Sergey Nivens - stock.adobe.com
If companies want to compete with others in their industry and improve CX, they need to embrace personalization.
Personalization, when done right, enables messaging to break through the crowded landscape. Brand leaders such as Amazon, Netflix and Spotify set expectations for consumers in terms of customer experience, as well as marketing and what engages -- and truly breaks through the clutter. One-size-fits-all messaging or messaging without a target audience is ineffective.
Personalization is key for the success of organizations and companies should expect to see more of it in the future.
Why personalization is a must
In its early form, organizations used personalization to customize a service or product to accommodate specific individuals, market segments or customer personas for a brand. Personalization has evolved in its application as a marketing tactic. Personalization has also become a critical element in social media and recommender systems.
Personalization brings a variety of benefits, including:
- improved customer satisfaction,
- increased digital sales conversion;
- better branding; and
- improved website metrics and advertising.
Many people have received a Netflix message that reads: Watch one of our top picks for you. With this personalization, Netflix wants to continue to get to know its customers and their viewing habits better. Customers expect and demand personalization from organizations they interact with. Customers are savvy and well-informed, and they know they don't have to accept nonpersonalized experiences. They are aware that in many cases, personalized products and services are options, and they are willing to pay for those experiences. Customers expect the company to figure out a way to personalize their experiences, such as using customer data to get to know them.
Ninety-one percent of consumers said they are more likely to shop with brands that provide offers and recommendations relevant to them, according to Accenture. Organizations are expected to move beyond the customers' basics -- such as name and date of birth -- and their purchase history and anticipate future needs.
A personalized experience makes a customer feel understood. For example:
- when a streaming service, such as Amazon or Netflix, offers recommendations based on previous viewing activity; or sends reminders that the viewer left in the middle of a movie; or
- when a customer receives a reminder that he or she hasn't completed a purchase on an e-commerce site.
These sites use recommender systems to aid in personalization development. These systems provide suggestions based upon a set of algorithms. The system uses a customer's past viewing or shopping habits to package and present recommendations to the customer as possible next steps. For example, the system may provide a movie recommendation for what the viewer may want to watch next. The viewer feels as though the company understands their wants and needs, which results in a better customer experience.
Customer experience has become a differentiating factor for companies. Customers expect businesses to provide exceptional CX, so if they don't deliver it, they won't be able to keep up with their competition. Personalization enables organizations to have more meaningful interactions with their audience and makes the customer's decision to purchase easier.
Consumers receive an average 6,000 to 10,000 marketing messages per day, according to PPC Protect. To increase engagement, organizations must break through that noise. These messages often result in the company casting a wide net and seeing who accepts the message; more often than not, the messaging is generic and ineffective. The less relevant a marketing campaign is to a customer, the lower the response rates will be.
Take care when using customer data
Organizations must use the data at their disposal to create a meaningful experience for their users. Customers are often willing to share their personal data with companies if that means they receive a direct and less expensive experience. However, while some customers are willing to share their data, many have growing concerns about data privacy.
When companies execute marketing campaigns correctly, customers feel as though the business appreciates their time. However, when the company incorrectly executes a marketing campaign, customers tend to ignore messages and recommendations and perceive them as clutter. Companies might not always get it right, but as technology advances and customers exchange more of their data with companies, the personalized experience continues to develop.
Where personalization fits in
The COVID-19 crisis demanded organizations to move past generic messaging, and toward personalized experiences that show customers that there are humans behind the marketing messages. Many people faced financial and personal challenges due to the pandemic, so it was important for companies to adjust their strategies from strictly making a sale and recognize that people may not be in the position to buy in that moment. COVID-19 also forced customers to seek out brands and experiences that convey empathy and understanding.
Personalization is essential for brand marketers and public relations and spans the customer journey, influencing brand awareness, brand loyalty and lead generation. Marketers can establish a real connection with customers by knowing who the customer is, what they want and what their preferences are, and use this information to promote messaging and offers.
How AI assists in personalization
AI will affect personalization in various ways within customer experience and marketing. Organizations that don't incorporate tactics or approaches to address personalization will find their gap widen versus their competition.
Here are five ways AI may affect personalization.
- Create intelligent personas. Organizations can begin with initial data -- such as demographics -- and then add in behavioral data and other aspects -- such as activity and even third-party data -- to identify where in the journey their users are to understand their requirements. Businesses can collect this data by asking customers directly, tracking user data and adding existing data into the mix. This additional data expands the understanding of the customer personas and details who they are and what they need. Adding this combined customer data to AI approaches -- such as machine learning, data mining and natural language processing -- can inform companies on where, when or how the customers want a business to personalize their experience.
- Drive content creation. While it's impossible to create individual, personalized emails for every customer, there is an alternative approach. Organizations can use AI classification algorithms to capture a large number of data points describing a customer's behavior -- such as emails that the customer opened and links that they previously used, past purchases and similar customer types -- and select the best content for each individual.
- Optimize mobile. Companies that create content suitable for mobile devices helps create a point of differentiation against the competition. AI-powered personalization can help organizations bring data together across multiple sources into a single view of the customer. Chatbots can also improve communication with customers and help customers with purchasing products while enabling them to use self-service for their online needs.
- Enable use of deep data. For organizations with large amounts of customer data, marketers can wield the power of in-depth data above large chunks of customers in their database. Companies can use that data to provide a breakdown of customer preferences and buying styles to create marketing profiles, personas or buyer segments. Businesses can also use their customers' online history to determine who their key customers are, along with their buying processes. This approach to data may be enough to get an organization started. A company should pair behavioral-based data such as habits and preferences with a typing tool -- also known as a segmentation algorithm -- to provide additional customer insight. This type of data helps determine real-time decisions, such as when the company should send other relevant content or offers; and how these other items will benefit them, for example, by solving or addressing a need.
- Bring algorithms into the mix. Personalization has moved beyond segmentation to the use of algorithms. Brand leaders are using AI through recommender systems to provide customers with more personalized experiences.
Within online retail, companies use AI to improve purchase recommendations, also known as content filtering. Based on customer preferences, the algorithms can be designed to use those preferences and customer behaviors to recommend products, cross-sell items and increase conversion. Businesses can also use AI in retail to share targeted content in real time, as well as to determine when to send follow-up offers after the customer is finished shopping.
Content-based recommendations are another type of recommender system. When users or items have similar profiles or characteristics, the systems recommend an item based on that match. When a user selects a music station, the system adds songs that match the station's attributes to the playlist.
How personalization will change
Companies that want to provide a more personalized experience may need to dust off some existing persona and segment strategies to determine if they still hold or need updating. Here are some examples of how personalization will change:
- Companies will continue to focus on understanding the person behind the purchase, the individual behind the issue and the employee behind the number.
- The goals of segmentation and personalization remain the same. They aim to enable sales and minimize marketing spend but differ on the inputs. Segmentation looks at broad strokes to break audiences down into groups, while personalization focuses on those individual segments and market to each one. While seemingly impossible and perhaps undesirable years ago, today's consumers demand to receive only relevant content, and a supply of data makes the delivery of personalized content possible.
- Companies will continue to pair traditional marketing tools with analytical platforms to help fill the gaps.
- Analytical platforms -- such as Google Analytics -- will intake the information that matches it against the segments' performance and detail out future improvements and actions that companies can take.
- Companies will learn information about prospects across the customer journey touchpoints that the business can consolidate, log and update as needed in the CRM system. When integrated with the rest of the marketing system, the CRM system enables other tools to feed it information -- such as the analytics or data management platforms -- and generate personalized content, unified across channels and at all stages of the customer journey.
Personalization as a means to break through the clutter to engage customers will, in most cases, require a strong data set, as well as some form of AI for an excellent net outcome and understanding of the company's customers.