Improving Customer Experience with Tech, Analytics, and Algorithms

How do you separate real analytics from snake oil analytics? It’s simple: it’s the results of a customer experience that will let you know if you are doing it right. You can have a wealth of customer experience management tools already. But in reality, the ability to turn the stories of each customer experience management tool

Here are some popular use cases of how technology, analytics, and algorithms play a monumental role in supersizing and launching an excellent customer experience for your target market.

Product Matching

There’s the infamous Target online store story of its algorithms detecting a teenager to be pregnant before the family ever knew. Extreme examples aside, you can find that online stores are popularly known for implementing what’s technically known as recommendation engines. It establishes mathematical relationships on what they know about the customer, his or her behavior in adding cart items from the same store, and the existing product list on inventory.

Machine learning algorithms for recommendation engines (like what you see on Amazon similar items or “customers who bought this also bought” sections on the webpage while shopping for items) allow you to relax while the math figures out on its own what items your customer will potentially like or add to their shopping cart.

Anomaly and Fraud Detection

American Express and other financial institutions take advantage of the ability to detect fraud or identity theft. You improve customer experience when you give them a safe shopping experience. For example, dubious transactions done way outside the customer’s usual travel destinations can send an immediate alert, as well as a sudden influx of large transactions in a suspicious location.

Customer Persona Refinement with Micro-actions on Your Website

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There are free online courses from Google Analytics Academy, and it will do you well to know more about these products, such as Google Analytics and Google Tag Manager. Google Tag Manager can go as far as determining how many seconds of video your customer watched on the landing page before moving on to other sections of your web page. You can also install heatmap trackers that will further determine the customer eyeball movement on your website so that you can put your call to action buttons and sales push campaigns on prominent areas of the page where they linger.

Checking Correlations for Churning Customers

You don’t just work to maintain your happy customers; you also try to find out what makes customers leave. And the technology can assist with this. One of the gold mines for this kind of information is Support emails and customer contact center voice recordings. If they are unhappy with a service, they will likely place in a phone call or leave feedback somewhere. Of course, disgruntled customers of your online business will not usually be too keen to tell you detailed ways to improve your business, especially if they have gone over to a competitor. It’s up to your analysts to detect patterns of behavior for customers before they churn or leave your services.

For example, phone plan users may be enticed by a competitor company with a better phone plan or more specs for the same amount of money they are paying their original phone company provider.

Given all the benefits of marketing technology to your customer experience, it’s worth it to join the bandwagon.

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