How to Use Applied AI in Retail

ElectrifAi
Mar 23 · 5 min read
Jacob Lund / Shutterstock

Creating an excellent customer experience is crucial for the retail industry. Return customers are the bread and butter for a store to continue operations. And word-of-mouth references from those customers increases the store’s revenue.

So, how do you create those amazing experiences? With the power of Applied Ai!

Applied Ai is the part of Artificial Intelligence (Ai) for those organizations who want to leverage the power and capability of Ai and machine learning models but don’t want to invest in the research, development, and resources necessary to build from the ground up.

Many companies are involved in Applied Ai in many areas of the ecosystem. At ElectrifAi, we bring Applied Ai and Machine Learning as a Service (MLaaS) to our clients. Our pre-built machine learning models are available to anyone who wants to take advantage of the benefits of Ai without building it from scratch.

How do we bring Ai to our clients to help them create a frictionless customer experience?

In today’s remote culture, reducing friction in how the customer engages with your company is very important. In this blog, we’re going to delve into how to increase traffic to your store, make your employees more effective, and how Applied Ai and machine learning models can help you do all this and more.

ElectrifAi’s Machine Learning Model Factory

ElectrifAi’s Machine Learning Model Factory enables you to look at a sea of solutions and pick the ones appropriate for your business that will allow you to grow your Ai competency. With so many machine learning models available, you can begin your Ai journey with ease to start solving critical business problems.

For example, you can start with mastering data management to find out what models (use cases) you can use, such as churn analysis or customer profiling. There are many models to fit countless use cases to help your business cut costs, increase revenue, and decrease risk.

But which ones specifically apply to retail?

Applied Ai Use Cases for Retail

Our experience has shown the most sought-after Applied Ai use cases for retail are the following:

Business Process Automation and Internal Bots

Many companies wonder how to improve internal operations. Machine learning can help find the best answers to that question.

Making employees more efficient is possible through many different models using Applied Ai. For example, classification models can improve the decision-making ability of the Legal, HR, or Customer-Service teams.

This is how Applied Ai really shines! Being able to look at someone’s everyday job to determine the areas with the most friction and — if it is applicable — apply machine learning to alleviate some of the work that person does.

Customer Intelligence and Recommendations

Companies always want to learn more about customers. Applied Ai can help you find out how to use social networks to get as much information as possible about customers so you can serve them best.

Intelligent Search

Many organizations have optimized their website’s search engine to make finding information easier rather than relying on an external search engine to find the right information (likely pulling up other companies in the process).

Similarly, ElectrifAi’s machine learning Recommendation Engine models can help you get a better understanding of the information you have so you can find it easier.

Oftentimes, a lot of friction — especially on customer calls — is finding out where the information is to get an answer. And that might take too long to answer the customer. Prompt responses are critical to keep a conversation flowing and make a deal.

Retail Intelligence

How do you get a better retail experience for customers? By providing everything from upsell/cross-sell opportunities, knowing the customer’s lifetime value, and so much more!

Engaging Conversations with Chat Bots

Chatbots are very common nowadays with online retailers. So, how do you stand out from the crowd and use this feature to truly engage with customers and make it a memorable and positive experience?

Frictionless communication by communicating the way customers want to is an easy way to use Applied Ai.

Natural Language Processing (NLP) has so many uses but one of its main abilities that isn’t used often (or at least well) is language detection. It is important to speak in the language of your customer to keep things from being lost in translation… literally.

Hyper-Personalization with Computer Vision

Let’s delve into an area of Applied Ai not many people have heard of but is a very useful feature of chatbots. This is the ability to hyper-personalize the chat with Computer Vision.

Imagine a customer wants a very specific item but doesn’t know the terminology to use (such as a rose gold watch with a round dial set with crystals and a gold mesh band). But the customer does have a picture of the product they would like to purchase.

Did you know if the customer gives the chatbot the picture of the product, the machine learning capabilities of Computer Vision can process the thousands of products available in the online store and locate the highest probable match?

Presenting that match to the customer… Bam! The chatbot has scored a sale.

But wait… that’s not all.

Before the customer checks out, cross-sell and upsell opportunities are presented. By truly understanding the customer’s desires, machine learning can target what that customer might like to add to their cart and present that to them before checkout.

If the customer is going to place an order anyway, why not add a few more things to the cart? Chances of sales revenue increase due to that slight nudge and the customer’s shopping experience has been elevated.

Conclusion

Possibilities are endless with Applied Ai. In fact, our very own VP of Solutions Architecture, Noelle Silver, delves deep into those possibilities with our weekly LIVE video series, This Week in Applied Ai.

Check out Week 2’s video to learn more about Applied Ai in Retail. Noelle describes the use cases in this blog in more detail, plus gives a very interesting use case example of how Computer Vision can help further personalization for in-store experiences.

Imagine walking up to a digital kiosk and being instantly recognized and pointed in the direction you need to go to your scheduled shopping excursion. And being greeted at the store by an Associate who already knows your name and everything needed to make your shopping experience a breeze? Talk about feeling VIP.

Want to learn more about how this works? Watch the video!

There are so many things Applied Ai can do in Retail (along with many other industries) to create a better customer experience. Applied Ai repeatedly drives value for companies, so the question is how do you get started?

Beginning your Ai journey is easy with ElectrifAi. Want to see a demo of how this can work for your company? Contact us today to learn more!

Medium is an open platform where 170 million readers come to find insightful and dynamic thinking. Here, expert and undiscovered voices alike dive into the heart of any topic and bring new ideas to the surface. Learn more

Follow the writers, publications, and topics that matter to you, and you’ll see them on your homepage and in your inbox. Explore

If you have a story to tell, knowledge to share, or a perspective to offer — welcome home. It’s easy and free to post your thinking on any topic. Write on Medium