Successful brands like Burberry, Thomas Pink, Louis Vuitton, Hugo Boss and more, have always sold immersive and one-on-one shopping experiences to in-store customers; and at the same time, most online stores are unable to provide similar personalized interactions to shoppers. However, with advances in artificial intelligence, digital experiences don’t have to be so impersonal.
As a photography hobbyist, I love taking pictures and am always buying and upgrading my cameras and lenses. Even though I have switched to buying camera equipment online a while back, I greatly miss shopping at my local camera store.
The sales staff at was knowledgeable, personal and had gotten to know my likes and dislikes. They knew what camera equipment I owned, regardless of where I purchased them. They also knew which camera bodies and lenses, I got repaired and tuned, and had detailed knowledge of my preferred style of photography and skill-level.
Decades ago, I jumped on to the Nikon bandwagon. Nikons use a specific and proprietary interconnect called F-mount to connect detachable lenses to camera bodies. Once you are in the Nikon ecosystem, you buy lenses and bodies that are F-mount compatible. Nikon further has cropped-frame cameras and lenses for enthusiasts and full-frame for pro-consumers and professionals. The staff at the local camera shop would only talk to me about Nikons and not Canons or Sony. They wouldn’t mention medium format cameras or lenses from Hasselblad.
The local camera shop knew that I prefer portraiture photography over landscapes, and would give me sound and friendly advice. “If you are going the spend that kind of money, do it on glass” — a reference to professional lenses, explaining why it is better to spend on faster f/1.4 prime lenses than camera bodies.
Every experience I had with the store was exceptional, including buying cameras or lenses, getting the camera sensor cleaned or tuning the autofocus on lenses, returning an item, or simply chatting and sharing experiences with the sales staff.
The camera retailer would contact me about specials, offer discounts on products I was interested in, and inform me when Scott Kelby was in town for a photography session. They cared about my photography.
The store never sold my information to someone else. They trusted me, and I trusted them. I always ended up purchasing more than I had planned, but surprisingly, I was always happy about it. The individual attention and personalized advice were worth paying extra when buying camera equipment.
In today’s e-commerce sites, consumers have to parse and filter through millions and millions of products before they can find something that they are interested in buying. Customers are usually looking for products that are compatible with what they own but have to spend countless hours researching.
The recommendation systems based on collaborative filtering — predicting whether a user would like a product based on products liked by similar people — do not work well for many reasons, but primarily because every user is different. Clustering users in a group and treating all of them collectively is not one-on-one experience.
Self-research is replacing friendly advice. Consumers are resolving to time-consuming research, browsing ratings and reviews, and reading question and answers. It takes up a lot of time and research reading reviews and separating out the fake ones. More often than not, consumers leave without buying anything. They have zero loyalty with the vendor and focus more on the price at the time of purchase versus total cost and experience of owning the product.
For an online e-commerce site, it is not easy to provide the individualized attention to millions and millions of digital customers. Digital experiences can be personal at scale by using technological advances that can deliver one-on-one personalization at massive scale.
Artificial intelligence machines — robots, humanoids, chatbots, and modern software — strive to mimic the cognitive functions of human minds including learning and problem-solving. Marketers can provide similar experiences to digital users using AI and one-on-one personalization.
What do digital users want?
So what do Digital users really want? Simply, they want to be understood, delighted, loved and trusted.
Users want to be understood
Knowledge of your digital users’ traits and behavior is the basis of understanding them. Characteristics describing the users’ demographics; their location; what devices or technology they use; what their values interests and opinions are; what is their attitude i.e. what they say via surveys, ratings, and reviews; what they own and what they need.
How users use your product i.e. the user’s behavior in your product, along with their traits helps in clustering of users with similar characteristics, which is helpful for macro-analysis and customer segmentation. You have to, however, pick and choose the criteria for segmentation carefully.
If you know that a customer is a novice, professional or hobbyist user, you can create custom action plans for them. You can grow loyal users, convert under-monetized users, re-engage attrition-risk users, and resurrect churned users.
You can create prediction models based on the variance of users from the center of the cluster. For example, detecting behavioral shifts of individual users from the center of the cluster they belong to can help in discovering attrition early enough to act and save users from attrition.
Users want delightful experiences
Not every user wants to scan reviews for content, relevancy, and accuracy. Not everyone cares about becoming an expert when purchasing products. Not every user has the patience to search through millions of products.
Users want to be helped. You know the user’s click, purchase and browsing history. You are aware of their likes and dislikes. You know how they have rated other products. You can survey users to find out what products they own. You have attitudinal data from reviews. You have access to keywords they used on search engines to arrive on your site or app.
Convert what you know about your users into one-on-one product recommendations. Show users returning products alternatives based on the reason of return. Show recommendations in chatbots. Surprise them by reminding them of promotions and coupons the customer has received in the past and could apply during checkout. Make every digital touchpoint delightful for your users.
Users want to be loved
Users want to be engaged when they are using your product. Building engaging, well thought out interfaces indicate that you care about your user. Engage users with personalized content, user interfaces and experiences when they use your product. Show them meaningful content and messages that help them.
Send them personalized and highly relevant promotions, offers, content that reminds them you care about them. Get implicit and explicit feedback about the topics that interest them. Send them warranty expiration or product recall notices. Focus on quality versus quantity of messages. Make every message personal and relevant.
Users want to trust
Consumers want their privacy respected. You should earn their trust before you send them personal and relevant promotions. Learn about them before they are shown product recommendations.
If you collect, track and aggregate user information, tell them upfront in an as clear way as possible without using legalese. Apps that ask for Permissions explaining why they need those permissions have a much higher rate of acceptance.
We want our online digital experiences to mimic the authentically human interactions we have in the real world. To create digital experiences that embody this, digital marketers must develop a profound understanding of their users and then use that knowledge to make every digital touchpoint delightful and engaging — this is what keeps users coming back.