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



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