During the pre-COVID era, I remember attending many events and workshops. Of course, one of the prerequisites for going to an event is signing up for those event management and ticketing platforms. Something in the back of my mind told me that this was just a one way ticket to spam city. But I wanted to support my local talent, so I decided to go through the process.
Countless permutations and combinations of these “events that may interest you” emails began popping up in my inbox. It was overwhelming, and with all of these random suggestions coming in, I really missed out on some hidden gems.
“Alright Events platforms, to the promotions tab you go,” I said to myself.
It was a Friday night, and I was bored out of my mind. I decided to pay a quick visit to my promotions tab, and I noticed that some of these events emails I was receiving began to align with my interests. I took the leap, and I went to the event.
Now ask yourself this, this email motivated me to attend the event, but is it enough for me to stay?
Here’s a quote from Jeff Bezos from Amazon-
“We see our customers as invited guests to a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.”
Personalization versus Hyper-personalization
Personalization is receiving the email to push me towards going to an event. However, as a first-timer and a complete stranger, I might feel a little lost and confused about what to do. If someone or if I got an email telling me to check out certain kiosks, I’d have more motivation to stay.
That’s what hyper-personalization is. It goes beyond personalization and uses real-time data to contextually communicate information that’s relevant to the customer.
The emergence of big data makes hyper-personalization really easy. Brands can now extract information like needs, expectations, and demands through behavioral data. Brands can also discover a customer’s personal preferences using these technologies.
Is hyper-personalization needed?
According to The WealthTech Book, “hyper-personalization promises to deliver higher client satisfaction at lower cost.” The current age of the highly-empowered buyer is underwhelmed by current digital offerings.
This, coupled with the fact that mobile devices are creating a monopoly on how people receive information suggests that brands need to ensure that the information they transmit to leads, captures their attention.
Brands only have 8 seconds to touch a customer, make it count.
Unfortunately, what we’re seeing instead is an overload of information that tunes buyers out. In fact, user engagement with content has decreased by 60%, according to TrackMaven. But, if you have a message with offerings that align with your customers’ interests, you’ll definitely see a spike in conversions. This is why hyper-personalization is the need of the hours.
Data like name, title, organization, specific interests layered with real-time information like demography, location, can provide more insights that allow you to hyper-personalize your messages.
The elements of a hyper-personalized framework
A well-integrated framework of tools and processes is all you need to master hyper-personalization.
Currently, 80% of customers feel like brands fail to understand them, according to this report by IBM. Without data, it’s impossible to understand who your customers are, what their needs are, and how to address them.
When it comes to data collection, there are 5 stages of personalization maturity.
Stage 1: No data
When you have data, or the data you have barely scratches the surface.
Stage 2: A peek into mass marketing
This stage is when you collect customer data, but seldom use it. Usually, companies at this stage of personalization maturity dip their toes into email marketing campaigns and open-ended broadcasts.
Stage 3: Slowly getting there
When you collect customer data and perform basic A/B tests to improve sales.
Stage 4: Segmentation
You collect customer data and begin to segment your existing and prospective customer base. Most companies fall under this stage.
Stage 5: The ultimate hyper-personalized experience
A collection of rich customer data that can be used to treat every customer individually through behavioral recommendations, omni-channel experiences, and predictive analytics to recommend products and services. This is where companies strive to be.
The simplest way to collect customer data is through conversation. Use a conversational chatbot to capture customer data in real-time. If you integrate your chatbot with Google sheets, or with a CRM, you’ll gain better transparency to understand your market as well.
We’ve touched on this in stage 2. After you’ve collected a substantial amount of data, you’ll have a better understanding of how your customers engage with your brand. You’ll come to realize that certain groups of customers engage in particular ways. You’ll pick up patterns and trends amongst certain groups and you’ll understand that not all customers are alike and that they have different needs.
Now imagine knowing this, and putting out a message that only resonates with a small handful of customers. That seems pretty wasteful, doesn’t it?
Instead, what you can do is group similar customers together through a process called segmentation. Most companies group customers that are in a similar location, have a similar demography, needs, average spend, and satisfaction scores together. And now you can target and write specific messages for each segment.
After creating segments and identifying each group’s needs, you can begin designing targeted journeys. Keep on eye on what channel is the most active and at what hour, as the more targeted and relevant your communication is, the higher the chance of conversion.
Measurement and Analysis
Campaigns aren’t just a one-and-done deal. You have to monitor and measure the effectiveness of it as well. Avoid looking at vanity metrics such as likes and shares, take a closer peek at more actionable metrics.
Once you understand these metrics and conduct an analysis on its effectiveness, you’ll have a better understand of what worked, what didn’t, and what needs to focused on for the next campaign you run.
The key to ensure success for hyper-personalized campaigns
To make hyper-personalization work, you have to follow a data-driven approach. Every click your customer makes, Every post they scroll past- these are all valuable pieces of data that can help you create an experience that’s tailored to your customer.
You also have to consider:
According to research by the Epsilon Group, 80% of customers are more likely to make a purchase when a brand offers a personalized experience. In fact, one of the respondents reported that hyper-personalized campaigns almost tripled and quadrupled customer engagement. A bump in registration was also observed. The main takeaway of this research is to collect and analyze data at every point of the customer journey, and to observe trends to discover how to best optimize the journey.
What makes Spotify and Netflix so popular? Is it their vast library of media or could it be because they know exactly what to market and to whom? Their recommendations are always on-point because they know exactly what a person like me would like to watch and listen to. By using behavioral data and real-time insights, they know how to create messages that align with a customer’s needs and pain points.
The final, and most important factor- trust. In order to collect data, your customer needs to trust you. This can be subjective to the region, some countries are less interested in hyper-personalized marketing because they feel it might be invasive. When you collect insights, and find that this is the case, it’s best to not market to this crowd.
In addition, customers will only gravitate towards brands they trust the most. Try to share content that contributes to your credibility. Blast educational content like how-to’s, insights from thought leaders, and videos that align with your customer’s needs.
How hyper-personalization ties in with localization
Localization is about sending the right message, to the right customer, at the right time, and in the right place. Hyper-personalization on the other hand targets specific users, whereas localization looks at specific markets, based on regions and creates messaging using local images and languages. A good example of localization in action is with McDonalds.
While they have a set menu with a few staples, it’s adapted for each region. For example, in the Middle East, pork-derived products aren’t served at all. Another example is India- the population of vegetarians in India is incredibly high, and there’s also a low population of people who eat beef. It would be nonsensical to provide an American menu, where the star of the menu is beef. What McDonalds did instead was a complete redesign of the menu with more options of veggie burgers.
Think of localization the same way. It’s about using real-time data about specific markets to create products and services that feel unique to the region. Going back to McDonalds, that’s why there’s a lot of appeal amongst travellers to visit each McDonalds in the place they’re visiting.
Another example is Starbucks. There’s a summer menu filled with iced coffees, lemonades, iced teas, and frappuccinos, and there’s a winter menu with hot coffees, and spiced teas. Starbucks is all over the world, and their pumpkin spiced lattes cause an uproar in the months of October to around January. But does it make sense to advertise that latte to those in the Southern Hemisphere, who are just about to experience hot breezes and summery nights? Starbucks instead sends coupons and deals and messages that follow the summer menu.
Localization is about sending the right message, to the right consumer, at the right time, and in the right place. Think of localization as utilizing real-time data about individual markets to create hyper-specific content or offers that feel unique.
Achieving hyper-personalization with localization
Hyper-personalization in tandem with localization is the future of marketing, but only a small handful of brands are leveraging this strategy. Here are a couple of ways on how to deliver hyper-personalized content at a scale.
Localize your webpages
As the digital world becomes smaller, our reach becomes more global. However, offering a single-language website closes many doors. According to this research paper, 60% of shoppers rarely make purchases from English-only websites.
Content translation is needed to give brands the opportunity to connect with their shoppers. Incorporate geolocation or plugins that allow your website to change language depending on the user’s browser history and update your content. Take it a step further and change currency per location as well!
Another easy way to implement hyper-personalized messages is through multilingual chatbots. Chatbots provide a straightforward path for both leads and customers to navigate through websites. And having a tool that communicates in a customer’s preferred language in real-time is extremely powerful.
Instead of having customers drift away and into the arms of a search engine, a chatbot can either resolve a query or direct the conversation to a live agent. This then builds both trust and credibility.
Multilingual chatbots can also be used as a data collection tool. They can gather feedback, collect information like name, contact details, and discover the customer’s interests. This data can be used to help you with your hyper-personalization strategy.
Chatbots have infinite memory, so the next time the same user lands on the website, the chatbot can deliver a hyper-personalized message along with recommendations tailored to the customer’s interests.
Predictive analytics and recommendations
As customers engage with your digital real estate, i.e., your chatbots, your website, etc., they’re revealing pieces of information to you. You’ll gain an insight into your customers’ lives, like their interests, their preferred messaging channels, etc. This is all you need to master hyper-personalization with localization. Amazon, the world’s biggest eCommerce giant uses this technique, contributing 35% of sales on the platform since 2013.
The Amazon technique
Say your prospect is a 30 year old man who opens his laptop everyday at 3pm and browses through your website. He usually stops at the “what’s new” category, and then moves to “electronics and appliances”. Through these interactions, you can predict that he’s probably a techy.
Since your chatbot has picked up his age, you can assume his preferred method of communication is email. A few minutes before 3, you can send an email with recommendations of the newest electronics for him to browse through. So that at 3, he already has an idea of what he wants to buy.
How to adopt the hyper-personalized approach
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