SHARE TO:

Cutting through the hype: The real benefits of machine learning

Yesterday we publicly announced our largest retail partnership to date. We are honoured and excited to partner with A.S Watson as their preferred vendor for a global roll out of machine learning applications. Over the past year, we have worked diligently with various leaders in the A.S Watson Group and have been impressed with how they approach the topic of machine learning. They’ve cut through the hype and have focused on implementing a strategy that truly benefits their customers, product mix, employees, and bottom line.

So what does this partnership mean for the machine learning industry? For all the frequent volatility that tech companies provide this world, I tend to find technology trends to be ironically predictable. If we look at game-changing industries such as SaaS hosted applications, Elastic Infrastructure as a Service, Open Service Data Businesses, and now advanced machine learning, the tech industry often follows the same cycle:

First Movers:
First movers usually enter the market with a technological breakthrough. In the advanced machine learning field, most of these breakthroughs came from academic spin-offs. The difficulty is that the first movers often have a hard time finding a commercial application of their research.

Hype Cycle:
Venture dollars, incubators, and everybody with a keyboard floods in to make their claim and start the hype. This is certainly the case for machine learning. Just yesterday, I read about a pet camera company that claims to be using machine learning to take their photos. I’m sorry, but a motion sensor doesn’t qualify as AI.

Legacy Leaders:
This is when legacy technology giants tend to do one of two things: They legitimately invest in this new technology and push out competing products to start-ups OR they start changing their product marketing material to reflect this new market and ultimately confuse the customer.

The Emergence of New Leaders:
Near the end of every cycle, new players emerge as the industry standard. For example, Salesforce set that standard in SaaS and Tableau set that standard in data visualization. Sometimes, these new leaders are large legacy players who have successfully made the pivot, like Google and Elastic Computing.

So where are we in the cycle of advanced machine learning in the enterprise? I believe that we are somewhere between the Legacy Leaders and Emergence of New Leaders Stage. This A.S Watson partnership goes a long way to showcasing Rubikloud as a new leader in this space (but then again I am biased).

So what can other retailers learn from this? Start-up or not, if a machine learning solution doesn’t offer tangible results, then don’t bother wasting your time. Our LifeCycle Manager and Promotion Manager made a measurable impact on A.S Watson’s respective loyalty revenue and promotion accuracy. Without these verified metrics, everything else is academic. I once got in trouble for saying on stage that an AI Robot will not drive earnings for retailers and I still stand by that statement. Machine learning for retail means ingesting intelligence into real tangible business processes and taking advantage of the modern data advances in elastic compute.

Finally, there are other technology companies involved in this partnership. Rubikloud and A.S Watson went through significant due diligence in selecting our elastic compute partner for this engagement. Over the coming weeks, we will announce the cloud partner we’ve chosen for our infrastructure support and what that means for this partnership and retail machine learning. I would like to thank our entire team at Rubikloud for all their hard work. Every day I am motivated and blown away by their dedication, intelligence, and innovation in this space. We’re very lucky to have such a world class team!



SHARE TO:

Data Driven Marketing Decisions
Data-driven decisions in retail need to rely on more than legacy analytics.

Read the Report