An increasingly important factor in your company’s ongoing success is being able to give your customers a personalized experience when they interact with your brand or business.
Personalization not only delights customers (a report by Epsilon indicates that 90% of consumers "find personalization appealing"), but it also leads to higher customer satisfaction and customer loyalty, thereby driving business growth. (Eighty-nine percent of marketers see a positive ROI when they use personalization in their campaigns.) With customers quickly moving from one business in a market to another, personalized communications create more opportunities to develop that critical loyal customers.
However, achieving personalization at scale has always been a challenging task for businesses to implement. This is where artificial intelligence (AI) comes in as a game-changer.
By leveraging machine learning algorithms and data analytics, AI can not only deliver personalized experiences but also improve operational efficiency and boost revenue.
Even as AI-driven personalization gains momentum though, industry thought leaders have raised concerns about privacy, ethics, and the trustworthiness of AI models. In this article, we'll explore how AI can be used for personalization, its potential benefits, and how businesses can address the challenges posed by AI-powered personalization.
Understanding personalization
Defining personalization
Personalization is how a company tailors a customer's experience to meet their unique preferences, behaviors, and needs. It is essential for businesses because it can improve customer satisfaction and loyalty, and ultimately increases revenue.
By creating personalized experiences, your business can build trust with customers and create long-lasting relationships that are mutually beneficial.
Benefits of personalization
Personalization can benefit your business in several ways. First, it can lead to increased customer engagement and loyalty because customers feel valued and understood. Epsilon's study says "80% of consumers are more likely to make a purchase when a business offers personalization."
Second, it may help your business increase revenue by encouraging customers to make additional purchases based on customized recommendations.
Third, it can improve customer retention rates by building trust with customers and reducing the likelihood that they will switch to a competitor.
Fourth, it can improve the overall customer experience by making it more convenient, efficient, and enjoyable.
Finally, and most importantly, AI-powered personalization can save your business time and money by automating the process of creating personalized experiences. This significantly reduces manual labor costs while ensuring that customer needs are met quickly and accurately.
Different types of personalization
There are several types of personalization your business can use to enhance the customer experience. These include:
- Content personalization is when customers see customized messaging and promotions for specific customer segments.
- Product recommendations are when a customer is shown specific products in which they may be interested, based on their past browsing and purchase history.
- Dynamic pricing occurs when prices are adjusted according to the customer's purchasing habits or the company's competitors’ prices.
- Behavioral personalization occurs when a customer's behaviors influence their interaction with the company.
- Product personalization allows customers to customize or configure a product to meet their unique needs.
How Artificial Intelligence Can Improve Personalization
How artificial intelligence works for personalization
AI can improve personalization primarily by quickly analyzing vast amounts of data about customers, their preferences, and their behavior. This data can be leveraged to make accurate and relevant predictions about what a particular customer is looking for.
AI can also identify patterns and trends that are not immediately visible to humans, making it easier to optimize content and product recommendations based on user history.
How artificial intelligence uses data
AI can be used for data collection by mining customer data from various sources such as social media, search queries, and email interactions.
Data analysis involves understanding the patterns and connections within customer data.
Predictive modeling involves analyzing historical data to generate future predictions for user behavior, content, or product recommendations.
How companies are using artificial intelligence for personalization
Many companies already use AI to enhance personalization including Netflix, Sephora, and Amazon. Netflix uses AI to improve content recommendations, Sephora uses AI to offer customized product recommendations based on skin tone and type, and Amazon uses AI to predict customer behavior based on prior shopping data and preferences.
Concerns regarding artificial intelligence and personalization
While AI has shown remarkable capabilities in terms of personalization, there are concerns about its impact on data privacy and security. Ethics is also a concern as AI can reinforce certain biases and perpetuate stereotypes.
Another issue that thought leaders have raised is accountability – as AI progresses, it may become increasingly challenging for businesses to maintain satisfactory levels of transparency with their customers.
These concerns will need to be addressed collectively to ensure that AI and its implications do not negatively impact consumers in the long run.
Best practices for implementing AI-driven personalization
A Twilio study demonstrates that 60% of consumers say they'll become repeat customers after they have a personalized shopping experience. Here are some best practices to help you implement AI-powered personalization.
Identify buyer personas and your target audience
Identifying the target audience and creating buyer personas is the first step in implementing personalization through AI. By segmenting customers based on age, gender, interests, location, and other factors, you can gain insights into specific demographics, curate content and products to their liking, and enhance their experience.
Collect and analyze data
Collecting and analyzing data about customers is critical to implementing personalization through AI effectively. By analyzing customers' data - such as browsing behavior, preferences, and search history - you can predict future behavior. This allows you to tailor product and content recommendations based on what "stories" are found in the data analysis.
In addition, you can use ChatGPT to give detailed information about your audience, even creating personas for use by your team. Detailed prompts are the secret to getting detailed, actionable information.
For instance, describe your company’s background and what you offer, especially the benefits it provides. Describe the problem you help solve. Explain the general type of person who would benefit from your offer(s) and ask for specific information, both demographic and psychographic. Ask especially for dreams, goals, defining events, fears, desires, self-labels, planted flags, etc. Be specific about asking what you're looking for. Then ask ChatGPT to provide a persona brief.
Create personalized content, recommendations, and offers
With that personalized data, now you can create personalized content in the form of emails, product recommendations, and ad delivery, all tailored to a customer's preferences and behavior. These types of personalization significantly increase customer engagement and loyalty.
Leverage AI-powered chatbots
One of the most promising aspects of personalization through AI is the rise of AI-powered chatbots. Artificial intelligence-powered chatbots, such as ChatGPT, can have personalized conversations with each customer, providing them with tailored content and product recommendations based on their preferences and behavior. AI-powered chatbots can increase customer satisfaction as they could be immediately supported when they have questions or concerns.
Connect with your network
Many businesses are now exploring - or already deeply implementing - AI-driven personalization. Make sure you continue to connect regularly with a network of business leader peers in order to stay up-to-date with the latest trends and concerns.
Challenges and Risks of AI
Consumers rightly are concerned about how data is being collected, analyzed, and used. Consider the following issues:
First, AI personalization works best when the data available is relevant and comprehensive. Poor data quality or biased data could compromise the AI's intent and cause negative customer experiences.
Second, businesses must ensure you are using the right AI model for your specific business needs, and not using AI just to use AI. Is there a real need? How can AI-driven personalization meet that need? It's important to consider how an AI model can impact your audience, as Newsweek Expert Forum member Erica McMillan shares.
Third, implementation can be complex with a large amount of data, complex algorithms, and high staffing requirements.
Address challenges; mitigate risks
Managing customer's expectations as well as privacy concerns is challenging. Although 36% (or more) of consumers want businesses to use personalization, 52% of shoppers worry that businesses know too much about them. (Study is here.) So here are some strategies to implement that can improve your ability to manage these risks.
- Focus on a human-centric approach that prioritizes transparency and accountability in the data collection processes so you can avoid the risk of bias.
- Work with data governance guidelines that promote accuracy, privacy, and ethical considerations.
- Regularly review machine learning models and the data sources they use. Ultimately, you also need to continue identifying and addressing potential issues after implementation.
Risk of bias and lack of transparency
Many business, community, and government leaders have concerns about the level of bias and lack of transparency with AI personalization.
The success of AI in personalization will depend on how responsibly businesses like yours use the data, as well as your ability to address ethical challenges. To ensure that AI-driven personalization is secure and effective, you should regularly review machine learning models and the data sources used for insights.
Additionally, companies need to have data governance guidelines that promote accuracy, privacy, and ethical considerations. Ultimately, you must prioritize transparency and accountability in your data collection processes. By doing so, you can build trust with customers and increase customer satisfaction and loyalty.
Takeaways
If your company vision includes anything about “providing an excellent customer experience” you must add AI-driven customer personalization to your toolbox of marketing strategies.
By leveraging AI-powered personalization technologies, your business is well-positioned to deliver uniquely tailored experiences to customers at scale. AI can help you uncover valuable customer data, generate predictions about user behavior and preferences, and optimize content and product recommendations. By doing so, you can ensure that AI-driven personalization is successful and meets your customer's expectations.
It is essential, however, to address the ethical, privacy, and trustworthiness issues posed by this technology. By focusing on human-centric approaches, data governance practices, unbiased data selection, and transparency, companies like yours can ensure you are using AI for personalization in a responsible and effective manner.
Ultimately, AI-powered personalization can provide a great competitive advantage to businesses willing to take the risk – and reap the rewards.
