Miinto uses RichRelevance Personalization to Drive 47% Growth for Lockdown affected Independent Boutiques

One of Europe’s Fastest Growing Fashion Marketplaces offers a digital lifeline to thousands of boutique stores hit by closures, bucks the trend with growth in sales for 1H 2020

15 September 2020, Copenhagen, DenmarkMiinto, a leading Scandinavian fashion marketplace operating across Europe, has tripled its business in the last three years and has experienced a surge of +500% in inquiries from independent retail stores offering high-quality fashion brands since March. With a sharp decline in-store footfalls, and consumers turning to online shopping for fashion needs, regional retailers are finding online marketplaces like Miinto to be a real lifesaver.

Miinto partners with over 2000 retailers to showcase more than 5000 brands and over 500,000 active products, and offers superior customer experience to shoppers. A big reason for Miinto’s digital success has been their investment in digital personalization, AI, and their ability to seamlessly tune digital strategy, test and experiment winning experiences at great speed. 

Having a vast and constantly changing product catalog, Miinto has a unique set of challenges. They rely on the RichRelevance personalization platform to help consumers find relevant products from thousands of pages of products. 

“RichRelevance has been a gamechanger for Miinto by allowing us to significantly improve our customer experience, making it personal and relevant to every single user that visits our website. We’re working hand-in-hand with RichRelevance on a daily basis to use all available technologies, and even develop new ones, to constantly optimize our onsite experience and make sure that we present the right products to the right customers at the right time”, said Paloma Truong, Head of Customer Experience at Miinto. 

Malthe Cederborg, Group CMO at Miinto believes strongly in a significant market opportunity for brand-led independent retailers worldwide. “Miinto’s business model offers retail store partners that meet high standards in product, availability, and logistics, a simple yet compelling model to take their business online to an international market that spans Scandinavia and the rest of Europe. To get started, all they need is a product catalogue and an integration with the Miinto platform that we can help with. We welcome regional fashion specialists to tap a large international consumer base by partnering with Miinto”, said Malthe.

Miinto, with its sales during the last year of almost EUR 100M, is a digital-first business and a role model for other industries to follow. Agility, scale and customer experience are all being shaped and managed by technology, even as business environments have remained dynamic and evolving. Miinto realized a 19.4% higher revenue with RichRelevance personalization, compared to their previous technology.

Commenting on the role of personalization technology in Miinto’s success, Thomas Hakansson, Director of Customer Success at RichRelevance Europe said, “Miinto is an innovator – be it their business model, or their definition of customer experience. They have passionately developed a world-class digital marketplace for fashion. Their use of RichRelevance Personalization has evolved from basic site search and recommendations, to include Xen AI powered real-time decisions with customer context and dynamic inventory, and is a strategic weapon to drive revenue growth. We are delighted to work with marketplaces with such unique needs.”

RichRelevance recently announced the next generation of product recommendations as part of their personalization cloud, DeepRecs

For more information on the story, contact respective company media contacts, as follows:

 

Miinto
Malthe Cederborg, Group CMO
mac@miinto.com
+45 2670 8281

 

RichRelevance
Thomas Hakansson
info@richrelevance.com
+46 7303 06634

 

About RichRelevance

RichRelevance is the global leader in Digital Customer Experience Personalization, driving digital growth and brand loyalty for 200 of the world’s largest B2C and B2B brands and retailers including REI, Walmart, Burberry, CDW, ShopDirect, ATEA, Komplett and Coop.SE. 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.

RichRelevance Launches ‘Deep Recommendations’: The Next Generation of Advanced Commerce Personalization

An industry first solution using deep learning AI that generates up to 80% higher attributable sales from product recommendations

SAN FRANCISCOSept. 1, 2020 /PRNewswire/ — RichRelevance, a leader in experience personalization, today announced the launch of first-of-its-kind ‘Deep Recommendations’, a set of advanced personalization technologies that, unlike traditional recommender engines, does not need historical events and behavioral data to immediately generate relevant product recommendations.

The new approach solves two problems: (a) it removes constraints associated with traditional recommendations which don’t work for retailers and brands with sparse data – seasonal products, fast changing catalogs and long tail products, and (b) it helps product discovery by catching user’s preferences through a product’s visual features and textual description.

With Deep Recommendations, retailers and brands that regularly introduce new products can expose shoppers to these new products instantly. In addition, categories such as fashion and home furnishings where shoppers look for ‘visually similar’ or ‘visually complementary’ products can break through the clutter with highly relevant and high conversion visual AI based recommendations.

RichRelevance Deep Recommendations are enabled by Xen AI, the most advanced machine learning engine in the space and the only one with composite deep learning, a industry first approach that blends all known data and decisions to predict the next best experience.

Xen AI extracts and combines feature vectors (the “DNA”) found in product text descriptions and catalog images, behavioral data, derived affinities and stated preferences and matches in real-time with shopper intent to create highly relevant, high-conversion recommendations. This helps your customers not only get what they are initially looking for, but also inspires them to discover contextual recommendations to fulfill their needs across their shopping journey.

Experience Optimizer (XO), the patented decisioning layer of Xen AI, is used to continuously experiment in order to  predict the most favorable outcomes by mixing and matching traditional strategies, personalized strategies and now, deep learning strategies.

Results from its over 30 early adopters and customers have revealed spectacular results, with Xen AI Deep Recommendations creating an average lift of 40% in engagement and 80% higher attributable sales, in comparison to standard recommendations prevalent in the industry today.

“We instinctively knew that using visual aspects of a product for recommendations is effective in fashion and lifestyle business – it’s much closer to the expertise of our merchandisers. I am excited with early results – our engagement is up 40% over our merchandising rules, and revenue per 1000 impressions has increased by 19%, compared to the other recommendation models,” said Sylvain Lys, Head of Omnichannel Customer Experience at PromodFrance.

“Deep recommendations is our top performing strategy right now, and is delivering average attributable sales of Eur 10.68 per click. The results are scarily good. Without RichRelevance, these innovative AI technologies wouldn’t have differentiated us, and helped us grow,” said Anton Paasi, Head of Ecommerce, Verkkokauppa.com, a leading Finnish online retailer.

“Deep Recommendations replicate how store assistants help a shopper with their purchases, by interpreting their likes through a combination of language cues and visual attributes revealed in the shopping journey, along with an understanding of their past affinities to a brand or price point. The relevancy will continuously improve as deep learning algorithms gather more volumes, and Xen AI learns from how users interact with these recommendations,” said Mark Buckallew,  VP, Product Management at RichRelevance.

RichRelevance was recently named a leader in Gartner’s 2020 Magic Quadrant for Personalization Engines.

To learn how RichRelevance Deep Recommendations work, and to read more client successes, visit richrelevance.com/deeprecs.

About RichRelevance

RichRelevance is the global leader in Digital Customer Experience Personalization, driving digital growth and brand loyalty for 200 of the world’s largest B2C and B2B brands and retailers including REI, Walmart, Burberry, CDW, ShopDirect, ATEA, Komplett and Coop.SE. 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.

For Press and Media Inquiries: info@richrelevance.com

7 ways Personalization is Evolving

The 2020 Gartner Magic Quadrant for Personalization Engines highlights the state of personalization technologies today, and in our opinion, offers great insights to buyers. At RichRelevance, we restlessly observe, anticipate and invest in a larger backdrop of unfolding changes, when it comes to businesses driving greater results from personalization. 

The personalization market is in a state of flux today, and could see rapid changes in a short timeframe with the merging of multiple technologies that will create a shift and set new benchmarks for organizations to follow. Thankfully, we’re ahead of the curve, and we’re happy to share from our vantage point.

The expectations from personalized customer experiences are becoming more complex and demanding every year. What was once communications based on simple product recommendations based on historical engagement, has now evolved to deeper recognition of intent and the ability to respond in real time. AI-powered algorithms, decision sciences, and the great computing power required to process millions of customer contexts, have created a new age for personalization.

Let’s look at what’s changing and what you should expect when crafting your customer experience strategy.

Uniquely orchestrating moments in cross-channel customer experience – insights that drive personalization are often available for one aspect of a channel, like recommendations on the commerce site, and often are unable to recognize nuances across interactions and channels. It is now very evident that customers use a combination of channels for different needs. Next-gen personalization technology has the ability to unify customer data from across channels, and interaction sources (such as content, recommendations, search query, email, call center) and generate real-time decisions  that help brands and retailers tailor their strategy uniquely for every individual.

Optimizing for the behavioral model of the customer journey – there is a need to recognize journeys not as a series of customer touchpoints, but a combination of customer intents that led them through the lifecycle. A behavioral model rather than a transactional model of the customer journey is essential to crafting winning customer engagement and journey optimization strategies.

Strategy configurations in personalization playbooks  – Personalization can work better if it is part of a broader customer and marketing strategy. And strategies define specific frameworks for customer engagement to create the right results. Model configurations built into the experience orchestration can drive specific outcomes the business desires or designs (be it conversion, engagement or bigger basket sizes). This also empowers marketers in executing and tailoring strategies like acquisition, cross-selling, growing user base, finding new segments and so on.

Creating richer, multi-dimensional customer contexts – advanced personalization critically relies on an advanced data strategy. Generating deeper insights requires unifying and managing a growing number of customer data points, presently changing or evolving information, relationships with other dimensions (like product, channel, brand, price, availability, previous experiences, householding) and a growing number of secondary attributes (such as color, ingredients, newness, health preferences) in the engagement lifecycle. Advanced customer data platforms bring together a greater variety of data for richer contexts. They also offer the ability to handle multiple data workloads for different analytical needs, like data lake architecture for pattern recognition, streaming data architecture for real-time processing as well as, and MPP architecture for complex decisioning are key to advanced personalization technology.

Understanding deeper relationships with product and brand experience – personalization models built to complete a transaction may focus on product attributes, price, and availability. Behavioral models that uncover customer affinities do far more in uncovering the customer’s profile, answering why they buy what they buy. Strategic personalization recognizes that brands and retailers need to increase their engagement and lifetime value with customers.

Combining the digital interactions for total personalization – moving beyond a fragmented approach, businesses that orchestrate a unified personalization strategy across multiple dimensions that impact the digital experience – like content, search, recommendations, product etc – are more likely to see success, because they create a greater impact together, than as isolated experiences. To make this happen, an evolved data strategy and an algorithmic decisioning architecture is essential.

Using algorithmic testing and predictive optimization – recognizing that customers do not always interact with a specific intent in mind, and that they like to discover or appreciate suggestions in their interaction, is a growing concern with personalization strategy. Oftentimes, personalization that fails to identify if the user is in ‘exploring’ or ‘buying’ mode can kill their experience. Algorithmic testing and optimization capabilities can detect the nature of the interaction early on and drive the necessary strategy to engage the customer. It’s important, however, to complement machine-driven scalability with human-controlled experimentation that provides guide rails for tuning strategy and outcomes (for example in merchandising).

While the Gartner MQ may be constrained by what the market offers today, at RichRelevance, we strive to push technology forward, at the speed of the consumer. We see early adopters raising the bar and moving to advanced personalization. It may be time for the larger market to rethink and upgrade. You can start by reaching out to me at bhavna.sachar@richrelevance.com.

RichRelevance Once Again Named a Leader in the Gartner Magic Quadrant for Personalization Engines

2020 report scored RichRelevance highly on marketing features such as predictive journey optimization, real-time streaming architecture, data science advancements, and strategy controlled marketing orchestration, powered by Xen AI

SAN FRANCISCOJuly 14, 2020 /PRNewswire/ — RichRelevance, the global leader in omnichannel experience personalization is named a ‘Leader’ in the 2020 Gartner Magic Quadrant for Personalization Engines[1] for the second year in a row.

Gartner evaluated 13 vendors in the benchmark research and industry guide on providers of Personalization and placed RichRelevance in the leader’s quadrant, based on Completeness of Vision and Ability to Execute.

The report highlighted RichRelevance’s strengths in data and analytics including a real-time streaming architecture and data science workbench for richer customer profiles and deeper shopping context, and the platform’s ability to offer greater business user controls in cross-selling recommendations, and predictive journey optimization using AI.

The report also cited RichRelevance’s joint go-to-market with Manthan Software, which enables RichRelevance’s platform to extend to new personalization use cases and industry verticals.

“Being recognized by Gartner for the second time is quite an honor. We’re consistently pushing the boundaries of innovation for our customers, improving the omnichannel experience for greater commerce and marketing outcomes. With Manthan Software, we’re ushering in a new era of algorithmic customer experience for our clients, where we seamlessly integrate data, decisioning and delivery to provide the most comprehensive stack of advanced personalization technology in the market today,” said Sarath Jarugula, CEO at RichRelevance.

“Hyper-personalization in RichRelevance, now with Manthan, goes beyond simple rules-driven engagement and combines rich, cross-channel behavioral profiles across digital and stores, real-time context, machine learning and orchestration across channels to execute omnichannel personalization,” said Raj Badarinath, CMO at RichRelevance, “This offers Retailers and Brands a real choice to break free of the Stockholm syndrome induced by the large marketing cloud vendors and the Russian roulette of the single use case startups.”

Learn more at richrelevance.com/gartner.

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, 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.

Gartner Disclaimer

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, express or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

[1] Gartner, Inc., Magic Quadrant for Personalization Engines, Jennifer PolkClaire Tassin and Jason McNellisJuly 13, 2020.

For Press and Media Inquiries: Info@richrelevance.com

SPRING ‘20 RELEASE

BOLSTERING HYPER-PERSONALIZATION

“Make it all about me” is what we expect as consumers. No wonder then that personalization was voted marketing word of the year in 2019. It’s gratifying to note that personalization leaders are driving tangible revenue growth and more efficient marketing spend. However, only 15 percent of CMOs believe that their company is on the right track with personalization.

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RichRelevance Unveils Spring’20 Release: Self-Serve Machine Learning for Power Users, Data Scientists Need not Apply

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 

San Francisco, California – May 7, 2020 – RichRelevance, the global leader in experience personalization, today announced their 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.

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RichRelevance Announces Changes in Executive Leadership Team

Promotes Seasoned Executives Sarath Jarugula to President & CEO, Raj Badarinath to CMO 

San Francisco, CA – May 04, 2020 RichRelevance, the global leader in Experience Personalization, today announced that as part of succession planning, Sarath Jarugula will become the President & Chief Executive Officer (CEO), and Raj Badarinath will become the Chief Marketing Officer (CMO) effective immediately.

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RichRelevance Announces Plans to Consolidate Business with Manthan Software

Creates Industry-leading Customer Data Platform, Retail Marketing & Merchandising, and Real-time Personalization Solution for Algorithmic Customer Experience

Becomes Industry’s Largest Independent Personalization Player Globally

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