Customers rely on a wide range of sites to consume everything from recipes to music, interact with friends, book trips or order cookies.
But as the data deluge swamps the world with zettabytes, and marches on to gigantorzillabytes (a made up word, but you get the idea), consumers of digital media, entertainment, education, ecommerce or any other category of information must be prepared to handle the associated challenges of so much data.
Wildly Varying Digital Experiences
One of these challenges is your online experience is likely to oscillate wildly – from the extremely satisfying, “I found what I wanted within minutes!” to the less enthusiastic, “It took me a while to figure out how to get what I wanted” to the downright annoying, “Why does this website keep showing me wart remover I am most definitely not interested in!”
The reason for such varied experiences is fairly simple – just as people are in different demographics, locations and even states of mind, digital service providers also fall into a large range.
Evolutionary stages of technology and industry offer a multitude of approaches to choose from when attempting to provide the best “digital experience.”
Although digital service providers’ approaches (and sophistication levels) may differ, most are interested in keeping you engaged.
A site may be virtually global, but content publishers, retailers, social media platforms, etc. know that to keep customers engaged, they must present highly personal and contextually relevant content, whether that relevance is determined by location, demographic or what I forgot to purchase today.
Search Isn’t Foolproof
A basic, but common method of providing customers with contextual relevance is through search.
Let people type in what they want and the right thing will pop up. But have you ever shopped online and wondered why it’s so hard, even after multiple searches, to find the item right?
The answer circles back to the data deluge. When there are millions of items to search through, results are hard to filter without additional information or algorithms that rank relevancy.
Often, providers trade accuracy for speed, taking an “it doesn’t matter if it’s correct” approach. The result? You spend hours hunting for a little black bag on a website.
Various Curation Techniques
Another approach to providing relevancy is curation. This is popular among reputable news sites (current events notwithstanding) and other sites that offer content such as on-demand video, social media platforms, and blogs.
Curation techniques range from the unsophisticated “ranked by popularity” to the somewhat intelligent “people who read this also read…” all the way to the very sophisticated machine learning/artificial intelligence approach of “based on what you read and where you came from, we think you will like…”
None of these approaches are without their pitfalls. But as the level of sophistication increases, the number of times you’ll find yourself irritated by irrelevant or downright annoying content will decrease.
Of course, there’s a ramp-up period that must be accounted for as machine learning models and artificial intelligence grow mainstream. Models need time to be trained, content shelf life is low and an infinite number of customer segments could possibly exist.
Technology, Infrastructure Limitations
There are also technology and infrastructure limitations that providers must overcome. Really good machine learning models are deep and have high levels of accuracy, but that also means that they are larger and need to be kept up-to-date in real time.
Serving such sophisticated models at scale and within the high-performance requirements needed for interactive applications requires sophisticated systems. This could also lead to an explosion in infrastructure requirements unless datastores can natively understand these models, and serve, update and execute them with as few resources as possible.
Combatting Data Overload
So what can consumers and businesses do as the digital world shifts to artificial intelligence in order to combat “gigantorzillabytes” of data?
For consumers, there will be a learning period, as with anything else undergoing rapid growth and change. Another important action is to be careful of their digital footprints. Unless you go incognito, chances are your data is being analyzed. Not-so-savvy advertisers could follow you around, leading to frustrating and potentially embarrassing situations.
What should businesses do? Invest in technologies that don’t require tradeoffs between real-time and accuracy1.
Real time is a must-have. Studies show a drop-off in customer engagement when the performance of your application isn’t up to par.
But accuracy is equally important to keep customers happy and avoid turning them off and missing opportunities as a result.
Real-time databases that can handle both high-speed interactions and analytics often make for a great choice because they avoid the need to trade off performance for sophistication.
About the Author
Leena Joshi is VP of product marketing at Redis Labs. Leena has spent more than fifteen years in the high tech industry in a variety of product marketing and product management roles.
Photo Cred: Pablo Duran
This Article was published By: Leena Joshi
and shared from: www.cmswire.com