It’s time to bid goodbye to the marketer’s favorite friend: “Personalization”
The last few years have heavily experienced marketers focussing on personalized content to drive customer engagement. But as we skim through 2020, the magic seems to be fading:
In fact, it can be harmlessly regarded that the chink in its armor for personalization is its actual modus operandi itself.
If we widely define personalization in the context of marketing, it will turn out to be something like this:
Keeping track of the purchase habits and browsing behavior of a certain consumer group and targeting them with offerings that they are more likely to purchase.
In other words, it was nothing but grouping related customers into various segments and targeting them accordingly.
Therefore it can be harmlessly said that personalized marketing was just a more systematic and automated version of the age-old tactic of Segmentation.
Is Personalization not enough in 2020 and the years to come?
What personalization inherently lacks is that much-required authenticity, accountability, and context that a consumer is constantly looking for in a brand.
In a Nutshell:
Personalized marketing as of now has been unable to provide value based on purchase behaviors that are completely unique to an individual buyer.
Hence it’s time to provide an iconic facelift for the marketer’s favorite weapon.
As per Business2Community, hyper-personalization is “The use of data to provide more personalized and targeted products, services, and content.”
Hyper personalization, as the name suggests is something that literally dives into the crux of the personalization element.
Individual Behavioural Aspects, yes that’s the only element that it focuses on, and thus holds the potential to significantly increase the success of a certain Marketing Campaign.
Why is Hyper-Personalization the Future?
1. Campaigns yield better conversions
The game of personalized marketing is all about Customer Touchpoints.
The higher the number of touchpoints, the greater the amount of consumer data that a firm can gather and finally use them to achieve Higher Conversion rates.
However, prior to when hyper-personalization was a thing, marketers primarily target one and only one customer touchpoint.
That’s the Previous Purchasing History or Browsing behavior of target customers that were grouped into various segments.
On the contrary, hyper-personalization offers a plethora of customer touchpoints that firms can target.
- The time of most frequent Purchase
- Preferences in communicating with a business
- Context of purchase
In this way, brands can generate significantly more appealing content/services to their target customers ultimately leading to higher conversion rates.
Let’s consider the case of the E-commerce industry that has benefitted heaps and bounds through hyper-personalization.
According to Forbes:
- Hyper-Personalization has led to a 49% increase in Impulse Purchases among E-commerce customers.
- Of them, only 5% of the impulse purchases made were returned.
The above stats corroborate the fact that Hyper-personalising marketing content has played a major role in providing an individual consumer with “exactly what he wants”.
2. Enhances Customer Experience
Customer Experience is another element of marketing where hyper-personalization can contribute significantly.
Hyper personalizing a brand’s website helps to streamline a customer’s decision-making journey, i.e. from awareness to the final purchase.
As a result, the overall scope of a customer making the final purchase increases significantly.
Naked Vines.com is a burning example of using Hyper-Personalization on Brand Websites:
Image Source- Crowdfire app
The Wine Seller allows its users to create customized dashboards so that they can be presented with unique product recommendations and offers, the next time they visit the website.
In addition to that, such type of customer data is driven through predictive analytics in order to trigger certain time-specific e-mail and push notifications that have higher chances of conversion.
3. Increased Brand Loyalty
According to Peter Reinhardt CEO and co-founder of Segment:
“Shoppers expect brands to remember who they are, whether they’re on a digital channel or in-store. However, very few companies can actually deliver on these tailored experiences.”
Also, as per linkdex, more than 50% of consumers in the US and UK expect brands to remember their previous purchases.
The above facts strongly indicate that there is a direct relationship between brand loyalty and personalization.
The more personalized a brand’s offerings are, the more motivated a consumer becomes when it comes to making a repeat purchase.
When a customer who has previously made a purchase from a certain brand, sees product recommendations that are fully catered towards interests, he becomes highly motivated to make a repeat purchase as well.
Therefore, providing hyper-personalized online shopping experiences can help a consumer in developing a strong bond with the brand and engage in continuous repeat purchases.
4. Proactive Customer Engagement
This is the point where Hyper Personalisation well and truly scores above personalization, and has the potential to provide an extravagant spike to a firm’s revenue.
Previously, when the concept of Hyper-Personalization was not that prevalent, firms typically relied on their IT Teams when it came to managing customer data.
Due to this Marketers had a very meager level control over how quickly they can act upon certain customer data or queries.
However, with the ever-increasing popularity of Advanced Business Management Software like CRM s and CDPs, there has been a drastic change in the manner in which businesses are handling and responding to customer data.
CDP/CRM software is fully managed by a firm’s marketing team which has full access to customer data in a real-time manner.
How do CDPs provide Customer Engagement in a Proactive manner?
With CDPs, firms have managed to significantly shorten the time period between the customer’s query and providing an answer or recommendation.
Secondly, CDPs enable firms to create data segments, belonging to different customer groups and can also communicate directly with a firm’s e-mail, advertising, and push notification platforms.
This facilitates marketers to almost immediately respond to online customer queries and targeting with appropriate and personalized offers.
Gathering Data for Hyper-Personalization
This is the first and arguably the most important step in your Hyper-Personalization journey.
Failure to gather accurate and relevant customer data would render your marketing campaign completely futile, as a customer would barely be able to resonate and thus won’t proceed further.
Gathering customer data for hyper-personalized Marketing campaigns requires a highly in-depth approach
Let’s begin by stating the nature of data that you should strive to collect:
(a) Nature of Data
The obvious Ones- name, age, location
Frequency- How frequently are you consumers interacting with your brand?
The Medium- On which medium/mediums are your consumers responding the most? This can include Social Media (paid ads or posts), e-mails, Text Messages, Google Ads, etc.
The Type- What types of Marketing Content garners the greatest response from your consumers? For Example discounts, free trials, free resources (e-books, seminars, detailed guides, etc.), social media interactions/contests, Product recommendations, etc.
The Time- On what time of the day, or between what time intervals are you getting the most responses from your consumers.
Your research should also include other crucial information that is exclusive to your own business and which can aid in providing you with a better understanding of the consumption pattern of your customers.
This kind of data gives you an insight into a customer’s behavioral patterns and helps you create an ideal customer profile.
It also empowers you to create hyper-personalized messaging, products, and services to attract and retain your ideal audience.
(b) Data Types
Once you have a clearly defined blueprint of the data that you have to gather, it’s time to know the various Data Forms/types that you should focus on.
- Quantitative Data
This includes any information that can be derived from the activities which have taken place between the consumer and the brand previously.
Gathering such type of data would enable you to have an insight into the manner in which a particular customer communicates with your business, reacts to your offers, conducts transactions, etc.
1. Activities on your official website: Product views, blog views, online registrations.
2. Activities on Social Media Platforms: Includes likes, shares, page visits, retweets, number of clicks on paid ads, etc.
3.Transactional Activities: Value of order, most preferred mode of online payment (debit/credit cards, net banking, COD, third party, etc.), product returns, renewal date, etc.
4. Customer Services: Through which mediums are your customers replying the most? For example e-mails, website surveys, calls, SMS, etc.
5. Subscription Data: data received from users who have subscribed to receive your resources and offers.
- Qualitative Data
Qualitative data Includes information that is collected via questionnaires, customer feedback/surveys, reviews on online platforms, discussions on social media platforms.
Gathering Qualitative Data gives you an idea the preferences of your target customers, the factors that motivate them a make a certain purchase, and the attitude that a certain customer has towards your brand:
1.Preferences: For example, if you are a clothing brand you may find out the most trending pieces of clothing that your target customers like to wear during certain situations like on a holiday, or to work or during a certain season.
2.Motivations- What is it that triggers a customer to purchase a certain product that you are dealing with? This can give you a clear idea of the exact customer need that you have to satisfy to make the sale.
3.Brand Perception: This includes the type of emotion that a consumer holds towards your brand.
For example, a consumer may perceive your brand to be:
- Descriptive Data
Unlike qualitative and quantitative data, collecting descriptions about your customers would help in identifying the context within which a customer purchases a certain.
A better understanding of the context of purchase would help you to personalize your marketing content in a much better manner for a certain consumer.
Descriptive Data generally includes gathering data on a Consumer’s
1. Lifestyle: For example the property he owns/lives in, the model of the car that he drives, whether he owns a pet or not, whether he fancies luxury goods or not, etc.
2.Habits- His hobbies, his online browsing behavior (the types of websites that he frequently visits), whether he is fond of attending events/concerts, etc.
3.Career Details: his profession, level of education, etc.
(c) The Tools
Once you are familiar with the various types of data that you have to gather, it’s time to choose smart tools that would help you in efficiently gathering this data.
Here’s a list of the different types of tools that you will along with examples.
- For Social Media Listening: Such tools would enable you to know what your target customers are saying/thinking about your brand as well as the industry you operate in.
Here’s a list of the 19 Best Social Media Monitoring tools if you want to consider further choices
- For Sentiment Analysis: These tools would provide you with an insight as to how a target consumer perceives your brand. In other words, you would be able to identify the “underlying feeling” that a certain customer has towards your brand.
Here’s a list of the 12 Best Sentiment Analysis Tools if you are looking for further options.
- Website Analytics- To know every detail about the customers that visit your website:
Recommended Tool: Google Analytics.
- Mobile App Analytics tools:
Here’s a list of the 15 Top Mobile App Analytics tools, if you are looking to consider further options.
Final Words on Data Collection:
Using Journey Analytics to Create Customer Personas
As a marketer/business owner it’s very likely that you have heard of the term “Customer Journey Mapping.”
In simple terms, Customer Journey Mapping refers to visually outlining the steps that a consumer takes throughout his purchase journey, and subsequently creating appropriate personalized marketing content based on every stage.
However, when it comes to Hyper-personalization, customer journey mapping is simply not enough.
That’s because it’s imperative for brands to have an in-depth understanding of the buyer’s journey.
This is where Customer Journey Analytics comes into play.
Unlike Customer Journey Mapping, Customer journey analytics is a fully data-driven approach. It analyses every data that is being collected across various customer touchpoints across different marketing channels.
The Outcome: With Customer Journey Analytics, a brand is able to create significantly more detailed customer personas.
This allows brands to create marketing content that is highly tailored to satisfy certain specific needs to consumers, thus leading to better conversion rates.
Implementation of Customer Journey Analytics would require a platform that has the ability to integrate customer data from various different channels/sources and provide a highly detailed persona of a customer.
CDPs or Customer Data Platforms are a relatively new name in the field of analytics software.
There’s a reason why CDPs are a much better option when it comes to Hyper-personalising a brand’s marketing content as compared to other popular analytics software like CRMs( eg Hubspot and salesforce) or DMPs (Adobe Audience Manager, Oracle DMP, etc).
Why are CDPs perfect for Hyper-Personalization?
Unlike CRMs or DMPs, a CDP provides marketers with a 360-degree view of the customer.
Secondly, CDPs have the ability to create detailed customer profiles, by gathering data from multiple channels.
CDPs also provide marketers with an option to target customers with appropriate marketing content in a real-time manner as explained earlier in the article.
CRMs, on the other hand, can only track the nature of interactions that a customer has with a company over an online platform.
Here’s a table demonstrating the functionalities of the various analytics software:
1. Personalized Recommendations
Ideal Example: Stitch Fix
Stitch Fix is a clothing startup that has perfected the art of providing Hyper Personalised recommendations to their customers.
Modus Operandi: Once a consumer visits the Stitch Fix website the brand makes sure that it collects relevant data about them, through short questionnaires.
This data generally includes things such as preferred clothing style, favorite colors, sizes, etc.
The brand has a team of more than a thousand human personal stylists, who then analyze individual customer profiles that are derived from CDP platforms after analyzing the collected data.
Subsequently, the brand delivers products to customers that are fully unique to their preferences. The customers can then try the products for themselves and buy the ones that they like.
The quality of product recommendations keeps on improving with time as the brand’s CDP platform acquires more and more data about each customer.
How Does This Strategy Help?
So what’s the most lucrative part of adapting such a hyper-personalization strategy?
After a point of time, it becomes difficult for customers to abandon your brand as they end up getting used to such recommendations with time.
In the long run, such a strategy would help you to create a highly loyal customer base.
How to use it for your Brand:
Sending out actual products for trials to customers may not be that feasible for every brand.
However such hyper-personalized experience can be easily replicated by sending out fully unique product recommendations through e-mails and push notifications.
Secondly, brands can also leverage AI in place of human experts/analysts if they are dealing with huge customer bases.
How can Service based firms and B2Bs leverage this?
Such kind of firms can provide fully customized service packages for every individual client.
Let’s consider the case of an Insurance firm that provides corporate insurance:
While deciding an insurance package for a particular client the firm can analyze various factors either through human analysts or through AI-backed software.
Some of these factors can be business type, size, number of employees, the possibility of public injury, region of operations, etc.
In this manner, the firm can provide a variety of tailored insurance packages to its clients.
These packages can also be scalable as the client grows or rebrands his business.
2. Customized User Accounts
Ideal Example: Spotify
Modus Operandi: Spotify encourages users to create their own customized playlists that are based on their choices as well as the recommendations made by the app.
Gradually users end up creating highly detailed playlists that can sometimes include up to thousands of songs.
How Does This Strategy Help?
The results are quite similar to the hyper-personalization strategy mentioned in the previous point.
Since a user invests so much time and effort to curate his personalized playlist/dashboard, he can barely think of ditching Spotify for a similar app.
In the process, many customers would be happy to pay for Spotify’s premium account membership as well.
How to use it for your Brand:
The key is to design a website/app that is highly useful on a personal level.
This includes solving user-specific problems or enhancing the ease with which a user performs certain day to day activities.
Your aim should be to make customization an intuitive part of using your website/app.
Secondly, the User Interface should encourage gradual customization where a user can spend a few minutes daily to customize his dashboard.
This will help you to lock users into your platform for the long haul.
3. Hyper-personalized Offers
Ideal Example: Starbucks
Modus Operandi: Leveraging the power of AI and CDP platforms, Starbucks managed to create a real-time personalization engine.
With the help of this, the brand sends highly personalized messages in the form of push notifications and e-mails.
Majority times, these messages are product offers and discounts that are totally unique based on the consumer’s preference and purchase history.
The coffee brand has managed to create 400000 unique hyper-personalized messages that they send to their customers.
How Does This Strategy Help?
Instead of providing generic discounts and offers to your customers, following the Starbucks model can easily land you with much higher conversions.
That’s because such offers are a bull’s eye when it comes to satisfying the unique individual needs of your target customers.
How to use it for your Brand
Other than having a CDP platform you would also require a Personalization Software in order to replicate this strategy.
As per HubSpot, a personalization software or engine is “a tool that customizes your content based on your customers’ characteristics and behaviors.”
The role of a personalization engine begins once the CDP platform derives detailed customer personas.
Subsequently, a personalization engine analyses these personas to curate tailor-made customer experiences and marketing content that can be automated through emails and push notifications.
Here’s a list of the 10 best personalization software that you can avail of for your business operations.