Artificial intelligence can turn your one-and-dones into customers for life

It’s been two decades since recommendation engines turned shopping upside down. You know how they work: if you bought this book, other people who made the same purchase bought these books. Or, if you’ve seen this movie, here are similar genres. Or, if you were looking for that armchair, here are others that look the same! These are all recommendations that we probably take for granted at this point, but they made us expect more from our shopping experience.

Remarkably, I’ve had less than 1 in 10 personal expertise where I think the dealer says, “Don’t worry Michelle, I’ll make you look great in this skirt.” Or maybe you say, “Don’t worry, Michelle, I’ll make you look great in this skirt.” “This is the right cladding for the faucets you have from Kohler in your bathroom and it will match the chrome on the vanity you purchased.”

Most of the time I’m all alone. This feeling is shared. Something 80% of buyers say that they feel they are not getting a personalized shopping experience, even though a Survey in 2018 found that two-thirds of consumers were interested in personalized recommendations and more than half were willing to share data to get that additional help.

There’s an obvious division between what buyers want and what they get. One problem is that the definition of “personalization” is unclear or inconsistent. Often times, interpretation leaves something to be desired as it simply shows buyers more discreet products that they are likely to buy. There is no coaching; no expertise; You don’t have to learn to be a better version of yourself or improve your game. What consumers want is to know what they need. The needs are so much deeper than just “This is the product out of 1000 from the same category that most likely fits you.”

The consumer has to actually take this product and operationalize it in his life. For a piece of clothing, this means combining it with other items in order to wear them for certain functions or occasions. For beauty products, it means knowing how to apply in a specific order to achieve a specific goal. For a vacuum cleaner, this means knowing which spare parts or add-ons are needed. Choosing the right vacuum is only the first step. It can be extremely frustrating to walk down a rabbit hole looking for filter bags and attachments that will fit your chosen vacuum model. You are not a vacuum cleaner expert. But the store should be. Why doesn’t this expertise come to you?

Automate a manual process

The reason is that many retailers and brands do not have the resources or manpower to leverage their data and bring their unique expertise to the consumer. Merchandising teams, business partners, and personal shoppers spend much of their time understanding how products work to help their customers make decisions and be successful with the products they buy, but there aren’t enough of these products- and brand experts. Top brands often have hundreds of millions of customers who couldn’t possibly get that personal attention. It is important to note that “attention” is not synonymous: new business partners may not know everything about every product, or they may simply not be suitable as a stylist even though they are a really good seller. Getting a highly curated, expert guide into the hands of hundreds of millions of consumers is not just a question of quantity, but quality.

Adidas sold 448 million pairs of shoes in 2019 alone. As one of our clients, we’ve helped millions of clients deliver this bespoke experience by helping them match their shoes with the rest of their outfit. It would not have been feasible to achieve what we have done by hiring experienced personal shoppers, let alone profitably.

Even if they were to hire these people, the process would still be inefficient as the data generated from every customer experience and engagement would not be spread across the various touchpoints. For example, in physical stores, customer interactions and related communications (e.g., emails) are often handled in this store.

In addition, creative assets are often static. Ideally, if the advertised product is out of stock or a product with higher margins is received, the ad should change in real time, otherwise there is an opportunity to convert customers. So we not only help with increasing sales and the average order volume, but also with the gross margin.

FindMine’s solution applies machine learning and artificial intelligence to the human creative process. Our technology provides predictive information about the outcomes a human expert would create for the brand, enabling a brand or retailer to produce continuously updated content that provides more customers with real-time branding and personalized expertise.

Create brand loyalty

Generating repeat purchases in retail is no mean feat. Most customers are “one and dones”, which means that they buy once and never return, mainly due to the abundance of options. Think about the websites you visit and shop from: do you care more about where to shop or which website to get the best deal? Everyone wants to save money, but a trustworthy brand with a service-minded mission will keep the customer coming back time and time again.

Providing customers with this guided experience is one way to increase that value. I take pride in my team’s ability to help our retailers and brands create loyalty, which is the biggest driver of overall sales. We have already demonstrated this: One customer saw the repeat purchase rate increase by 4.5% within 30 days and another increased by 8% within just two weeks. That doesn’t seem like much, but when most of your customers are “one-and-dones” and 8% more of them come back within two weeks of buying them, it has a huge compounding effect. In fact, retailers see somewhere between 20 and a whopping 95% increase in profitability for every 5% improvement in repeat purchases. Even that small increase can make a big difference to the bottom line.

The success rate when selling to an existing customer is between 60 and 70% compared to the success rate when selling to a new customer, which is between 5 and 20%. Acquiring a new customer can be costly five times more than retaining an existing customer. Whichever way you cut, it’s in a brand’s best interests to keep their customers as long as possible, and that means giving them a reason to come back.

The future of the retail experience

Many brands still often describe the shopping experience in different silos: retail, wholesale, online, offline, social, and email, although they may seek consistent data collection across all channels in order to create real-time marketing campaigns across all channels. They know this will work if only it wasn’t that expensive.

By automating this data collection to create continuously updated content, the cost is not that high, especially when compared to returning it.

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