Introduction
Individuals of this generation are less inclined to follow the crowd or identify themselves as a part of a specific community. Instead, they are more weighed into the ideology of individualism or uniqueness, meaning they love to be valued and feel special.
From a marketer’s point of view this cultural shift should be highlighted by giving more attention towards the audience rather than bringing their attention towards the brand.
Cutting through the noise in a space bombarded with data can be quite challenging, yet analysing this data is an essential step to achieve broader marketing objectives.
In this blog article, we will explore a marketer’s perspective into the personalization approach and how to strategically incorporate hyper-personalization into the overall marketing strategy.
What is Hyper-Personalisation?
Hyper-personalization is the upgrade of the traditional personalization approach which does not limit to data based on past behaviours and preferences but by leveraging advanced algorithms to capture data in real time which results in a more advanced customised experience speaking to customers on an individual level over a segmented audience.
This approach, identified as the ‘segment of one’, builds thoughtful touch points that resonate like recommending ‘how to videos’ or content that will be different from individual to individual.
For example, if members A and B have enrolled to a language learning application – and both prefer reading as the best strategy for productive learning, the traditional personalisation strategy will recommend some of the highly rated stories.
But when it is Hyper-personalisation, tailoring becomes more granular. With the use of AI a deeper analysis into each member’s goals, performance, preferences and will be identified to provide content that best suits each one individually.
And after, depending on the member’s performance the app is able to adapt and provide new recommendations keeping each member challenged at their own level.
Hence, Hyper-personalisation differs from personalisation on the level of customisation and the use of real time over historical data which supports in creating contextual and a more relevant experience.
How does Hyper Personalisation step into the Personalisation Approach?
The approach to converting a customer involves more than sending a thank you email with their names or newsletters on a trending topic.
The goal of a personalisation strategy is to enhance the touch points of a customer journey by providing personalised experiences informed by data on customer preferences and behaviour. The objective is to address the audience’s challenges at the right time and at the right place.
Thereby, collecting this data is the key factor in determining the success of the whole strategy.
63% of marketers have observed that personalization enhances customer interactions, resulting in higher conversion rates.
Traditionally, personalization was only focused on gathering data based on recent search history, relying on static data, broad segments highlighting the past interactions with the brand.
However, this approach is deterring and does not remain a convenient or a stable method in the future. The mind of the consumer is changing so fast that the data captured by a past interaction is no longer considered insightful when identifying his/her current behaviour which for example has been influenced by modern trends.
Hyper-Personalisation in the B2B Arena
In a B2B scenario the need for a Hyper-personalised strategy becomes a high priority. Clients are more likely to trust and invest in a partner who can understand their unique challenges and address solutions in an effective way. Therefore, the more focused the approach is the more likely it boosts client engagement.
Understanding the concept of hyper-personalisation and how to implement it is crucial for staying relevant throughout the process. Too much data-driven customisation will keep leads engaged but deter the overall buyer experience. For the challenging leads, a solid brand strategy is not enough alone, the brand image also plays a significant role. A strong and trustworthy brand has a higher chance of success.
Clients will base assumptions on security concerns such as encryption standards and how data is handled. Hence, over relying on automation can make interactions raise negative concerns on client trust. However, by leveraging hyper-personalisation a balance between technology and human interaction can be achieved, enhancing authenticity and credibility when connecting with leads.
Hyper-personalisation and Lead Generation
Why is it essential to have a lead scoring system? (backlink)
Assigning lead scores be it positive or negative – the lead scoring supports the B2B market by allowing to identify which leads are most likely to convert. For this purpose, handling a chunk of data is vitally important.
Hence, with the use of Hyper-personalisation and lead scoring optimising for lead generation efforts become more effective supporting a more refined approach to lead management.
Once the lead is segmented as hot or cold leads, content can be tailored accordingly. For a lead with a lower score, an educational piece of content would be more valuable than tailored product recommendations, case studies or e-books which is more suitable for a lead with a high purchase intent.
Hyper-personalisation supports this system by fine-tuning the way content is pushed to each lead by focusing on their individual behaviours, interests and needs supporting it to be more relevant and appealing to the ideal lead.
7 Data-Driven Strategies for Hyper- Personalisation in Lead Generation
Focusing only on the highly converting leads is more efficient than forcing long hours of effort on all leads. Attracting these right leads is an art, but when taking the right messaging, marketing channels and right data into consideration high-quality leads can be driven.
- Customer profiling: identifying the ideal audience
The initial priority is to identify the target audience and segment them into the right buyer groups. Research can be conducted by customer insight analysis tools, market research and other software for automated analytics.
With the use of hyper-personalisation analysis of data are revolutionised in the following ways
- General analysis of data: Analysis of data using mathematical and scientific techniques.
- Advanced analytics: Data captured with the use of emerging technology such as AI and ML (Machine Learning)
- Augmented analytics: Advanced data capturing with the use of AI and ML to assist data gathering, preparations and other analytical tasks.
Type of data to collect:
Demographic information: This will give the basic idea to the customer information with a variety of contexts from age, gender, location, careers etc.
Interests: What are their goals? In what product or service features do they find value? This category will give insights into how and where we can promote our product.
Pain points: The challenges they face is a highly critical factor when evaluating an exceptional content strategy. The marketing message will be tailored to reaching this objective.
Purchase behaviour: The frequency of purchasing and product/service usage is another valuable insight into determining how to add value.
- Lead Categorisation
The next step after defining the customer profile is to categorise which leads fall under the Marketing Qualified Leads (MQLs), and Sales Qualified Leads (SQLs).
MQLs are the leads that have better chances of converting while the SQLs are leads that have a high buying intent with an increase in the potential to convert to paying customers with lead nurturing.
MQLs
With the use of closed loop analytics marketers can analyse customer data across multiple platforms like Google analytics and CRM. By identifying the current status of the customer in the customer journey, marketers can attain a clear understanding on which actions lead to conversions and optimise them accordingly.
For this purpose, following might be key metrics to track for efficiency.
- Website traffic
- Content shares
- Bounce rates
- New vs returning visitors
- Social media engagement
- Total conversions
Considering the data gathered based on the above criteria prospects can be given values to a process; lead scoring.
SQLs
A positive MQL moving down turns into an SQL in the buyer journey.
At this stage, leads have a higher chance of approaching you as they see the product/service offering as a solution that talks to their pain points. However, defining a SQL depends on the length of a sales cycle which can be differentiated depending on factors such as size of the sales team, previous job experience.
Hyper-personalisation plays a vital role in nurturing these prospects with the right content strategies.
- Capturing data with web forms
50% of companies state the use of web forms for lead generation as the highest converting lead generation method.
It is common that shorter the lead forms the higher the chances are for prospects to complete the form. However, the drawback is that this form will be limited to only the basic information such as first name, last name and business mail. In some cases, this data might not be enough.
Therefore, prioritising on a software that offers inbound lead enrichment is a solution that comes along. Hence, by including more details such as work experience, education, job title can be a better customer profile fit.
As a result, sales outreach and lead nurturing campaigns can be further personalised without the use of lengthy forms. From a marketers perspective, a quote (RQF) form is more valuable as it allows to customise an accurate estimate for each customer.
- Structuring data
Problematic data which is data that is duplicated, missing, incomplete, incorrect, inconsistent or anything in the category that meets irrelevance affects the quality of lead data which as a result drives a lead generation strategy.
By conducting an audit, potential issues that affect the accuracy, reliability and quality of your data can be identified in order to ensure clean data.
To conduct the audit, start by identifying the data sources and checking potential errors including data gaps and outdated information. Data validation tools act as a great tool for such workflows in these key areas:
- Include additional data points like industry, company size, and location.
- Utilise standardised data formats (eg: dates, currencies, names etc.)
- Merge or eliminate duplicate data records.
- Impute missing values where appropriate.
A reverse ETL is recommended to support the streamlining of data flow from centralised warehouses directly to operational systems and SaaS tools. As a result of this data driven process there is an increase in the likelihood of creating hyper-personalised experiences for potential customers.
- 2. Choosing the right tech stack
A hyper personalised lead generation uses cutting-edge technologies such as advanced data analytics, artificial intelligence, machine learning and marketing automation platforms. Choosing a software based on the degree of complexity and efficiency of features is recommended.
- Create content that resonates with the target audience
A hyper-personalised approach delivers content catering to the interests and pain points of leads within the lead cycle.
For a lead who has already interacted with the business by filling a certain form or opening an email could reflect a sign that the particular prospect is actively looking out for a solution. In this case, case studies, white papers and other value added material will support them to walk down the marketing funnel.
Type of contents can include; blog posts, podcasts, newsletters, case studies, ebooks, webinars.
- Prioritising an inclusive user experience
To create an inclusive lead generation strategy – an in-depth segmentation of specific populations such as people with disabilities is found essential. This identification helps in not limiting the user experience journey to a specific crowd only.
Considering the above challenge, below are some key points to consider:
- Create accessible website design navigation: By adding semantic HTML, alt text for images, intuitive navigation, video captions and zoom capability for compatibility with assistive technologies the website enhances the user experience for individuals with disabilities.
- Developing content that is accessible to everyone: Create content by paying attention to details in font choices, colour schemes and contrast ratios. This strategy promotes user readability and retention.
- Optimisation of lead forms for accessibility: Focus on clearly labelling the fields in a form to provide concise instructions and easy to understand error messages where ever needed. This facilitates the navigation process and the compatibility for screen readers broadening the potential audience.
- Diversify customer touch points and marketing channels: Different individuals have different preferences when it comes to offering interest, some might prefer a chat bot over email messaging. Thereby, offering a variety of channels for people to get in touch with creates space for a better engagement rate.
What to Note for the Future of Hyper-Personalisation
Studies show that 66% of consumers have expectations for brands to have a better understanding of their needs and 97% of marketers are increasing personalisation efforts in achieving this goal.
Hyper-personalization is a strategy that organisations must continuously adapt, as approaches will inevitably evolve over time. Shifts in consumer lifestyles, smartphone usage, and shopping trends will drive marketers to explore new techniques and strategies. With the adaptation of AI and ML data collection and processing will be much improved with tailoring, faster and advanced options in the coming years.
Although today’s successful strategy may not remain optimal, hyper-personalization will be at the core of any effective marketing approach.
Conclusion
Focusing on individual needs and behaviours over traditional segmentation is the future approach in the marketing. By leveraging advanced technologies such as AI and ML real time data can be achieved helping brands to create relevant and customised experiences at every touch point.
In the B2B market, personalisation can foster stronger client relationships and lead generation by allowing businesses to target qualified leads with precision.
Excessive data-driven customization can deter the customer experience if it feels intrusive or sacrifices brand integrity. Trustworthiness, data security, and an inclusive user experience are crucial to keeping clients engaged and building long-term loyalty.
Adapting to evolving consumer trends, experimenting with new approaches, and refining personalization tactics will enable brands to stay relevant and competitive in a dynamic digital landscape.
