Human engagement through Artificial Intelligence
It is a question that every retailer ponders: How are customers engaged with my brand and how can I keep them engaged?
In the past, surveys were a common tool for gauging customer interest, but today’s shoppers are inundated with requests for their opinions and most often those get lost in the shuffle.
Since humans are often too busy or forgetful to be reliable sources of feedback, some retailers are relying on machine learning — artificial intelligence (AI) — to learn if they are succeeding with customers.
Shoppers provide retailers with an abundance of data, simply by voting with their dollars at the POS: What styles or products are popular, what is not trending, what colors are in vogue, etc.
Size, gender and age are among many characteristics that are vital in creating personas, but also, shoppers’ actions are quantified.
The backbone of AI is machine learning; Programs take all that customer purchase history data in POS like Retail Pro, and unify it with other data sources like browsing behaviors, to analyze exactly how customers view a brand, a store, or a style.
Interestingly, shoppers tend to follow some repeated patterns.
For example, a person often buys the same things, behaves in a predictable way and follows similar intuitions.
By learning one buyer’s pattern, another’s might be revealed as well.
Human intuition
A recent survey by retail management firm BRP Consulting reported that 45 percent of retailers were planning to increase the use of AI to improve customer experience over the next three years.
For many years, retailers relied on sales associates’ perceptions to determine how engaged customers were.
But humans can be biased, and that information is therefore inaccurate.
Today, AI can combine the intuitiveness of human employees with a machine’s ability to analyze massive amounts of data in seconds.
AI helps retailers understand consumers, improve worker productivity, boost efficiency as well as raise sales.
AI-generated recommendations
AI is increasingly being integrated into commerce and retail experiences.
A great example of using AI to recognize customers’ preferences is Amazon’s Recommendation Engine.
Shoppers see items similar to ones they have viewed, as well as others that are commonly purchased displayed prominently alongside the item currently being viewed.
Different recommendation “entry points” are integrated into Amazon’s tool as well, which maximizes cart value.
Recommendation engines help retailers forge a relationship with their customers.
Users can click on the “Your Recommendation” link to display a page that contains categorized products that might be of interest, or they can refer to the section containing similar items with previously viewed products.
McKinsey has reported that up-sell technique is responsible for some 35 percent of Amazon’s revenue.
Small wonder why Amazon has decided to make the underlying technology available through AWS with the “Personalize” tool.
Another instance of a successful personalized user experience is Netflix’s extensive “smart” list of movie and TV show suggestions.
Roughly 70 percent of all content watched by subscribers is a personalized recommendation, according to Netflix.
Shoppers enjoy personalization because it makes transactions feel customized, which leads to a feeling of “specialness.”
And predictive technology lets retailers promote products in a targeted way, which provides customers with a curated experience.
Commit to understanding their preferences
By continuously revising the ad content across various marketing mediums, the likelihood of a purchase increases, although retailers must guard against ad fatigue that can easily evolve into ad blindness, ultimately leading to ad blocking.
Customer engagement has always been a top concern for retailers; the cost of cultivating new customers is steep.
Enticing customers to return by demonstrating a commitment to understanding their preferences pays off not just at the cash register, but also in the word-of-mouth advertising that is gained by being intuitive and responsive, which AI solutions are expert at providing.
