Automation doesn’t have to be scary. In fact, for the foreseeable future it stands to be the next revolution for our economy. As it relates to retail, we are now faced with more data than ever before. “Big Data,” “Data driven,” and anything to do with Data these days is a hot topic, but how are people leveraging this data and how is it driving results?
Despite it being such a hot topic it still remains something mostly talked about, but not often used. I thought I’d take a look at some of the companies doing a good job at leading the charge to smarter/faster decision making, which ultimately relates in better customer experiences.
Innovators like Pinterest, Yelp, Nextdoor and Disqus have been vocal about their use of Machine Learning to improve the experience and deliver the sought after 1-to-1 messaging. Machine learning is being used to determine how User Generated Content (UGC) is being viewed by Yelp and Pinterest, while Disqus is using it to identity and remove spam comments. All of the above-mentioned brands were successful in their approach to machine learning by simply identifying key challenges in their business and researching what machine learning solutions can support them.
The CEO of Walmart is quoted recently at the shareholder meeting saying: "No doubt our work will be different in the future —robots, drones and algorithms will do some work that we used to have to do," he continued. "Some people are afraid of what these changes will bring. I don't think we should be. Instead, I think we should recognize that we'll be able to learn, grow and change together."
Here is a quote from Christopher S. Penn, which speaks to why a machine needs to be part of our personalization strategy:
The reason the promise of personalization has not panned out is because we treat people in clusters and groups that we can mentally manage. Our marketing capabilities simply cannot create true personalization for thousands or millions of people. Could you imagine even trying to build a website with thousands of variations for every possible customer? It’s an insurmountable task. As a result, we pulled back from personalization. We started creating artificial constructs like customer personas to cluster types of customers together. However, we know that personas are lies. There is no Sally Soccer Mom, no Tony Technologist. These aggregated people don’t exist; every person is a unique individual. Creating marketing based on these gross generalizations has led to unimpactful campaigns, causing customers to feel like abstract afterthoughts rather than valued individuals.
Now, AI can identify trends, patterns and nuisances down to a level that is hard for us to understand and impossible for us to process like a machine.What if you were able to see that someone entering from paid search on a Tuesday night, who spends X amount of time on a page, and scrolls at Y speed, who has clicked on Z product will be 80% more likely to purchase if you alter the customer experience slightly. Imagine this type of scrutiny and impact for every shopper who visits your page.
If you'd like to chat with me more about how retailers are already using these best practices in machine learning or will be going forward, you can drop us a line and I'd love to spend a little time talking to you about it!
Greg Chiefa is the VP of Sales at Granify. Greg’s years of selling to enterprise retailers have given him a focus on process-driven growth. His ability to take a sales team to the next level has been on display at Cartera Commerce and RetailMeNot before joining the Granify team.