When you visit websites like Amazon, Flipkart and Snapdeal, you’re no longer subjected to endless promotions. Everything you see on the home page – advertising, product recommendations and special deals, are all tailored according to your interests.

Now how did they know what you like? Well, eCommerce stores now leverage machine learning technology by companies like Wigzo to learn about the visitor’s preferences. These tools track, analyse and understand the user behaviour to be able to create a personalized journey for him.

This in turn, improves the overall customer experience on these shopping sites.

As businesses across industries go digital and the competition increases, it is becoming increasingly important to interact with one’s target audience in a contextual manner. This has led to businesses using machine learning in their day-to-day processes.

Also read: How can non-eCommerce brands leverage data marketing

Here’s taking a look at why these businesses are using machine learning today and how it enhances the customer’s experience:

1. Tracking and maintaining customer profiles

Machine learning helps businesses track, as well as maintain their customer profile data. This will help them understand what their customers are looking for, stay up-to-date with their changing needs and keep their campaigns optimized for higher results.

For instance, a financial support business can keep a tab on the major life events of their target audience to be able to make the right offers to them, at the right time. Here’s an example – one of their customers just got married and posted the life event on Facebook; the company can now target them with an advertisement that speaks of having their own home and offering a loan for the same.

2. Making personalized content recommendations

Since machine learning tools track and analyse a user’s behaviour closely, the data can be used by marketers to personalize their content recommendations. Showing the user/visitor more content on where is interest lies, infinitely increases his chances of staying on the website longer and converting on an on-going campaign.

For instance, when you go on Spotify, the home page recommends you new artists based on the songs you have heard before on the site. Your interests are kept in mind and at the same time, other content is being promoted to you – you didn’t mind, did you?

Spotify recommendations

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Also read: Why and how to get started with content personalization

3. Predict user behaviour and trends

Since machine learning tools are enabled to keep the customer data up-to-date, businesses and marketers are making use of them for predictive analysis. This helps them gauge what a user may look for in a few days from interaction and create a custom customer journey for him based on that.

For instance, if a customer has bought a smartphone from your online store, you could predict his next purchase based on the data of his demographic’s interaction and engagement with your website. It could be a screensaver or a phone cover that he might come looking for in no time; you might as well target him with a personalized campaign for the same before someone else does!

Predictive-Analytics

Also read: Why predictive modelling is important for modern day digital marketers

4. Improve customer interactions

Machine learning can be used to understand how customers choose to interact with your business and optimize the process. Be it on social media or routing the calls the right representative as per the customer concern in a call center. This would infinitely improve the customer interactions by reducing call durations and offering instant gratification.

For instance, if a customer has incurred a problem in taking the backup of his mobile contacts and decides to call the customer care for the same, he could be routed to the representative who is handling similar concerns. The representative wouldn’t take long to offer the solution and the customer wouldn’t have to wait or hold the line.

5. Establish stronger customer relationships

Continuing on the point above, when you improve customer interactions and their experience with your business, you establish stronger relationships with them. Machine learning helps you run multi channel campaigns across various platforms to create multiple touch points for customers. This helps them understand which platforms are being used the most by the customers and which segment of the target market is interacting with them the most.

Customers that interact with businesses on multiple channels are more likely to remain loyal to it. And with the increasing market competition, it is important to keep these customers consistently hooked on to your business. Be it via a customer loyalty program or offering occasional special discounts to him. This also gives marketers the opportunity to create effective referral programs for the business to leverage word-of-mouth promotion.

6. Creating effective marketing campaigns

In our previous post, we spoke about how data helps in storytelling for high performing marketing campaigns. Whether it is a social media campaign you’re chalking out or a rich media content that you’re planning to create, the data provided by machine learning tools will help you work in the right direction.

Since you know what your target audience wants, what they are more likely to engage with and how you can approach them effectively, you are automatically able to create and run effective marketing campaigns.

The marketing budgets get optimized as no effort goes waste during the execution, because everything is actually guided by ‘what the customer wants’. In simpler words, you’re able to create personalized customer journeys for the different segments of your target audience – which they are more likely to convert on.

Over to you

Machine learning is being used for various purposes by different businesses, across different industries. These tools are giving them the competitive edge over others who aren’t leveraging the technology yet and helping them acquire the market more effectively.

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