consumer.”](https://reader035.vdocuments.us/reader035/viewer/2022070100/600c6df288aff6064f0d8b7e/html5/thumbnails/1.jpg)
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Give Suggestions, Get More Sales: How Web Recommendations Can Drive Online SalesSamantha Krafte, David TaitelbaumApril 4, 2019
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Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
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Agenda
3
1 The Personalization Landscape
2 Overcoming Personalization Challenges
3 Web Recommendations Overview
4 Q & A
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The Personalization Landscape
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The Evolution of Digital Marketing
• Good news: digital marketing works!
• Bad news: evolution of content has been slow
• Batch and Blast has been tried and true
• Volume has increased to maintain performance
• Subscribers are becoming fatigued
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The Evolution of Personalization
• Automated campaigns are the most successful form of personalization
• Personalization = triggering a message based on a subscriber’s actions
• Automated campaigns have extremely low unsubscribe rates
• The one notable exception is Message 1 in a Welcome Series
• Personalization 2.0: rolling out personalized recommendations based on purchase and browse history
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The Evolution of Web Personalization
• Web Personalization gained popularity through Amazon
• Data has indicated it is extremely effective at driving conversions
• The technology is now widely available
• The big question is how robust is the data set you are using to create recommendations
• More data = better personalization = better conversions
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“…35 percent of what consumers purchase on Amazon and 75 percent of what they watch on Netflix come from product recommendations…”
Source: How retailers can keep up with consumers, McKinsey & Company October 2013
Ian MacKenzie, Chris Meyer and Steve Noble
The Rewards of Personalized Content
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Personalization Strategies
• Targeted Marketing is by far the most effective tool when it comes to influencing buyer behavior
• Customized Digital Experiences and Localization-based Marketing are also effective
• Recommendations fit two of these three marketing strategies
• Localization based can be implemented with contacts where you have geographic data like Zip Code or nearest store
Targeted marketing and customized digital experiences are two of the biggest factors in driving conversions.
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Overcoming the Challenges of Personalization
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“Many marketers are still hung up on the notion
that personalization means creating hundreds
of tag lines, creative variants and more. In
reality, [it’s]…about making the experience
relevant to the consumer.”
Source: Why Marketers Struggle with Data-Driven Personalization, eMarketer October 18, 2018
John Douglas, Sr Director of Product
Marketing, Sizmek
Personalization Challenges
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Personalization Challenges
• Data Driven Personalization can be highly effective
• Creating the data models can be extremely complex
• As a result many companies are looking for third party partners who can build out the Recommendations models for them
• The sweet spot is a partner who can do all the heavy lifting on the data side and make it easy for Marketers to implement Data Driven Personalization
Data driven personalization and marketing technology are two of the most difficult tactics for Marketers to contend with
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Web Recommendations Overview
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Where to Place Web Recommendations
• Homepage
• Product Page
• Basket/Cart Page
• Category/Brand Page
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Types of Recommendations
• Recommended For You (purchase & browse history)
• Frequently Bought Together (wisdom of the crowds)
• Bought This, Bought That (wisdom of the crowds)
• Bestselling in Category you Frequently Purchase
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Web Recommendations OverviewThe Product Recommendations Overview includes the total number times item has been recommended.
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Web Recommendations Overview
Product KPIs include Page Views, Quantity Sold and Revenue.
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DEMO
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Q&A
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THANK YOU