Raj Badarinath
Raj Badarinath is the CMO at RichRelevance, where he’s enabling retailers and brands compete on memorable digital experiences. With over two decades of experience in Software/SaaS, Raj is responsible for driving growth via global marketing and communications initiatives for the company, from strategy, positioning & differentiation to demand generation, branding, alliances, martech and product marketing. His prior background over the last two decades were with high growth startup companies with successful exits such as Nutanix (NASDAQ:NTNX), 2Checkout, PeopleSoft and systems integrators such as Capgemini and Infosys. He’s lives in the SF Bay Area with his family and is a dog lover.

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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How to become a CXO with Omnichannel Personalization

So you are a personalization expert – congratulations! You are now on the fast track to become a Chief-X-Officer.

That X can be Marketing (CMO), Merchandising (CM’O), Customer (CCO), Experience (CE’O) or Digital (CDO), and ultimately, become the Executive (CEO).

Here’s why personalization is putting all these titles on a convergent path, and you can choose any path as long as it has personalization in it.

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UK: AI in online retail: How is hyper-personalisation driving the sector?

Technology advances are enabling retailers to introduce new levels of customisation, with companies introducing artificial intelligence (AI)-based hyper-personalisation experiences to tailor and follow consumer shopping trends.

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Experience Designer for Digital Marketers

Content creation is a heavy lift for most digital marketing orgs. Creating multiple variants is a huge challenge in itself. But how can you curate the content variety in a data-driven manner and target explicitly for a commerce audience?  With Experience Designer, you can jumpstart your content personalization. 

In the last post,  we learnt about the Experience Browser, the industry’s first solution for transparency in AI decisioning. Experience Designer plugs into the XB, leverages the Xen AI engine to determine the right targets automagically, and leverages your existing content to create campaigns. 

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Experience Browser: Shining a Light on the AI behind Web Personalization

Can you tell if personalization is working effectively on your commerce site, right now? Not just the “what” — content or products/offers is being shown — but why and how?

As companies forge ahead and invest in artificial intelligence and machine learning technologies for their e-merchandising teams, the goal is to treat every website visitor as an individual and let them pick out their own experiences instead of defining an one-size-fits-all “journey”. 

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Algorithmic Testing: The Evolution of Experimentation

“Test Everything” screams a headline from one of the A/B testing vendors.

This is the world that marketers live in today… hundreds of A/B and MVT Tests, statistical significance, traffic allocation, optimize, rinse and repeat!

But what if that advice is outdated, inapplicable to your business or so widely peanut-buttered across everything that its being used as a substitute to your human intuition and experience? What if it doesn’t apply to ecommerce sites at all?!

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Happy Holidays… in August?! [Part 1 – Holiday Readiness]

While it’s true that I am based in California where cannabis is legal, I will assure you that no substances have been imbibed during the authoring of this seemingly mistimed post.

It’s because most of our retail and brand customers are gearing up for the holiday season right now, in August. And like most of them, the IT cutoff to make any meaningful changes, test, and deploy to production is before September. 

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Not your Grandfather’s Personalization

A quick story. 

About two decades ago, a relatively small ecommerce company focused on selling books introduced a new feature that allowed customers to see what others had liked and purchased, called collaborative filtering, for product recommendations. This feature became popular with the business guys as the “wisdom of crowds” and very soon, every retailer on the planet was scrambling to implement it. 

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