What is Personalization?
Personalization is the practice of creating personal interactions and experiences for existing and prospective customers through the use of digital marketing technologies to grow these customers into your best customers. A somewhat ubiquitous term, personalization is often used blanketly to describe segmentation, targeting, and optimization techniques, while purists equate it to 1-to-1 personalization or individualization.
Types of Personalization in Marketing
Personalization – also known as personalized marketingor one-to-one marketing – is achieved through the deployment technologies and strategies that deliver personalized customer experiences. Over the years, as technologies have improved and strategies have been refined, users have discovered more opportunities to deliver improved customer interactions.
With personalized customer experiences, each specific user is served dynamic content using a machine learning algorithm that leverages behavioral targeting and predictive analytics. The personalization technologies used may vary based on the type of digital property, user intent, and the desired conversion action like an ecommerce sale or lead.
Segmentation or Rule-Based Personalization
A segmentation-based approach requires identifying a subsegment of people within your larger audience in which you can target a specific experience. A good example would be targeting loyalty customers with specific messaging that you would not want to show to non-loyalty visitors.
The aim of segmentation is to produce better business outcomes by delivering more relevant customer experiences that encourage the customer behavior you want – increase conversions, revenue, etc.
One of the challenges of segmentation-based personalizationis that in order to produce ever greater outcomes, you have to target smaller and smaller segments. You will eventually hit a plateau, where marketing spend to manage the segments and all the creative for them is greater than the return.
That being said, segmentation-based personalization can produce substantial results if your segments are large enough and your experiences tailored well enough.
The term “1-to-1 Personalization” is derived from the term “personalization,” but denotes a focus on delivering optimal experiences to individuals rather than customer segments. The term “Individualization” carries the same connotation.
1-to-1 personalization technology aggregates a user’s behavior such as site visit history, browsing activity, geographic location, type of device, and other data. The artificial intelligence personalization engine analyzes the aggregated data and pushes the best, most relevant experience for each specific user.
1-to-1 personalization is best used to achieve business outcomes when the best experience for each user is difficult to predict ahead of time. The machine learning algorithm can analyze each user, track how each user behaves, and make adjustments very quickly.
1-to-1 Personalization describes the practice of delivering the optimal experience for each individual customer or prospective customer using all the data available about each person. Deployment of hyper-personalization requires rapid data aggregation and analysis, cross-channel deployment, and machine learning optimization.
The term “1-to-1 personalization” is derived from the term “personalization,” but denotes a focus on delivering optimal experiences to individuals rather than customer segments. The term “Individualization” carries the same connotation.
1-to-1 personalization technology aggregates a user’s behavior such as site visit history, browsing activity, geographic location, type of device, and other data. The artificial intelligence personalization engine analyzes the aggregated data and pushes the best most relevant experience for each specific user.
Hyper-personalization is best use to achieve business outcomes when the best experience for each user is difficult to predict ahead of time. The machine learning algorithm can analyze each user, track how each user behaves, and make adjustments very quickly.
Examples of Personalization in Marketing
Email personalization is a great way to connect with customers. However, this must extend beyond the subject line. If your business caters to many different clients, your organization must consider how to deliver the right message to the right user. This can be done by segmenting your email list (for example: by job function, company type, or user demographics). However, the most effective way to deliver the right content is through personalization. Using machine learning, you can target users based on browsing history, geography, and location. The result is more personalized results instead of guesses based on flat personas.
Personalized Web Pages
Increasing engagement is an important goal for marketers. Customers who are between their first and second purchases pose a higher riskfor not making another purchase. You can mitigate this risk through personalized web pages, which are a chance for your organization to connect with customers through dynamic content, recommended products, and updates based on location and weather.
Product recommendationsare used widely within retail ecommerce and other industries. The recommendations are determined by algorithms that analyze customer behavior to curate products that may be of interest to the customer. A user is shown related products, offers for specific product categories, or similar purchases by other users. The data to create personalized content is gathered through a variety of ways:
- Previous website sessions(pages visited)
- Technographic profile
- User generated data (account settings, surveys)
- Behavioral targeting
- User data generated offers (birthday sales)
- Real-time data (geographic location, time, day)
The Benefits of Personalization and One to One Marketing
1. Boost ROI
Personalization boosts revenue by increasing conversion rates across the board. Gartner found that organizations who invested in personalization were likely to see their investments pay off, since consumers responded positively to these efforts. 88 percentof those surveyed said they wanted to see some sort of personalization from brands. However many brands are still failing to deliver on the amount craved by consumers, which can give your company an advantage should you choose to act.
2. Increase Engagement Rates
The ability to identify customers is a game changer according to our EQ Reports. When retailers focus their efforts on accumulating the right data on their consumers, they can create better experiences. Personalization that combines the data you already have with the in-session analytics leads to a 45 percent increase in engagement rates.
3. Connect with Customers
Engagement should be a key metric for ecommerce companies. The more engaged your clients are, the more likely it is that they will convert. Increased engagement leads to more loyalty which has a direct impact on the bottom line.
- Increased AOV – Customers who have made between two to ten purchases have a higher AOV of 4.5 percent compared to first time buyers.
- Increased Brand Loyalty – According to Gartner, customers want to see personalized content and many will consider switching to a competitor should these needs not get met. By failing to meet this demand, you could be missing out on opportunities to connect with your customers and driving them to your competitor.
4. Make better recommendations
Product recommendations are a valuable tool for ecommerce companies, but where many retailers struggle is providing the right recommendations. Solving this dilemma can have big payouts for organizations. Clients who add a recommended product to their cart have a 33 percent higher AOV. And even when product recommendations encourage even a little bit of engagement, purchase rates go up by 70 percent. Making the right recommendations can have a real impact on your bottom line, while driving customer loyalty.
5. Personalized Experiences Compound Over Time
Personalized experiences deliver more value as they accumulate. Conversion rates jump up by 1,859 percent between the first personalized experience and the tenth, while add-to-rates see an increase of 679 percent. Having these ecommerce metrics skyrocket means better results for your bottom line, so organizations should take the time to make sure these experiences are not just one off tactics.
Targeting and Personalization
Targeting and personalization allow you to reach your target audiences. Targeting does this by segmenting users into lists based on job titles, demographics, or other attributes. Personas are often used, which often feature generalizations, resulting in some limitations when seeking to target their core audience. Personalization on the other hand, focuses on the individual. It can incorporate their preferences, location, and shopping history to deliver more relevant messaging. By swapping traditional targeting approaches with personalization, your organization can better connect with consumers.
Monetate Personalization Engine
The Monetate Personalization Engine’s powerful decisioning capabilities can make complex decisions in real-time. Our machine learning algorithms decide which data is most relevant and which action will have the highest probability of achieving a specific outcome such as increased average order value (AOV) or conversion rate.