How to Use AI to Segment and Personalise the Buyer Journey

Segmentation and personalisation are essential in the modern GTM landscape. Every customer, from B2B buyers to B2C consumers, now expects companies to tailor their sales, marketing, and even customer service strategies to their specific needs. 

According to McKinsey, around 71% expect higher levels of personalisation, and 76% are frustrated when they encounter a generic experience. Traditional segmentation strategies, which involved using insights into demographics, psychographics, and behavioural data, have helped companies deliver higher levels of personalisation to their consumers. 

However, many organisations still struggle to scale their strategy, as exceptional segmentation depends on your company’s ability to collect, analyse, and leverage huge volumes of data effectively. Fortunately, AI could be the solution, driving a new era of GTM personalisation.

The Traditional Challenges of Segmentation and Personalisation 

Generic and untargeted campaigns don’t cut it in today’s world. 80% of consumers exclusively do business with companies they know will deliver a tailored experience. Unfortunately, dividing customers into segments, and personalising each stage of the buyer journey hasn’t always been easy. 

To succeed, companies need to overcome challenges with:

• Manual data analysis: Traditional segmentation requires companies to collect data from numerous sources, from websites to surveys, and convert it into actionable insights. It’s a time-consuming process, which can suffer from numerous errors. 
• Basic data source limitations: Relying on basic data sources, like demographic information, only provides a limited image of customers. It can be difficult for companies to access and utilise more in-depth data, and real-time insights, without intelligent tools. 
• Growing data sets: As the amount of data generated by companies and consumers grows, traditional data storage solutions struggle to accommodate scaling data sets. Plus, extracting valuable insights from larger volumes of data becomes more complex.

Artificial intelligence and machine learning solutions provide tools that can help, streamline the segmentation process, and help businesses deliver more tailored experiences.

Using AI to Transform Customer Segmentation

The first step in delivering personalised experiences for most companies is dividing customers into segments based on crucial insights about demographics, behaviours, and more. 

AI platforms make it easier to analyse vast amounts of data, track information in real time, and automate the segmentation process. They can support the visualisation of customer groups based on advanced data science techniques, and even process and clean data more effectively. 

Companies can use AI in the segmentation process in various ways, such as:

• Analysing data sets: Machine learning algorithms and deep learning models allow systems to analyse extensive data sets more efficiently, and highlight patterns, relationships, and trends. This paves the way for precise customer segmentation decisions. 
• Gathering more advanced data: AI solutions equipped with natural language processing and understanding capabilities can shed light on dark data. They can draw insights from human language, track sentiment, and even recognise customer intent. 
• Automating segmentation: AI tools can automatically organise new contacts and leads into segments based on pre-defined rules. They can analyse the characteristics of a customer in seconds, optimise customer profiles, and rapidly build segments without human input.

Using AI to Personalise Buyer Journeys

Alongside helping companies to improve and optimise the segmentation process, AI solutions can also assist with the development and delivery of personalised experiences throughout the customer journey. With AI tools, companies can:

• Rapidly create personalised messages: AI and machine learning tools, as well as generative AI solutions, can draw data from your ecosystem to create personalised content for consumers. They can predict the type of content that will engage specific groups or individuals, and even determine the best time to send messages to consumers. 
• Enhance the website experience: AI solutions can make websites more dynamic and “bespoke” based on the needs of specific groups. Dynamic website applications can alter messages and promotions instantly, based on the browsing behaviour of customers, previous purchasing histories, and even their location.
• Improve sales recommendations: When consumers are in the “consideration” stage of their purchasing journey, AI solutions can help them find the right products for their specific needs. Models can learn how customer behaviours and characteristics influence their needs, and recommend specific products to each consumer group. 
• Transforming service experiences: When a consumer makes a purchase, AI can help to enhance the post-purchase experience. AI assistants can help with personalised onboarding processes, showing customers how to leverage tools to achieve specific goals. They can track sentiment throughout the customer journey, and alert customer service reps when the risk of churn increases. They can even identify your most valuable advocates and return buyers.

How to Use AI to Personalise the Buyer Journey

90% of leading marketers say personalisation significantly contributes to business profitability. Already, countless companies are embracing AI and machine learning tools, to help them take their personalisation and segmentation efforts to the next level. However, there are a few steps organisations need to take to ensure their initiatives are successful. 

Step 1: Ensure You’re Collecting Relevant Data

AI solutions for personalisation and segmentation rely on access to large volumes of data. The data you use to train and support your AI model will depend on your specific goals. For instance, if you’re using AI exclusively for segmentation, you’ll need to ensure you have plenty of data to share about your consumers, their preferences, and buyer journeys. 

If you’re using AI to optimise your messaging strategy, you’ll need to combine that data with insights into the success of previous content campaigns, and competitor statistics. Ensure you’re collecting data from as many sources as possible to create a holistic “database” for your AI system.

Draw data from your CRM (Customer Relationship Management) platforms, marketing tools, websites, email campaigns, and even your contact centre. Connect qualitative data insights into the landscape with surveys and one-on-one interviews with your target audience. 

Step 2: Leverage and Optimise the Right AI Models

Once you have the right data sets, the next stage is choosing an AI solution that can support your personalisation goals. Different types of AI models are designed for different purposes. Some AI bots are specifically tuned to delivering customer service, while others can proactively reach out to consumers and support your sales teams. 

There are even AI solutions that focus specifically on the marketing landscape, creating content for websites, email, and social media campaigns, or delivering dynamic website experiences. Whichever solution you choose, make sure you can optimise and customise it based on your specific needs. 

You should be able to infuse your AI model with your proprietary data, so you can deliver truly bespoke (branded) experiences. Additionally, you’ll need to ensure your AI solution can integrate with your data sources and existing systems. This will ensure the solution can constantly draw fresh insights from your business, and evolve over time. 

Step 3. Find the Right Human/AI Balance

Over 80% of companies have already adopted AI in some format, and the demand for intelligence is constantly increasing. While it’s tempting to leverage AI in all aspects of your GTM strategy as much as possible, to boost efficiency and minimise costs, balance is crucial. 

Innovative AI solutions can help with segmenting customers, delivering personalised experiences, and collecting data. However, they can’t accomplish everything. You may still need to edit AI-generated content to ensure it resonates with your target audience.

You’ll still need a valuable human sales team to help convert leads into customers with tailored pitches and guidance. Plus, you’ll need to ensure you can still deliver a human level of service, with empathy and compassion, when consumers need it. 

Remember to Monitor and Optimise

Finally, ensure you’re constantly monitoring the results of your AI initiatives, paying attention to conversion rates, engagement, and retention. You’ll also need to pay attention to any feedback you get from customers, watching how their satisfaction rates change as you implement AI solutions.

Optimising Journey Personalisation with AI

Artificial intelligence, machine learning, and deep learning solutions represent an incredible opportunity for companies to optimise their approach to segmentation and journey personalisation. The right tools can save you significant time dissecting your customer base into specific groups for highly tailored sales, marketing, and service campaigns. 

Just remember to ensure that your AI strategy doesn’t involve eliminating the “human being” from your personalised approach to GTM this year.