It’s no secret that companies are always trying to improve customer satisfaction. Happier customers directly translate to retention, more sales and overall business growth.
Marketers understand this and play a central role in how customer experience is managed – they are the key drivers of the buying journey. And the marketing function is one area where many organizations hope to tap the benefits of artificial intelligence.
The hope is that with AI advancements, marketers can both save time and enhance the customer experience to provide superior service. Automation should leave time for marketers to focus on the aspects of their job that are more strategic and creative, like building the next digital campaign that will catch consumers’ attention.
Additionally, the ability of AI to automatically analyze data can enable marketers to deliver relevant and personalized content to potential buyers, allowing them to improve the customer experience at every digital touchpoint.
For marketers striving to improve customer experience and increase sales, let’s explore the following AI-enabled strategies.
AI-enabled customer retention
AI can analyze and optimize the customer experience by detecting the patterns of use that lead to dissatisfied customers, giving brands an opportunity to mend relationships and prevent churn.
Retention insights rapidly capture data from machine learning to identify past events that put customers at high risk of taking their business elsewhere. Marketers can then easily view all instances that have contributed to customer dissatisfaction — and AI can help decide what the next customer interaction should be.
Having instant access to information allows marketers to offer unique promotions to customers as an incentive to stay with the brand, or to simply send a thank you email for their ongoing loyalty.
Personalized recommendation engines
AI’s ability to make consumer recommendations increases the potential for marketers to identify other products and services that customers might be interested in.
For example, an AI bot can recommend items, provide product advice, and anticipate customers’ wants and future purchases before the customer may even realize they need something. For example, past purchases and browsing history can be used to suggest add-on items that customers may find useful.
Let’s say you’ve just put a new water bottle, a jumprope and a pair of sneakers from your favorite athletic brand into an online shopping cart. You get distracted and plan to complete your purchase in a few hours, but before you even do that, you receive an email from the company with the items you left in the cart – making sure you don’t miss out on them before they are out of stock.
They also add an item you might enjoy – a matching gym bag to round out your purchase so you can easily carry all of your new gear. This is a simple scenario in which recommendation engines use data to offer relevant content to customers and make the overall buying experience even better. The AI-enabled engine can also help make recommendations by comparing an individual’s choices with other similar consumers to move the customer further along the buying journey.
Best channel and contact time predictions
AI-enabled marketing tools can hold the promise of optimizing customer interactions by identifying the best contact time and channel for each customer, as a way to make their buying experience as smooth as possible.
For example, AI can differentiate between a 20-something who logs into their email app on their smartphone during lunch time and a grandparent who logs onto a desktop browser once a week to keep in touch with family. Due to the difference in habits, AI will recommend distributing messages across different channels and at different contact times to best reach the individual, and automatically keep track of the results.
This technology enables you to reach your target customer, regardless of their internet usage. AI can analyze the variety of signals they receive each day and use these insights to determine the next best action for each individual. For example, this may include a recommendation to reduce the number of marketing messages to ensure that the customer doesn’t opt-out because of excessive points of contact.
In the future, we’ll begin to see more marketers use AI-enabled image recognition to intelligently track customer interactions in-store, determine how much attention outdoor ads or window displays receive, and more. New interactive displays can help customers “try on” different outfits, or make recommendations that are aligned with what they’re already wearing.
For example, if a green-eyed shopper is wearing a blue crewneck sweater, they would be guided toward green sweaters with a similar cut to complement their eye color and match their personal style.
AI-driven technologies such as face-recognition are very powerful, but this is an area where marketers must be very careful not to invade customer privacy in counter-productive ways. It has always been critical to respect consumer privacy and with new regulations such as GDPR being enforced soon, these actions should be taken to the next level. Marketers should focus on the opportunities to use these new technologies to provide superior customer experiences while being mindful of governance.
Thankfully, there are good compromises available that can provide valuable demographic data while respecting governance laws and without compromising customer privacy — for example, cameras pointing at knee-height can still provide marketers with valuable demographic data on customer age and gender without identifying individuals.
As AI-enabled marketing technology continues to advance, marketers should consider how these assets can help their overall brand strategy. Despite having a wide range of consumer types, buyers expect brands to think of them on an individual level.
The days of mass emails and simple name personalization are over – consumers expect more. To enhance the customer experience and keep consumers happy, and make them more likely to purchase, marketers can leverage AI-enabled tools to automatically improve the customer experience and demonstrate just how well they know their customers.
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