Boosting Online Retail with Machine Learning

Neat websites, mobile apps, excellent digital customer communication are no longer the prerogative of ‘digital companies’. Everyone has to utilize available technology in order to compete in the market, from bakeries to software development start ups. The demand for new content, digital products, multiple-device support is growing, as do the customer expectations.

The modern online retailer can hardly survive, let alone strive in this market, without multiple customer touch points and excellent customer experience across all of them. Everything has to run smoothly, be constantly improving in terms of offerings, cool features (like social media account integration) and certainly avoid any bumps for the customer. Otherwise you will lose them to the next company.

Today, the biggest market leading retailers know how to run the business in the most efficient and profitable way. Well, rather, they have a solution that does. Machine-learning is the answer, and behind all the media frenzy and new ‘buzz’ words, you can clearly see – this is the next big thing for online businesses.
You can use machine-learning for literally any one of your business needs. However, online retailers can focus on three crucial parts – pricing, inventory and cost saving.


An overwhelming number of offers in the market, all the discounts, and seasonal changes make the pricing incredibly dynamic. There are many more factors involved that impact market prices and it becomes humanly impossible to keep up. With the fight to retain every single customer so fierce – you have to be sure that your pricing is absolutely perfect, both for the customer and your business. Machine learning can be the ‘brains’ behind your pricing policy. Taking into account all the KPI’s you’re aiming at, and what the customers will see as an appealing offer, machine learning algorithms will provide you real-time instructions on how to hit the bulls-eye every time you rollout new product or update existing ones.

You can test-drive propositions derived from machine learning on focus groups, a sample of prime or random customers to make sure that your pricing is effective and that the machine learning solution does work. Moreover, machine learning will not be hard-coded (hence, the ‘learning’), but will reuse found patterns and trends to improve performance, forecasts, and recommendations. You’ll be getting better or more accurate results as the time goes by and there’s more data to process.


67% of consumers name bad experiences as the reason for churn. And you can definitely put ‘Sorry, the product is not available at the moment’ in that category. It is a special type of disappointment. And it is certainly a ‘bad experience’, when you’ve offered the perfect price for the customer but didn’t have the foresight (or, rather, the technology) to ensure that you really DO have the offered product.
With machine learning at your disposal, you don’t have to worry about that. Now you have your own personal oracle for inventory forecasting. Not only will you be able to pro-actively monitor your product availability, but you will have the forecast for future demand and the areas where you have to stock-up.

Essentially, it works in the same way as the pricing algorithms – gathering information from various sources, building predictions and learning off results.
For the retailers, it means always being in the ‘sweet-spot’ when it comes to inventory stockpile. You’re not overburdened with products that are never or rarely bought, and you’re always in stock (and we mean always, no more surprise surges in demand because you have already anticipated it with the machine-learning forecast) on the trendy stuff.


And if all of the above are not good enough – on top of getting all the perks and benefits of implementing a machine learning solution you are simultaneously reducing costs! All the manual working hours poured in figuring out the best price and procurement are substituted by code lines. The manager can just add a human touch to the rock-solid calculations and forecasts done by the computer.
Add to that boosted revenue from better customer experience, agile pricing, accurate product availability and you get a serious differentiator among competitors.



Machine-learning is red hot at the moment and still gaining momentum. Those who were quick to adopt a machine-learning solution are already monetizing the intelligence that they receive. The best part is that it is absolutely scalable. No matter if you’re Amazon or a small online shop – you will be getting similarly effective and applicable results.

Online retailers absolutely have to tap into this trend in 2016 and readjust businesses to correspond to customer demands, competitors and the available technology.

Not only will you learn infinitely more about your customers, you’ll also get a new insight on your own business and how to bring it closer to the big guns of online retail.

Author: AI.Business

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