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But what if that advice is outdated, inapplicable to your business or so widely peanut-buttered across everything that its being used as a substitute to your human intuition and experience?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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How to Personalize without Behavioral Data using NLP

Personalization traditionally works best when you have tons of behavioral data for each product. But how do you personalize for new products or ones that are considered “long-tail”?  How do you ensure that this inventory is immediately visible and recommended to your customers? Well, you couldn’t until recently .. not without NLP.

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Personalization = Data + Decisioning: 3 Data Feeds You Should Prioritize

You can’t have a meeting these days without someone throwing out the platitude “data is key”, but all too often, we find that even with the vast amounts of data being collected, business leverage of this valuable data is a problem

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Will AI Restrict Consumer Choice?

Personalization, at its core, is the idea that as a consumer, you are served exactly what you want, when you want it. AI is being deployed by retailers and brands who understand that this is a “big data” problem and when product catalogs become larger, machines start to perform as good as, if not better than, human merchandisers.

But does this quest for delivering “exactly” hurt consumer choice? 

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