Transforming Retail Experience through Artificial Intelligence

Transforming Retail Experience through Artificial Intelligence

There is so much talk around about the age of AI and how it is going to transform every business. Bring this platitude to any retailer and you are mostly likely to be met with a deep sigh. (S)he will probably tell you that when it comes to retail, it’s always been the age of the customer and will continue to be so. With customers being constantly connected and exposed to messages from the competition, providing a standout retail experience is becoming increasingly difficult. The key to bettering customer expectations lies in providing a highly personalized, targeted retail experience. This not only leads to improved customer conversions, but also builds affinity and loyalty with them.

As technology enablers, the onus is on us to provide solutions that help retail enterprises make smarter customer centric decisions and provide targeted retail shopping experiences. Let us look at the following 4 AI solutions that help achieve this transformation.

1. Precise Customer Modeling Systems

Precise Customer Modeling SystemsTo put it bluntly, traditional marketing segmentation based on demographic data like age, gender, etc. simply no longer works. This is because demographic marketing is simply mass marketing, which fails to take the sub-segments in your audience into account. Instead, what works best is to understand the interest of the customer, not just the age and / or location.

Machine learning systems have been very effective at analyzing patterns that are not discernible to the human eye. These systems, called Unsupervised Classification Systems, have found widespread application in solving customer segmentation problems. With accurate customer segmentation models, marketers get a clear understanding of customer behavior, thus greatly simplifying the decision-making process. Marketing campaigns can be highly targeted to achieve greater conversions and boost customer engagement. By analyzing the rate of conversions, marketing processes can be made to self-heal and self-correct to adapt to changing trends.

The Donald Trump campaign made use of Facebook’s powerful user segmentation models, to identify similar groups of people and target them with the right messages. Armed with a massive identity database, the Trump campaign was able to secretly target Hillary Clinton’s supporters and covertly discourage them from going to the polls to vote.

2. Superior Recommender Systems

Superior Recommender SystemsSome of the greatest success stories in machine learning have been borne out of the success of recommendation systems. Recommender systems are great at understanding what the customer would be interested in. They not only factor in what other similar customers were interested in, but also pay attention to customer’s own past behavior to predict the tastes and preferences. Companies like Netflix, Spotify, etc. have seen greatly improved their engagement by deploying the right recommender systems. Recommender systems can be used to significantly boost up-sell and cross-sell conversions for retailers.

3. Alert Conversational Assistants

Alert Conversational AssistantsAdvances in Natural Language Processing, have made rich conversational assistants participate in increasingly human like conversations. One of the most successful experiments in the use of AI was done at Georgia Institute of Technology. In a course on Artificial Intelligence, a professor deployed an AI based assistant. No more than one or two students in the 300+ sized class had any suspicion of the assistant’s true nature. Rather, most students were impressed by the fast responses and friendly reminders.

For a retail organization, it is impossible to deploy enough humans to listen to every customer conversation. By coupling AI based assistants with social listening tools, one can ensure that every customer is given an adequate and satisfying response. Incoming messages can be understood, purchase intent can be discerned, and the sales process can be triggered automatically.

4. Turbocharged In-Store Experiences

Turbocharged In-Store ExperiencesWe are seeing the first wave of innovations like Pepper Robot, a humanoid greeter that is leading to increased sales and footfalls. However, we can also leverage AI to greatly improve the in-store experience by truly intelligent mobile apps. Scanning an item by a customer could lead to customized offers, store layout information, deals, navigational / shopping assistance, to name a few.

Thus, in the age of the customer, AI can be a game changer in delivering value to customers of retail enterprises. At TechSophy, we strive to make enterprise decisions simpler and more meaningful. Get in touch with our team to understand how we can help you transform into a customer centric retail enterprise.

For any additional information on AI applications for retailers, feel free to get in touch with us today.

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