Bring personalization into omnichannel today

We are at the beginning of a significant journey to bring digital capabilities to the in-store environment and vice versa. Personalization should be a large component of this journey. Over the last couple of years, some retailers have deployed interesting omnichannel applications. Examples are those that allow consumers to check inventory or locate items in stores (Best Buy and Target respectively) or manage loyalty (Guess and Sephora). Also, some vendors have launched mobile shopping applications (like Shopkick, RetailMeNot or ShopSavvy). But still, very few of these initiatives are truly personalized.

Yet, the use cases and technology for personalization in omnichannel have never been more viable, and the imperative to get started more apparent.

Omnichannel personalization can be done at two levels. The first consists of pulling together consumer data from different channels to create a comprehensive profile of each consumer (omnichannel data). The second consists of deploying personalization across multiple channels (omnichannel touchpoints).

When these two levels are combined, the following is possible:

  • Personalizing a single channel using omnichannel data
  • Personalizing multiple touchpoints using single channel data
  • Personalizing multiple touchpoints using omnichannel data

One example of personalizing a single channel using omnichannel data is what one of our customers in the upscale department store category did. By merging online intent data with store POS data and applying it to onsite recommendations, they were able to drive a 2.1% lift in website sales (compared to recommendations that utilized only online intent data).

One example of personalizing multiple touchpoints using single channel data is what Monsoon Accessorize, a UK high street apparel leader is doing. They use online intent data to personalize their onsite, in-store and mobile channels. The store solution integrates RichRelevance, Micros and YESPay to allow in-store sales associates to locate and sell a product anywhere in the UK supply chain and show shoppers an extended and personalized product range on their tablets.

Stores utilizing the solution see a 133% improvement in AOV, an increase in one item per check out basket, a 2% reduction in returns and improved customer experience ratings.

Delivering this type of access to rapid innovation is the reason we built our infrastructure and SOA (service-oriented architecture) platform for API-based personalization services. We call this platform Build™ and it provides our retail customers the intent data and functionality needed to bring offline data (like POS) from stores and call centers to the digital experience. This includes real-time data ingestion and export, model import and building, consumer profiles, product and content co-occurrence, segmentation and consumer ID matching. With this functionality, retailers can quickly explore, experiment and build personalization capabilities using an iterative cloud-based approach that doesn’t require data scientists or large investments in infrastructure.

This ability to rapidly innovate to build superior customer experiences through personalization is not limited to omnichannel retailers, it applies to pureplay etailers as well.
In the US, long-time customer was able to test an age-old theory on the impact of recommending similar products based on the number of common attributes. Using Build, it developed and implemented a custom personalization algorithm that leveraged the intersection of multiple attributes and measured its performance against the existing set of pre-built RichRelevance algorithms. Not only was the speed with which moved from concept to deployment to production unprecedented, the new “similar products” algorithm became one of’s best performing strategies, generating about $5 per click.

Our expectation is that Build will become the personalization platform of choice not only for our retail customers, but also for many consumer-facing applications developed by multiple vendors in the space. Build has a light footprint, rich functionality, and is a super performing platform that can sit underneath Hybris, Demandware, Responsys, Exact Target, SLI Systems, HookLogic, Olapic, LivePerson, CrowdTwist and other applications to enable omnichannel personalization via APIs and services.

So make today your Day 1 and commit to omnichannel personalization. Analyze your current and/or future omnichannel applications, determine what different data sources can be used for personalization, decide how many channels you want to enable and then leverage Build to create a superior omnichannel customer experience. We’re here to partner with you each step of the way.

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This post was written by Eduardo Sanchez

ABOUT Eduardo Sanchez
A global technology veteran, Eduardo Sanchez brings more than 25 years of strategic and technical leadership in data, cloud, mobile, social and enterprise technologies to RichRelevance. Most recently, he served as Executive Vice President, Strategic Development at MicroStrategy, where he was an early member of the leadership team and played a critical role in the development of the company, spearheading its foray into new lines of business and international expansion. Previously, he was COO at Paris-based Cartesis (acquired by Business Objects in 2007) and EVP of Global Sales at Lawson Software (acquired by Infor in 2011).As CEO, Eduardo is responsible for the daily operation of the company – including engineering, data science, cloud infrastructure, product management, marketing, sales, services and partnerships – and will play a key role in driving continued growth and global expansion as RichRelevance evolves its personalization for commerce across its customer and prospect base of leading retailers and brands.Eduardo received a B.S. in Electrical Engineering from the University of La Plata in Argentina and a M.S. in Systems Engineering from George Mason University in Virginia.
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