The digital era has shown that generic messages can no longer attract attention. Customers have become more sophisticated, demanding messages that consider their own needs, preferences, and environment. Customization has become the benchmark. However, how do you add a personal touch to tens of thousands, hundreds of thousands, or even millions of users?
The solution is in utilizing AI-enabled variables, which are intelligent, dynamic elements in your outreach plans that personalize messages based on information understanding. AI variables help you to scale communication without losing relevance.
This guide will address the concept of AI variables, their applicability, and ways to leverage them to personalise outreach to various industries.
Understanding AI Variables
The concept of AI variables is a data-driven approach that automatically inserts your outreach messages. They are basically artificial intelligence-enhanced versions of a simple merge tag (e.g., {{FirstName}}), and they can adapt to user behaviour, preferences, and context.
A personalized one would sound like this: Hello Sarah, as you watched our email automation tools last week, here is a custom guide to increase your email ROI.
The AI variables can utilize CRM data, browsing history, purchase behavior, engagement metrics, and geolocation to adjust the tone, content, and recommendations. You can get more from lemlist’s AI variables.
Why Personalisation at Scale?
McKinsey concluded that the companies that are masters of personalisation make 40 percent more money than the average competitor. However, it is not possible to compose different messages to thousands of contacts manually. AI variables open up to the capacity to:
- Automate relevance: Every message seems to be created specifically for the recipient.
- Increase engagement: The user will feel understood, leading to higher click-through rates and open rates.
- Convert more customers: Recommendations based on individual preferences are more effective.
- Minimize churn: Continued, unique communication fosters trust and loyalty.
Important Applications of AI Variables
These are effective AI variable applications in your outreach strategy:
Behaviour-based personalisation
The AI variables can recognize the engagement of the contact with your site, app, or emails. For example:
- Abandoned carts receive a customized message tailored to the items they added to the cart.
- There are more personalized recommendations for visitors who frequently visit a particular type of product.
Place-delivery and time-sensitive message
Appearances of being local and time-sensitive can be achieved through the use of AI variables, taking into consideration geolocation. Examples:
- Wishing you good weather in Toronto, here is a seasonal offer just for you.
- It’s 8 PM in your time, which means it’s an ideal time to utilize a 5-minute tailwind to boost your productivity.
This will be a humanised brand and get more affection.
Stage of customer journey
AI variables allow you to define outreach by lifecycle stage: lead, active user, dormant customer, or loyal advocate.
- The New sign-ups are greeted and provided with a learning tool.
- Incentives for upgrades apply to long-term users.
- Inactive users are reactivated with customised incentives.
Role and industry-specific messaging
Artificial intelligence can modify messages based on a job title, industry, or company size. This works particularly well with B2B outreach.
For instance, as a Finance Director of an expanding SaaS company, you may be interested in using our reporting dashboard, which can be used to plan monthly. It suggests that you are aware of their specific areas of concern, rather than the overall benefits.
Emotional similarity of tone
High-level AI variables are capable of examining historical interactions and the style of communication preferred to modify the tone and style of communication, such as formal, playful, or encouraging.
Example:
- Formal attitude by the lawyers.
- An informal, joking atmosphere exists between the founders of startups and designers.
Such fine-tuning enhances the reception and perception of your message.
What to Do to Personalise with AI
One could be neither a data scientist nor a tech giant to use AI variables. This is an easy road map:
Clean and divide your data
The starting point is, of course, good customer data, including CRM fields, behavioral data, location, etc.
Using the appropriate tools
Dynamic AI personalization is now available on platforms such as HubSpot, Salesforce, ActiveCampaign, and various AI-powered email and writing tools.
Stipulate your personalisation rules.
Specify rules that define variable behaviors (e.g., “Considering the variable product interest = CRM tools, then display CRM feature banner).
Test and optimise
Variant A/B test messages with and without AI variables. Monitor open rates, CTRs, and conversions.
Conclusion
The future of interacting with customers lies not only in automation but also in empathetic automation. The secret to sending personalised, relevant, and timely messages at a large scale lies in AI variables. They enable sending messages at scale while maintaining a human-like and non-robotic approach.
The use of AI-powered personalisation in email marketing, cold outreach, onboarding, and customer success will enable companies to stand out and establish stronger connections. The world today is filled with noise, and therefore, relevance prevails.
