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Personalizing the Online Shopping Experience: Using Data to Delight Customers

Nobody needs to sell you on the benefits of online shopping; It’s a staple. It’s a given that if you sell products, you need a good online store.

What is less obvious is how easy it is for you to collect big data and insights and use them to make your customers happy. That’s what you’re going to learn about today, and it’s all a lot easier than you might imagine.

Collecting Data

Personalizing the Online Shopping Experience: Using Data to Delight Customers

Before we even talk about using data, it’s important to understand how you can even get your hands on it. Since we’re discussing online shopping, there’s a lot of good news; You don’t need to buy elicit data from shady brokers or have to spy on your customers.

Instead, you can simply keep track of what they do on your website. That alone provides you with most of the data you could ever want or need.

To build on this idea, any time someone visits your website, you can see which pages they view, how long they view those pages, what order they go in through the site, what they buy, what reviews they choose to leave, and any returns they try to process.

You can see what they do and don’t like on your online store with just this information, and your website is already built to collect that data. You just need to know it’s there and make sure the data tools are turned on.

Crunching Numbers

Of course, a bunch of raw web data is hard to use. Fortunately, your web services can also crunch the numbers to provide tons of useful insights. Again, you just have to turn them on and actually look at the results.

Using Insights to Delight Customers for Online Shopping

So, what do you actually do with these crunched numbers? You can apply them to intentional efforts that make customers happy.

Multichannel Communication

First, let’s clarify: multichannel communication is a term that refers to the different ways your business can talk to customers. Things like social media, emails, chat support, phone support, and anything else you might use all fall under this umbrella.

So, what does multichannel communication have to do with data-driven personalization?

To simplify the idea, you can use your data tools to collect customer information and update multichannel communication with it

Imagine a customer ordering a smartwatch from a digital store. They get the watch, and it doesn’t work quite right. So, they contact your support channel to get help with it. Unfortunately, they can’t resolve the issue in that first conversation, so the customer contacts you later using another channel. Maybe the first contact was a phone call and the second used live chat.

You can dramatically improve this customer’s experience with data-driven personalization. You already have data telling you who this customer is, what they purchased, and when they purchased it. You can also collect data from each time they talk to you.

By doing this, you can avoid a ton of frustration in the second conversation. Your chat support specialist can already see what has been discussed so they can jump right into the new conversation and be ready to help.

This idea extends beyond support.

A customer might use multiple conversations to figure out which product they want to buy. Multichannel data support still fosters streamlined, continuous conversations across these channels.

Personalizing the Online Shopping Experience

Personalized Recommendations

Multichannel communication is probably the least intuitive example in this article. Personalized recommendations make obvious sense, but it’s still worth discussing some of the details.

If a person interacts with your online store, you can see what they browsed, and your data tools can keep track of that and automate many of your online responses.

The short version is that your website can now make personalized recommendations to them based on their own personal browsing data. Social media sites do this already, but a more concrete example might drive this point home. For example, if you operate an online bookstore, consider keeping track of the customer’s prior purchases and use that information to recommend a book that they would like. 

Imagine you sell an online food subscription service. People order meals from you, and you deliver the food right to their door. Food is extremely personal, and if you keep track of what a customer orders, you can see their eating preferences. Your systems can use that to recommend additional meals that make browsing easier and keep them delighted with food they consistently enjoy.

Custom Products

You can run with the idea of personalized recommendations and even expand what you offer based on customer data and preferences. Trends and even direct requests build up the data you need to see what new products might sell well.

Consider another example.

This time, you help customers pick out formal wear for events — like tuxedos. Over time you see that more and more customers are ditching bowties for cravats. In fact, you can see it in hard numerical terms, so you decide to offer more cravats to delight your customers.

Which cravats should you offer? You can dig back into your numbers to see colors, patterns, and materials that get the most positive attention and go from there.

Product Education

Another form of personalized delight comes from product education. Sometimes, customers need to learn more about their products to get the most value from them. This seems obvious with complicated tech tools like a new smartphone, but it even applies to simpler products. Health and wellness supplements for UTIs, for example, often require specific dosages and regimens for each customer, so education is key in order to make the customer feel comfortable purchasing. 

For instance, if you sell a customer a frying pan, they might have questions about the best ways to care about the pan. They might also wonder if it’s oven-safe or dishwasher-safe. Countless other questions abound.

You can use customer data to personalize the answers to those questions. Modern chatbots allow customers to ask direct questions, and the bot can then provide a specific answer to that question. You can go further too by creating additional educational resources for common questions. Maybe you should make a video that shows the best way to clean the pan.


The bottom line is this:. Digital shopping creates mountains of data, and you already have access to tools that can collect and analyze that data. The rest is up to your creativity, but with a concerted effort, you can use your data tools to make your customers happy and build a solid business foundation.

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