Listen to, Learn from and Leverage the Voice of the Customer

According to the recent report from eMarketer entitled Customer Product Reviews: The Next Generation, customer product reviews have garnered an increased level of trust amongst the Internet populace in part because retailers and brands have become more enlightened in their attitude toward displaying negative customer feedback on their websites. This has driven readership rates for customer product reviews to 92% of all Internet users, as well as existing and planned implementation rates to 84% of online retailers. This broader adoption on both sides of the ecommerce transaction has set up this form of user-generated content (UGC) to be harnessed in ways that transcend their original purpose.

Towards this vision, the eMarketer report advises that “the most sophisticated brands derive benefits from leveraging the content of reviews in marketing copy, integrating it with social networks, incorporating it into search campaigns and employing it to improve product design and innovation.”

At Covario, we classify customer product reviews under the aegis of the “Voice of the Customer” (VOC), which encompasses all user-generated content, as well as search query and search behavior data. Over the past few years, we have been mining and analyzing VOC data to derive the types of benefits for our clients that the most sophisticated brands on which the eMarketer report describes. Examples of these strategies include syndicating customer reviews to the search engines; crowd-sourcing the task of keyword discovery to customers; mining customer search interaction with variations of ad copy and incorporating the best-performing content into different advertising media; and harnessing VOC to amplify search engine optimization through self-learning technology.

Actionable Insight 1:

Amplify the Voices of eCommerce Customers through UGC- SEO
Covario partnered with Bazaarvoice, the leading product ratings and reviews platform provider, to develop a solution for a shared client, Cabela’s, that would allow search engines to more easily crawl, index and serve customer reviews on Cabela’s tens of thousands of product pages. In this way, Cabela’s essentially crowd-sourced the task of keyword discovery to their customers, while turning customer product reviews into brand assets by syndicating them to the search engines. The results that this partnership achieved for Cabela’s are documented in this case study.

Actionable Insight 2:

Use Search to Increase Cross-Channel Brand Interaction
Intel wanted to change their image from a high-tech maker of really fast and powerful technology ingredients to the essential provider of the consumer’s future experiences. That’s a huge undertaking. Their ad agency came up with a brilliant concept – “Sponsors of Tomorrow.” But for some reason, the messaging wasn’t resonating with consumers when the campaign was first launched. The Covario Media Operations team manages Intel’s search marketing program – they mined search data and discovered that a slight tweak to the messaging increased by an order of magnitude consumer interaction with the new brand positioning. Intel then used this information to revise the messaging in broadcast media and public relations. This approach proved so effective that Intel now uses Covario-powered paid search programs to rapidly deploy and test new marketing messages in order to leverage strong performers across all marketing channels. The results are documented in this case study.

Actionable Insight 3:

Harness VOC to Automatically Amplify SEO
Companies with websites containing thousands upon thousands of pages know that 90% of online revenue is generated by 10% of the pages. So investing time and resources in optimizing the 90% of pages that generate only 10% of the revenue is a losing proposition, because taken on an individual basis, these pages offer negative return on investment. However, taken collectively, they offer the highest combined opportunity for revenue growth. So Covario will soon be launching a product that scales this endeavor by crowd-sourcing the keyword discovery task to customers who actually found these pages and that automatically optimizes page content based on these referring search queries. We call this smart, self-learning automation technology “Algorithmic SEO.”

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