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For e-commerce businesses, artificial intelligence (AI) and machine learning are nothing new. Both have been gradually transforming the way retailers operate and improve their online offerings through enabling greater efficiency and a better understanding of their markets.
In 2021, however, technological advancements and enhanced intelligence in these areas will expand the way businesses can benefit from an AI integrated model.
This article addresses how businesses can leverage the ever advancement of AI to build out perfect customer profiles and, in turn, generate more effective marketing campaigns and online sales results.
Businesses are constantly looking for ways to improve both the efficiency and effectiveness of their operations. And this will only become a more important focus as we continue to navigate the complex and volatile COVID-stricken commercial climate.
Fortunately, e-commerce is thriving. Unlike physical retail, which has been significantly impacted by pandemic restrictions, online sales are up. In fact, during the 2020 holiday season, which is typically the busiest shopping period each year, online sales were up by 44.8 percent, with almost half (47.8 percent) of all retail sales taking place through remote means.
With a permanent digital shift on the horizon, or at least one that will see businesses adopting an omnichannel approach in order to benefit from the best of both worlds, more will look towards ways to streamline what may be unfamiliar practices for new digital business, as well as to lessen the larger workload.
AI is already offering solutions for these pain points. Through its data collection opportunities and automation options, there's the ability to reduce administrative tasks and wasted resources, saving businesses time and money and creating a better customer experience as a result.
In 2021, there's a case to take this one step further. Now that we're aware of the benefits of AI and can be certain that it's here to stay, businesses should see much less risk involved with an integrated approach.
By using the technology and data available to build better customer profiles, retailers can truly utilize AI’s power and capability to their advantage.
Better Understanding of Your Customers
AI is known for its ability to collect data in order to demonstrate and predict customer and market trends through analyzing shopping behaviors, as well as influences in both the micro and macro environments.
The result is a holistic picture of your market that can then go on to inform business decisions. But as it advances, the quality and use of the data it's able to collect and analyze has moved on in leaps and bounds.
Today, and going forward, data and insights can be used to generate a detailed and accurate understanding of each individual customer, rather than general consumer segments. For instance, through the collection and acceptance of cookie data when a consumer visits your website, you can begin to build their profiles, including product interests and browsing preferences.
With this information stored safely in your data platform, you can then tailor content when they revisit a page to create a more personal and favorable experience. And if agreed in your policy, you can even use this information to tailor targeted ads and communications.
Now, there are differing views on the ethics of this practice. However, even with tightening regulations and compliance measures, data collection control does remain in consumers’ hands. For those that do accept, it's the retailer’s responsibility, and in their best interests, that they use it sensibly.
Typically, a consumer will want their browsing preferences to be remembered. It makes for a more convenient shopping experience and saves them time in resetting and re-filtering options. In fact, 90 percent of consumers are willing to share personal behavior information with brands for an easier experience. Therefore, a brand that's able to do this will be looked at much more favorably, encouraging revisits and repeat purchases.
What they don’t want, however, is for brands to abuse the knowledge they hold by spamming them with endless communications and retargeted ads. In fact, these may actually damage the reputation of the brand, rather than offer it any benefits.
But the data you collect can help you predict that, too. You can uncover which type of ads are responded to best by each customer, and even detail the time it was responded to, in what form, on what device or channel, for how long, and whether it did in fact encourage a clickthrough or conversion.
This information is invaluable for building customer profiles. With it, you can create more successful campaigns and offerings as you're giving your customers exactly what they want.
And while in the past, individual profiles tended to be grouped together into segments by similarities, the automation abilities of AI integrated systems mean every individual consumer can be given a personal and tailored experience.
The success and sales results speak for themselves. Personalized content already receives better engagement rates than more general alternatives. For example, personalized emails can achieve up to a 55 percent increase in open rates, and 91 percent of consumers are more likely to shop with brands that provide relevant offers and recommendations.
Now, just think of how much more successful these activities can be if we take targeting a step further and inform our decisions with information we've collected through AI advancements in order to create detailed and accurate customer profiles.
Personally, I believe it’s an opportunity that cannot be missed.
Nate Burke is the founder and CEO of Diginius, a software and services provider with a performance-based approach designed to grow your sales and leads online and compete in the marketplace.
Related story: 4 Key E-Commerce Personalization Trends to Expect in 2021
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Nate Burke founded Diginius in 2011. He is known as an early e-commerce pioneer and entrepreneur. He launched his first internet business in 1997 and is a two-time nominee Ernst & Young Entrepreneur of the Year. He has a BA in Computer Science and an MBA from the University of Alabama.