3 Reasons Why Retailers Need Machine Learning


When you hear the word machine learning, lengthy algorithms may pop-up in thought bubbles around your head and soon you may feel a bit faint. But in all seriousness, machine learning’s benefits in the retail world are monumental;  machine learning has improved how retail operates for every function from customer service to supply chain,.

You’ve heard the saying ‘data is king.’ It is used to tap all decisions like what to stock, how to optimize prices, enhanced purchasing suggestions, how to identify patterns, how much to buy, what products to suggest to repeat customers and so much more. Well, data may be king, but it can’t act by itself. Retailers’ data must work for them, and that is where machine learning comes in to help retailers really succeed in the current market.

What Is Machine Learning and Why Should You Care?

Machine learning is a subfield of artificial intelligence that automates data analysis. Users feed a data set into a chosen algorithm that analyzes the data and creates a model that can then make predictions about other similar data. Machine learning is being used by retailers and marketers in so many ways, as mentioned above. (And in some cases, maybe a little too well, as in the infamous machine learning incident where a large retail company learned of a teenage girl’s pregnancy before her own family even knew).

Here are three of the most important ways that retailers can and should already be using machine learning:

1. Predicting Shopper Behavior

Retailers already predict shopper behavior, but I’m talking about going far beyond typical predictions. For example, think about what you need to buy when you are on vacation. You might need an extra pair of sunglasses and sandals, or maybe you forget your cell phone charger and need a new one ASAP. With the right algorithm, you identify travel behavior and then use location and brand preferences to deliver offers that are likely to appeal to consumers right then and there. When you start thinking about all the combinations you can possibly predict, it’s apparent that machine learning is necessary to handle it all, if you have any hope of handling these predictive recommendations successfully.

2. Making Data Actionable

Retailers have an incredible amount of data at their fingertips – zip codes, pricing, brand preferences, product patterns, and so much more. This data is worthless, however, if you don’t also know how and when to act upon it. Artificial intelligence allows you to determine not only the content that matters to consumers, but to understand when it matters and where to deliver it. This is especially important in today’s environment when privacy concerns are paramount and irrelevant offers are ignored. By getting in front of consumers only at the most opportune time, retailers leveraging machine learning will have a huge advantage.

3. Driving Brand Engagement

Not only does machine learning allow you to understand how to best engage with your consumers, but it can handle the process automatically. Machine learning can be used to automatically respond to the most common inquiries, giving your audience access to lightning-quick answers. That’s why we are seeing an explosion of chat bots.

If something is too complicated for a quick answer, it can still be passed along to your Social Team for a more in-depth response.

Machine learning has quickly established itself as a huge force in the marketing world, across all channels and campaigns. Despite years of chatter about machine learning transforming our businesses, we’re really still only in its infancy. So many of the most powerful applications are still only a pipe dream. Brands that are able to get the hang of it now will not only enjoy plenty of short-term benefits, but will also be well-positioned to dominate in the future in ways we can’t even imagine in 2018.




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