A new age of Machine Learning is here
It’s often spoken of as a new development but the truth is that machine-learning is nothing new. Anyone who watched The Imitation Game, the story of Alan Turing, will know he predicted the role that “machine learning” would play in modern computing way back in 1950, in an article that outlined the concept of the Turing Test.
What has changed in recent years, however, are the huge advancements in readily affordable computing power and the quantity of data available; algorithms we never thought we could use are possible today. The speed at which data can now be processed, analyzed and actioned would amaze even Mr Turing. This has completely changed the machine learning game: the fundamental concept remains the same, but now it’s far more sophisticated, efficient and easily deployable.
Beyond the big, headline-grabbing examples of how machine learning will impact our lives – such as driverless cars – the potential it offers to put an end to ineffective customer experiences is truly exciting.
By harnessing machine-learning, businesses can revolutionize the way we all engage with their store or use their service. Forget product recommendations as we know them today, this takes us far beyond that, into the realms of much more hyper-personal sophisticated experiences.
See, think, act
It’s not just about the ability for machine learning to automatically process vast quantities of data to understand customer behavior and identify where the opportunity lies. Today, we can action it as well.
To give an example, machine learning might identify that a British retailer has high traffic from Spain, but lower conversion than expected. It can segment these visitors into two groups – native Spanish speakers, and English speakers. The retailer can survey visitors to find out whether the English speakers are British ex-pats or holiday makers. It can then ensure that the right programmatic abandonment recovery strategy and messaging is sent to each of these groups to encourage them to purchase.
Alternatively, an airline can identify those customer segments that are going to be most keen to fly to a destination at a particular time of year, as well as what will nudge them to convert. It’s a chance to banish meaningless customer experiences forever.
We live in a world where delivering customers the content they are looking for in the very first couple of seconds is critical. If you don’t, the chances are they are going to get bored, distracted, and leave. Tinder’s ‘swipe-right, swipe-left’ mentality is driving change across all sectors.
As always, it’s easy to blame this on “millennials”, but it’s true that this generation are driving the demand for hyper-personal sophisticated experiences. This younger generation values experiences over commodities, and are driving a change in the way brands generally interact with consumers – also known as the experience economy.
The adoption of machine learning is no longer a “nice to have”.
The rise of programmatic customer experiences
To get a sense of the potential impact of machine learning on customer experience, you only need to look as far as the arrival of programmatic advertising a few years ago.
This completely revolutionized how ads are bought and targeted online, harnessing data to not only automate a lot of the “grunt” work, but also to make much smarter, more strategic decisions about where the opportunities for brands lie. The use of programmatic techniques enables campaign performance improvements of between 30% and 50%, according to some studies.
In the same way, harnessing machine learning for programmatic customer experience has enabled marketers to identify clear customer segments and target them in ways that they know will resonate. They now start from a position of knowing who their customers are and what will excite them, empowering them to focus their efforts on meeting their needs and exceeding their expectations at every interaction. This will change the face of digital commerce in the next decade.
We want to change customer experience forever
At Qubit, we want to make it easy for businesses to grab this opportunity and that is why we are immensely excited to be launching Qubit ML. This engine integrates cutting edge, unsupervised machine learning techniques into the core of our platform. The first feature to harness this is Opportunity Mining, available today as a preview feature.
This new tool takes all your available data in Visitor Cloud, identifies customer groups, and automatically prioritizes them using a combination of predictive analytics and machine learning. These customer groups are then listed for you according to which ones offer the largest untapped revenue opportunity, allowing you to programmatically target them by deploying relevant experiences for their needs – whether these be abandonment recovery strategies, social proof, product recommendations, or even a combination of all three.
This is a ground-breaking development for customer experience.
As a marketer, it provides you with empirical empathy: you can measure what your customers are doing and feeling, who they are, what they want, and – perhaps most importantly – how to tailor their online experience.
The businesses that will win in this new expectation economy are those who are obsessed with the customer, that have both great products and programmatic experiences at their core, and understand how to deliver the very best experience for each customer segment.
We are poised to completely change the customer experience game forever.
If you would like to discuss how Qubit ML can help your business, send us an email to [email protected] or get in touch on the form below: