Personalized Marketing: What It Is & Best Practices 
Today’s customers have come to expect a highly personalized marketing experience. Data-gathering tools are experiencing unprecedented growth and with the advent of generative AI, the marketing ecosystem is facing a renaissance. In 2022 alone, 91% of Fortune 1000 companies made an investment in AI to develop their personalized marketing strategies.
Personalization is nothing new…when the barista at your local coffee shop remembers your order, they establish convenience and incentivize your return. But what does that look like at scale in an ecommerce space?
In this comprehensive guide to personalized marketing, we’ll delve deep into these questions and more as we explore the world of personalized marketing. We’ll uncover the core principles, benefits, challenges, and best practices of personalization – and ultimately discover the tools needed to succeed in today’s ever-competitive market.
What is Personalized Marketing?
Personalization has become a bit of a buzzword in the marketing space, so let’s take a minute to break down what it is – and what it isn’t.
Often, we see the term “personalization” slapped onto tools and software that use outdated strategies that don’t approach true 1:1 personalization. Many tools and software that market themselves as “personalized” often use rules-based personalization strategies.
This is when marketing strategies follow predefined rules, such as sending a follow-up email to every customer who fails to repurchase after a set number of days or retargeting all customers who have left a product in their cart.
Or, they rely on segments: grouping customers with similar behaviors together and targeting them using a one-size-fits-everyone-in-the-segment approach. Implicitly, a segmentation approach can never achieve 1:1 personalization because it reduces each customer to a single data point: the segment they belong to.
While these techniques may be somewhat effective, for the ultimate ROI and conversions, marketers are turning to one-to-one marketing. This involves tailoring every interaction and communication with a customer based on what type of offer it would take for them to convert.
Advanced personalized marketing should rely on the rich, first-party data you have about your customers to provide a genuinely tailored experience. This may sound daunting, but when it comes to the emerging world of machine learning and data science, innovative solutions to scale personalization exist.
This is exactly what OfferFit does: the automated experimentation platform uses your first-party data to determine the best offer for every single customer, which can vary by messaging, creative, incentive, channel, and timing. The AI then learns from every customer interaction and applies these insights to the next day's recommendations, so you can continuously maximize any KPI you want to improve.
Personalized Marketing Examples
Let’s illustrate the difference between the more traditional rules-based segmentation approach and true personalization.
A rules-based approach to personalization might look like:
Sending a discount coupon to a segment of customers who recently browsed a specific category on your website.
Sending the same email sequence to every customer who makes a website account.
Running annual campaigns offering every customer the next-highest tier plan.
In each case, everyone in the segment gets the same thing. True personalization takes it a step further. For example, OfferFit can help marketers and businesses:
Empirically discover which customers are susceptible to leapfrog offers vs which customers require discounts or other incentives to upgrade, and send a personalized message or product recommendation to each individual.
Use automated experimentation to find the best renewal offer for each customer and identify customers who are less price-sensitive and need less significant discounts to renew.
Send the best product offer each individual customer, with the most effective subject line, sending time, and frequency of communication.
In these examples, the recommendations are tailored to every individual customer, thus maximizing the results of the marketer’s chosen success metric.
Benefits of Personalized Marketing
If personalized marketing is not at the nucleus of your marketing strategy, it needs to be. Let’s discuss a few of the benefits of personalization.
Improved Customer Experience & Retention
First and foremost, personalization lets your customers know that you care. Personalized experiences create a strong emotional connection with customers, enhancing their overall experience and increasing the likelihood of their return.
Not to mention, it’s now become a baseline expectation. Over 90% of marketers indicate that their customers and prospects have come to expect a personalized experience. This means personalized marketing isn’t a nice-to-have: it’s now a need-to-have.
Better Engagement & Conversion Rates
Tailored content and recommendations significantly increase engagement, leading to higher conversion rates and more successful marketing campaigns. According to Epsilon, 80% of customers said they were more likely to make a purchase when interacting with personalized content.
Not only can you expect to see higher conversion rates, but satisfied and loyal customers are more likely to share your brand with their friends and family.
Boosted Revenue & ROI
By catering to each customer’s unique needs and interests, personalized marketing campaigns tend to yield higher revenue and a better return on investment (ROI). When you can tap into your customer data to uncover exactly who will be most responsive to cross-selling and upselling, you can nudge people to take the next step that results in boosted revenue.
At scale, this yields a massive ROI increase. A 2020 study found that 7 out of 10 marketers using advanced personalization saw 200% ROI as a result of those efforts.
The Challenges of Personalized Marketing
The promise of personalized marketing is clear, but savvy marketers may anticipate the challenges of maintaining privacy and investing the time and resources into securing the technology that could accomplish any of this.
Fortunately, none of these barriers are insurmountable.
Customer Data & Privacy
Marketers know that data privacy is a paramount concern for their customers. While it’s vital for marketers to prioritize protecting customer data, many software in today’s martech economy account for this.
The most sophisticated one-to-one marketing software should go to great lengths to address privacy concerns. Ensure that any personalization software you choose doesn’t collect personally Identifiable Information (PII), has security certifications including SOC-2, and partners only with organizations that have a serious commitment to protecting customer data.
This is exactly what OfferFit provides–but do your research. Not every personalized marketing software necessarily follows these guidelines, so make sure to ask about privacy practices before making any purchasing decisions.
Another challenge is finding and selecting technology that provides true one-to-one capabilities. While marketers may encounter an abundance of software that offer “personalization,” most of those currently on the market provide only basic personalization. These technologies typically use A/B testing to help marketers divide their clientele into segments and test out different marketing strategies. As established, this segmented approach is not truly personalized.
Companies seeking to implement personalized marketing strategies should look to technologies that offer one-to-one solutions. With advancements in AI and machine learning, A/B testing is as good as dead.
Time & Investment Limitations
If implementing true one-to-one personalized marketing sounds like a daunting, time- and resource-intensive effort, you’re not alone. A Gartner survey found that 74% of marketers were struggling to scale personalization efforts.
You need to learn which solutions are the best fit for each customer profile–but markets move quickly and results from one test might not apply in the future. Plus, for true personalization, you need huge data analytics teams, which can be hard to hire for.
However, ignoring personalization will cost you: companies without a personalized marketing strategy risk losing 38% of their customers.
Fortunately, the right tools exist to accelerate and automate your experimentation with 1-1 marketing – without having to hire expensive data analytics teams or build out your own solution.
OfferFit’s automated experimentation platform harnesses the power of reinforcement learning AI to make daily personalized recommendations for every single customer. All you do is let the platform know what KPIs you want to maximize, determine what dimensions to test it on (e.g. the offer, the timing of sending the offer, etc.), and then the AI takes over.
It uses first-party data to make recommendations specific to every individual customer, learn from those recommendations, and then provide new recommendations–every single day.
This not only dramatically reduces the time and resources needed to implement true one-to-one marketing but also provides incredible results. Plus, OfferFit users can directly measure the performance of an AI-driven campaign against their business as usual so they know the exact ROI of every experiment.
Best Practices For Your Personalized Marketing Strategy
Let’s get into the steps you can take to excel in the realm of personalized marketing:
1. Gather Customer Data While Respecting Privacy
When it comes to personalization, data collection is your starting point. If you want to effectively market to your customers, you should be able to predict how they will respond to your messaging.
The more data you can collect, the better insights you’ll have. Ensure that you continuously collect rich, first-person customer data through purchasing behavior, preferences, or feedback. True personalization results from analyzing all of these data points together, ultimately creating a full picture of your client and determining the most effective strategy to call them to action.
Still, it can be difficult to toe the line between earnest data collection and customer privacy. Customers today are more wary than ever of providing unlimited data to faceless companies. In fact, while aggressive data collection may provide short-term gains, this is likely to be at the expense of long-term customer loyalty. So what can marketers do to proceed cautiously?
Transparently explain to your customers what type of data you’ll collect.
Give them control to opt out if they wish.
Make it clear what value they get in return.
The trust established by a balanced, transparent data collection increases customer loyalty, leading to more opportunities for one-to-one marketing and more conversions in the long term.
2. Identify Metrics for Improvement
The next step is to isolate the specific success metrics you want to maximize. This might be revenue, conversions, ARPU, or any other key performance indicator (KPI) you’re looking to improve.
3. Determine Where & What You’d Like to Test
Once you know your metric, choose the dimensions along which you’d like to test. This might be an offer, subject line, creative, channel, cadence, or timing. Then determine where you’ll test these changes, whether it's via email, website, live chat, social media, or another message variant.
4. Scale Your Experimentation
How is it possible to continually experiment to find the perfect offer on the perfect channel for each individual customer? By using AI breakthroughs to push past the bottlenecks of experimentation. With the right platform, you empower your marketing teams to scale quickly and efficiently–leading to more revenue from happier customers.
5. Analyze the Success of Your Personalization Marketing Campaigns
As with any successful marketing campaign, you should regularly analyze results to identify areas for improvement and determine how to refine your strategy. This means you’ll want to invest in a machine learning platform that uses reinforcement learning to experimentally discover optimal actions for every unique customer.
Reinforcement learning AI learns from every customer interaction and applies these insights to the following day’s recommendations. This constant cycle of analysis and learning means more engagement, higher conversions, and an unbeatable ROI.
Personalized Marketing Tools
Here are some important tools to incorporate into your personalized marketing strategy.
Automated Experimentation Tools
The marketing world is engulfed in the buzz around AI. But it’s important to think about which specific types of AI will truly augment scalable personalization.
Many marketers turn first to generative AI (like ChatGPT). And while generative AI can do wonders in terms of interpreting customer data and composing messages and variants, it has limitations when it comes to experimentation. It can create content at scale–but will leave marketers wondering how to effectively use that content.
Experimentation, instead, requires predictive AI that can engage in a process of reinforcement learning to forecast future outcomes based on data patterns. Fortunately, automated experimentation solves this problem for marketers.
By leveraging automated experimentation tools like OfferFit to accelerate and scale your experimentation efforts, you can fine-tune your personalization strategies and see the ultimate ROI.
Customer Relationship Management (CRM)
If you’re going to be collecting a massive amount of customer data, you’ll also need a place to store it. Using a customer relationship management platform will help marketers track customer interactions, preferences, demographic information, and purchasing history.
When used appropriately, the data gleaned from CRMs can provide valuable insights in designing one-to-one interactions. Your CRM should help you design tailored communication and stronger relationships with your clients.
Data Analytics Platform
Data analytics platforms allow you to sift through a vast amount of data to gain insight into customer patterns and preferences. Traditional data analytics platforms harness the power of data to segment customers based on demographics, behaviors, preferences, and other relevant factors.
Marketers who want to move past segmentation to true personalization might look to AI, which utilizes machine learning algorithms to identify patterns and forecast outcomes. This opens the door to real-time, iterative personalization, once a pipe dream.
Data Warehousing & Management
When you’re collecting data from various sources, a data warehouse can help you efficiently store and manage information. If you’re using various platforms for collection and analysis, then you likely need a centralized repository to gather and consolidate the analytics from these sources.
Software with Personalization Capabilities
Depending on your needs, you may look toward specialized software for email marketing, personalized AI videos, landing page builders, and more. Personalization software leverages cookies, data analysis tools, and user profiling to generate personalized marketing and, ultimately, convert visitors to loyal customers.
Personalized Marketing FAQs
What is personalized vs customized marketing?
Personalization cross-references an abundance of data to create a unique set of recommendations for each customer – and then learns from past results to inform the next day’s recommendations.
On the other hand, customized marketing offers predefined options for customers to choose from. Customized marketing often uses A/B testing to segment customers and provide a set of recommendations. While this is better than nothing, it is not true one-to-one marketing.
Why is personalized marketing important?
Customers expect it. Businesses profit from it. Personalized marketing enhances customer engagement and retention, ultimately boosting revenue and conversions. By providing a tailored experience that meets each customer’s unique needs and understanding their purchasing behavior, you get the results you’re looking for.
What are some personalized marketing ideas?
Personalization can (and should) happen at every level. This might look like:
Personalized product recommendations: In today’s highly competitive digital landscape, personalized product recommendations will yield higher average order values, reduce cart abandonment, and increase cross-selling and upselling opportunities.
Dynamic email content: Go beyond simply using someone’s name in an email! (In fact, an OfferFit client discovered using names in subject lives actually lowered rates.) Instead, try using responsive designs that adapt to various devices and screen time, showcase complementary or higher-value products based on past purchasing behavior or browsing history, and prioritize sending emails at the right day and time.
Personalized videos: Extremely personalized videos can address each recipient by name, call out specific purchases, suggest specific upsells and cross-sells, and much more. Personalized videos lead to more engagement, higher conversions, stronger customer loyalty–and a better bottom line.
Personalized offers: Sending out tailored promotions, discounts, or incentives to your audience based on their unique characteristics, behaviors, preferences, or past interactions will resonate with customers on a personal level. When customers receive offers that align with their interests, they’re more likely to engage. Read: higher conversion rates.
Targeted advertising: When you tailor advertisements and promotional messages to each individual, you reach the audience most likely to be moved to action. And it works: research indicates that targeted ads boost click-through rates by 670%.
There are plenty of ideas for how you can begin the journey of personalized marketing. But no matter what route you take, the key is to ensure that you are truly marketing to each customer–and ready to experiment to see success.
Improve Your Personalized Marketing Campaigns
While personalization may be a buzzword, 1:1 marketing is the strategy that will transform your business and lead to maximum conversions and engagement. And today’s lifecycle marketers are closer than ever to scaling personalization thanks to the rapid developments of AI.
To truly maximize your personalized marketing campaigns, leverage the transformative power of automated experimentation tools like OfferFit. OfferFit’s AI uses reinforcement learning to experiment and continuously improve.
The AI learns from every customer interaction and applies these insights to the next day's recommendations so you can capture the full value of your first-party data, finally understand why different offers resonate with different customers, and ultimately boost your profits.
Ready to experience one-to-one personalized marketing?
Ready to make the leap from A/B to AI?