You may be a retailer out to run a successful business, but you are also a consumer. This means that you are well aware of how predictive analysis, thanks to machine learning and artificial intelligence (AI), embedded into our everyday technology, enables you to make smarter purchasing decisions. From seeing relevant advertisements pop-up on social media feeds, to having offers for a particular purchase you have been contemplating arrive in your mail, to personalized shopping experiences at a store, Gartner has predicted that 85% of customer interactions will be handled autonomously by 2020. This will be done with cross-channel bots that will even be able to recognize voices and faces of customers. This last, can happen as early as 2018.
Here is also some of what deep learning and AI can help retail businesses achieve with their customer interaction:
- Based on purchase patterns, stock levels and inventory management will become easier, with updates handled in real time.
- Being able to provide personalized shopping experiences with the help of Natural Language Processing (NLP) will be a reality.
- Based on customer purchase pattern analyses, customer loyalty as well as life time value (CLTV) can be predicted, which enables a retailer to customize customer retention strategies.
- Deep learning and AI can help in creating algorithms that can recognize suspicious behavior on the store floor as well as on the backend to prevent theft or any sort of monetary scam.
If you look at it, these are things that are easily observed by floor staff in a retail set-up. However, their observations have never been automated up until now and hence the benefits of such analyses are being recognized right now. While retailers have laid off floor staff to cut corners and enhance the bottom line, it is collection of this data from their time on the floor that can actually enable increased profits.
Another key source of data from consumers comes from wearable devices, providing a great deal of information that can be analyzed to come up with detailed predictive consumer profiles. This will allow a retail establishment to interact in more personalized ways with their customer.
There are three key areas where AI can work on enhancing the consumer experience and as a retailer, these are segments to concentrate on:
- Using bots to evaluate customer purchase patterns and create simple interactions that will enhance consumer experience. For example, following the purchase of a convection oven, emailing a set of recipes that can be made, a cleaning and maintenance manual or even a common FAQs will go a long distance.
- Using analyzed data to enhance a sales representative’s abilities on the floor will bring about that elusive predictive knowledge based customer engagement through human interaction.
- Automation of backend tasks such as routing of consumer requests, post sales services etc. can be handled with AI and deep learning in a much more effective manner.
While a slow change is being seen in the retail sector in this regard, digital native retailers (who have kick-started their businesses online and are now moving to brick and mortar set-ups) have already begun using AI and deep learning to their advantage.
Now we have spoken a lot on the need for quality sources of large data that can be used for analysis. Now let us also look at what kind of analyses can help make that huge difference. Here are two main categories:
Recommendation engines: These are ones that look into the purchase pattern analysis angle of all the information that is gathered. This gives the retailer a holistic view of customers’ tastes, their shopping styles and strategies. Deep learning applications can help create a powerful interaction strategy that will enable conversions.
Sentiment analysis: Analyses of this nature puts together a mix of customer knowledge and balances it out with external factors such as special days of the year, weather, generic purchase patterns etc. All of this uses deep learning and works in a seamless manner to help retailers increase their conversion rates in online as well as physical store sales.
Tracking consumer behavior discreetly and understanding it has become an easier task, thanks to AI and deep learning. Following a retail consumer through the cycle of being a shopper enables a business to enhance conversion rates as well as ensure return customers.
Implementing machine learning and AI in your organization need not be viewed as a daunting affair. There are numerous service providers that can help you set up and get you on your way. The benefit with going with such providers is that their services can be scaled up and down based on your specific needs. As an organization, the only thing you need to do is ascertain what your needs are and focus all your analyses in meeting these goals. With accurate technology supplemented with quality content, AI and machine learning are going to help your business take customer service to the next level in the coming years.
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