May 7, 2020 12:00 PM ET
iCrowd Newswire – May 7, 2020
The Latest release features advanced personalization capabilities for greater business user-controlled experimentation with new algorithms and a first-in-the-market real-time streaming catalog API
RichRelevance, the global leader in experience personalization, today announced its latest Spring’20 Release. With this release, retailers and brands can deploy advanced personalization algorithms without dependence on data scientists and IT experts, leading to faster time to market. The spring release is a milestone in the company’s vision to drive revenue growth from personalization strategies with a focus on continuous optimization using a combination of machine-driven and human-controlled experimentation, to improve accuracy and relevance.
RichRelevance now provides unparalleled self-service options to marketers, product managers, and merchandisers to create and deploy new strategies to test new hypotheses, target underserved segments, and provide real-time insights into the performance of these algorithms.
Here are some of the key capabilities in the RichRelevance Spring ’20 Release:
Business User-Driven Strategy Configurations
Configurable strategies enable non-tech users to quickly build, test and iterate new personalization strategies, without having to wait on data science and engineering teams. Users can pick from a library of algorithms (such as viewed together, co-purchase), and then apply a personalization filter (such as shopper’s brand history). New strategies are tested automatically in real-time by the Experience Optimizer ensuing rapid feedback on performance, improving time-to-market dramatically.
Customizable Model Parameters
Similar to building new models, business users want to tweak certain parameters in an existing model to get more accurate results like setting different lookback periods for different models, or suppress occurrence of products that are always bought in a shopping trip.
Unlike several competitive products that are limiting, for example, static windows in lookback periods, RichRelevance customers can change the windows to help better respond to the current situations where demand is fluctuating quite rapidly.
Affinity-biased recommendations
Affinity-biased recommendations are used to score and re-rank the results for every individual on attributes such as brand, category, color, price, promotions and so on, and consider not just purchases, but also actions such as views and products in cart. Marketers can experiment by controlling weights of different attributes, such as color being weighed higher than brand.
This feature has been generating higher attributable sales for RichRelevance’s early adopter retail clients.
Real-Time Catalog Updates
With a Streaming Catalog API, our search solution FIND™ automatically identifies any changes to price and availability of items in the catalog, and updates these attributes in real-time. This is a first in the industry, as most engines are updated only once in a day, leading to obsolete search results.
Marketer-Controlled Site Placements
With the Experience Designer, marketers can now insert placements of individualized recommendations, as well as segment-based content directly on the site, without the need for another tool or IT intervention. This makes it possible to create, preview and launch campaigns on the fly.
Benchmarking Metrics with Industry Pioneers
With the new Benchmark Report, our customers can now measure on personalization metrics such as sales from recommendations and click-thru-rate against peers from their sub-vertical – be it fashion, consumer goods, beauty, B2B or grocery.
RichRelevance also recently announced joining forces with Manthan to consolidate their category-leading businesses to offer a wider martech stack with a customer data platform, lifecycle marketing capabilities, and cross channel marketing orchestration, along with hyper-personalization.
About RichRelevance
RichRelevance is the global leader in Experience Personalization, driving digital growth and brand loyalty for 200 of the world’s largest B2C and B2B brands and retailers including REI, Burberry, LL Bean, CDW, ShopDirect, ATEA, Komplett, Coop.SE and Office Depot. The company leverages advanced AI technologies to bridge the experience gap between marketing and commerce to help digital marketing leaders stage memorable experiences that speak to individuals – at scale, in real-time, and across the customer lifecycle. Headquartered in San Francisco, RichRelevance serves clients in 44 countries from 9 offices around the globe.
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Keywords: Personalization, Personalization Strategies, Customer Data Platform, Recommendations, real-time insights, machine learning, self-service
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RichRelevance Unveils Spring’20 Release: Self-Serve Machine Learning for Power Users, Data Scientists Need not Apply - Reported Times
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