AI Can Personalize Your Customer Experience and Grow Your Bottom Line

AI Can Personalize Your Customer Experience and Grow Your Bottom Line

Are you looking to draw in, activate, grow, and retain great customers by offering the best products and services? Do you agree that in today’s highly competitive and tech-enabled world, this won’t be enough in order to provide a stellar customer experience?

If you’re a really savvy decision-maker, you already know that the customer expectations have increased dramatically. You can no longer solely depend upon merely the techniques that worked over the past decade in today’s fast-paced business environment.

Leading customer-centric businesses are increasingly turning to AI to precisely target as well as personalize customer interactions prior, during, and after the engagement. To convert this into an excellent customer experience, these precious customer engagements ought to be personalized with time and location-aware experiences. This is best accomplished by harnessing the customer data that you simply just have amassed from your various disparate software applications and converting this into powerful customer insights.


Let’s say that your company agrees on the chance in order to target specific individuals or certain customer segments using geographic, behavioral, demographic, and psychographic data.

As you set upon your task, you realize that the relevant and necessary data is spread out across many various systems: in one system you have point-of-sale transaction data, in another eCommerce, in another CRM information, and in another the sorts of products and services they might prefer to buy. In order to actually take advantage of this personalization opportunity, you really need to figure out exactly how to get the proper data from these relevant source systems.

Of course, piecing the information together are often extremely difficult and time-consuming, especially without the assistance of a data analyst and a sophisticated analytics system.

AI can assist you to accomplish this task much more easily via using AutoML algorithms or Automated Machine Learning algorithms. In this it take all the raw source data, automatically stitch together the related data from across various systems, and transform these numerous data points into actionable insights. This will actually further assist your business with providing an A1 customer experience. In today’s jargon, this is quite often called an AI-based Unified Data Analytics Platform (UDAP).

This UDAP which is AutoML-enabled further allows decision-makers to couple the powerful customer marketing analytics that actually enable Acquisition, Activation, Revenue, Retention, and Repetition (AARRR) with the strategic growth levers of Price, Promotion, Product, and Placement (4Ps). This is actually done in order to drive profitable growth in new data-driven ways.

Following are some good examples of opportunities for such precise customer targeting:

1) For example, maybe you’d wish to target women who are 35+ years of age and who also frequently dine out. Let’s call this group “Food Lover”


Food Lover don’t seem to be price-sensitive when it actually comes to their love for healthy organic menu items. In addition you can discover this by using Intelligent Pricing so as to enable a predictive understanding of how customers as well as segments will react to several price points on certain products as well as services.


Nothing excites Food Lover more than an upscale dining experience. Send them a targeted promotion letting them know that if they spend $75 in the next week, they’ll be eligible to win tickets to a Food Network show!


You noticed that Food Lover love desserts, so you send them an email that for this week only their dessert will actually be on the house. Then conduct a basket analysis and send them a good discount on a bundle of other frequently purchased menu items. After all, if they really come in for dessert with a friend, they’ll naturally also need some dinner beforehand and a extremely nice bottle of wine too!


You learn that Food Lover tend to dine in your restaurant more often than ordering delivery. Get answers about their shopping behavior in order to inform how products in your stores are often displayed to promote sales, like by displaying some tasty desserts closer to your entrance. Make sure that their favorite menu items are in stock, and also the promotions are as strategic and visible as possible!

2) In another example, consider that you’d wish to sell golf-equipment to men who are 55+ years of age on your e-Commerce site. Let’s call this group “All Sporty.”


Don’t just measure final conversions; you need to start monitoring your entire funnel from starting to end, beginning with acquisition micro conversions. So when All Sporty actually watches your video on social media or click on your product pages, you’ll know you’ve found much more potential customers as compared to before.


Use analytics to discover that exact ‘A-ha!’ moment when All Sporty get excited by your product. To measure activation, consider metrics ranging from newsletter sign-ups to seeing when All Sporty spend extended time on your blog reading about all the latest in golf gear.


Analytics that is quite precise allow you to not only track revenue holistically, however also segment this into revenue per channel and per customer. From this, figure out which customers are nearing their total revenue potential, and which of them are still likely to spend more. This lets you precisely personalize your messages to All Sporty to decrease lost sales opportunities and to increase revenue.


While most of your promotional efforts may be focused on attracting new customers, most marketing experts agree that optimizing for retention is where you’ll be able to really hit gold! Identify returning customers or trends in individual customer spending to see whether All Sporty are buying just one golf-club -: or if they keep coming back for more!

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