Personalizing the Customer Experience we are able to bring the human factor into e-commerce, making the customer feel as comfortable as when they met a kind shopkeeper in the store. Read on to find out how to accomplish something similar online and increase sales.
Today, we are so used to buying online or in large retail chains that we may not remember what it was like before.
People used to buy in stores, where the real plus was the kindness and helpfulness of the salesperson who enticed you not only to finalize the purchase, but also to come back and talk positively about it to your friends. In these few elements is encapsulated the essence of commerce and thus of marketing. Clearly, what played a key role was the human factor.
In recent years, commerce has definitely shifted to the digital channel, and indeed bringing the human factor online has not been easy at all. However, it is possible to recreate something similar by focusing on personalizing the user experience, that is, making the potential customer feel comfortable, offering him content and products truly designed for him, advising him as the aforementioned store clerk would. What is personalization if not the transfer of the human factor to the cold, analytical world of digital?
Advanced profiling and segmentation
To achieve this goal, technology intervenes, albeit skillfully guided by humans. It aims to get to know the potential customer as much as possible, collect data from him, systematize it and process it with algorithms that can even go so far as to predict his next move. More or less what the experienced salesperson used to do when confronted with a new customer: he would team him up, try to figure out what kind of customer he was, and propose the product that might be right for him. Advanced profiling and segmentation repeat this same path in the digital world.
With the profiling you collect as much data as possible about the user: age, gender, buying and browsing habits, but also interests, tastes, lifestyles, values and needs. With the help of some platforms, one can integrate various data sources, online and offline, from different channels and collect data at all available touch points. It’s as if salespeople from different stores in the same chain are talking to each other and comparing the latest customer experiences. That’s actually what happens, and all the data ends up in a CRM, a database that collects user data, which is particularly valuable material for marketers.
What about segmentation? Based on the data collected, ideal customer models, buyer personas, are outlined. Users are grouped into macro groups characterized by certain factors in common: the same buying habits, the same job, and so on.
Another technique to frame the customer and derive very useful data for our business is the RFM matrix. The acronym stands for:
- Recency
- Frequency
- Monetary
We evaluate potential customers on the basis of these three factors, which are related to their buying habits and in particular the days since their last purchase, the recurrence and the amount spent. We use this data to give a kind of “score” to users and figure out which ones are the most profitable for our business. We might simplistically think that the best customer is the one who spends the most, but that is not really the case. According to the criteria in this matrix, it is the combination of spending made, frequency and time since the last purchase that reveals who the best customers are.
Based on Customer Lifetime Value, we can then further segment our customers, creating new clusters and planning targeted and thus more effective strategies. Imagine the aforementioned experienced salesperson teaching the newbie the basics of the trade and explaining to him how to recognize a customer who is able to spend from one who probably just came to browse
What about the seller’s experience? Is that a purely human thing? Not really, we have at our disposal Machine Learning and Artificial Intelligence, which by collecting data are able to build a kind of historical memory and “learn about” potential customers.
The importance of personalization in the context of an eCommerce
The most important factor in turning a potential customer into a real customer is theshopping experience. It is no coincidence that some famous brands have come up with specific strategies to enhance the experience in physical stores. Think of music and scents that envelop you (or hammer you) as soon as you cross the threshold of certain stores-have you ever heard of olfactory marketing? Then again, this attention to the sensory aspect is a normal consequence of customer-oriented marketing. The customer as a human being spends his life having experiences, so marketing has also become “experiential.”
So why invest in the personalized customer experience?
- In order to implement effective cross-selling and upselling strategies
- To improve customer retention
- To improve customer satisfaction
And thus ultimately to increase sales and optimize investment. And it’s not just theory; the data backs it up. Let the numbers speak for themselves:
- companies that invest in customer experience are 60% more profitable
- Brands that curate the customer experience for their customers bill 5.7 times more than those that do not
- 84 percent of companies that decide to improve their customer experience report an increase in revenue
- McKinsey research has shown that user experience personalization can increase ROI by about 5 to 8 times and sales by 20 percent
- Dimension Data reports that an appropriate customer personalization strategy leads to a 92 percent increase in customer loyalty, 84 percent increase in revenue, and 79 percent cost savings
- personalized CTAs convert 42% more than traditional CTAs, the average transaction value increases, as does the conversion rate
One of the companies that has taken advantage of Customer Experience Personalization strategies more than others is Amazon, and it seems to have made a good profit. If you happened to do a search on the site, you may have noticed the personalized pop-ups, the purchase recommendations based on your search history, and after the fact emails with ad hoc offers. It’s enough to start with small things, little touches that make the user feel considered and listened to. And today that is a winning combination.
Tools and features for customization
It is not necessary to become Amazon; we just need to study a strategy that suits our business. We have several tools at our disposal and it is not necessary to use them all. The risk is to become too aggressive towards the user and we would get the opposite effect to the one we wanted.
As anticipated, we start with data collection and analysis to learn more about our potential customers through profiling. Then with segmentation we group our audience into segments and delineate typical customer types, which will be the target of our marketing strategy. For each buyer persona we have identified needs, fears, values, needs and tastes.
Now we need to create a personalized path for each of these personas, leading them (hopefully) to conversion. We also need to try to predict what the users’ possible reactions might be and prepare alternative paths. All of this is the workflow, a diagram that traces the possible path of a user interacting with our brand. We have several types of interaction available.
- With content personalization we can plan differentiated communication depending on the type of user. We will make different banners, slideshows and communications appear on our site depending on the segment.
- La product recommendation, particularly suited to the world of commerce, involves showing potential customers the products that are best suited to them, including through up-selling and cross-selling strategies. Amazon is a master in this field. The experienced salesperson will never offer a 500 to a couple with children in tow; he will perhaps opt for a station wagon. The salesperson will recommend the customer based on her physicality and occasion of use.
- Behavioral messages are communications that appear to the user via banners or pop-ups that are closely linked to actions he or she takes on the site. Certain actions trigger reactions, in this case in real time. We can try to convince the undecided and prevent them from leaving the site. If the customer in the store approaches the children’s book section, the experienced salesperson will approach to inform him of the current promotion on that very genre of books, observing how the customer moves around the store, in real time.
- Email and text message campaigns to try to re-engage the customer once they have left the site, through personalized offers based on their preferences and search history.
- Push notifications are a powerful tool because they are the only type of communication we can schedule for anonymous users, those who leave us no contact. They appear directly on the Home of the user’s device without him doing anything, even if the application is not open at that moment.
It would seem that through algorithms, it is possible to recreate in the digital world the sensory experience of shopping in the store. We can curate the design of the site to make it more appealing, follow the customer with personalized messages, as a salesperson or salesperson would do. We can understand what kind of customer we are dealing with, how much they are willing to spend, what their availability is.
