Fetch Communications

How customer data and AI-driven consumer insights combine to turbocharge your marketing

Personalization has been used in marketing for decades as a strategy to strengthen connections with customers. Ever since the 1980s when businesses first learned to mail merge a database of contacts into a form letter, consumers have rapidly increased their demand for individualized interactions with brands. Now, with the continued rise of technology, e-commerce, and data analytics, the ways consumers interact with businesses have drastically changed.

In an era where service-oriented experience is the most important competitive differentiator, it should go without saying that brand loyalty is not reinforced when customers feel like nameless, faceless, nonentities on a balance sheet. Your customers want to be known, valued, and have the ability to interact with (and even influence) your brand offering. They want to matter to you. More so, they expect sophisticated personalization and choose brands that can meet their specific demands at the moment they need them.

Recent data analytics advancements have enabled marketers to extract tangible information about a buyer’s behavior and personality from various channels, including social media and e-commerce platforms. They use predictive analytics to create real-time individualized curated experiences at every stage of the sales process. As businesses recognize the benefits of offering personalized experiences to their clients and partners, they have now started investing in technologies and strategies that can address both the scale and intricacies of such experiences. This has come to be known as hyper-personalization. Source: datafloq.com

While marketing in the past involved splitting people into groups and providing different experiences for each, hyper-personalization involves using a person’s real-time data to provide an experience unique to them.

Hyper-personalization is the process of using Artificial Intelligence (AI), Machine Learning (ML) algorithms, and real-time data to display highly curated products and content to shoppers. It treats customers as individuals with distinct tastes and preferences, enabling brands and retailers to provide a unique customer experience that’s different for each shopper. Consider this Netflix example from kps.com:

Keeping people engaged is Netflix’s number one priority, so its ability to show users intriguing content they might otherwise miss is key to its ongoing success. To do this, the company’s personalized recommendations system draws from many sources. One is customer ratings, which feeds into an algorithm to determine what content is shown and to who. 

Netflix also incorporates what is internally called the ‘implicit signal’ into the algorithm: how the users interact with a show or movie: how long they watch it, whether they rewind, fast forward or stop watching and, if so, at what point. It also includes data on time, location and on which device users watch its content. This does not merely change what gets recommended: it informs the streaming service’s original programming, as was the case with House of Cards and The Crown.

How it works

Hyper-personalization in large organizations typically requires ample quality data, and the tools and expertise to analyze it effectively. For example, in e-commerce, analyzing a customer’s browsing and purchase history, demographics, location, and other data points helps to create a detailed profile of the customer’s persona.

Once a customer persona/profile is created, businesses can use this information to curate a hyper-personalized journey for the customer. Datafloq explains that customer profiles can be combined with AI and ML, allowing the model to be trained to predict customer’s requirements and cater to them accordingly. For example, Amazon’s recommendation system uses user activity data to suggest products, notably boosting sales.

Additionally, targeting specific customers can help companies increase their return on investment by focusing their marketing efforts on the most profitable buyers from their customer base. Businesses can increase customer retention with hyper-personalization by understanding their customers and optimizing their sales and marketing efforts and spend accordingly.

These practices take on amplified importance when working with small businesses in today’s overcrowded market where consumers want personalized experiences.

For small businesses

In order to implement a hyper-personalization strategy to foster tighter ties with your customers, you must understand that this approach calls for a keen balance, ensuring personalization without violating privacy.

While data procurement and management is a hurdle for SMEs, there are scalable ways you can apply hyper-personalization practices to magnify customer loyalty and increase sales.

According to buzzboard.ai, these practices take on amplified importance when working with small businesses in today’s overcrowded market where consumers want personalized experiences:

• Prioritize integration and streamlining data management systems to aid in overcoming data-related hurdles.
  
  
• Utilize customer relationship management (CRM) tools to gather and scrutinize customer data. CRM data helps you comprehend customer behavior and inclinations, which can effectively guide your targeted marketing maneuvers.
  
  
• Use data to provide highly relevant content, offers, and product suggestions to potential and existing customers.
  
  
• Capitalize on real-time engagement. Hyper-personalization flourishes on instantaneous interactions, so swift responses to customer inquiries or feedback can augment the user experience substantially.
  
  
• Create opportunities at every customer touchpoint to gather data about customer needs and purchasing decisions.
  
  
• Ensure a smooth customer journey across all channels. Simplify this process for your clients by guiding them in maintaining a consistent and personalized user experience across all touchpoints, be it a website, email, or mobile app.
  

5 examples of brands excelling at tailored customer experiences:

1. Starbucks

Starbucks excels at hyper-personalization. With the help of AI, the coffee brand uses real-time data to send users unique offers based on their preferences, activity and past purchases. With more than 400,000 variations of hyper-personalized messages to send, coffee lovers always feel as if their communication with the brand is tailor-made.

2. TastryAI

TastryAI partners with wineries to offer customers individualized wine recommendations. Consumers answer a simple 20-second quiz and the winery’s entire retail assortment is ranked and matched to the individual through complex AI systems. The customer then rates and reviews the wine, and TastryAI continues to fine-tune its recommendations. The founder of TastryAI, Katerina Axelsson, said:

“One question may be ‘How do you feel about the smell of fresh-cut grass?’ The AI already knows which compounds or groups of compounds are responsible for that sensation. When the answer to that question is known, the AI has learned about many compounds you may like or dislike.”

This hyper-personalized approach to wine keeps customers coming back for more. Indeed, those who use Tastry recommendations are 20% less likely to shop at a competitor.

3. L’Occitane 

L’Occitane’s e-commerce team noticed a segment of users in Brazil visiting the website between the hours of 10pm and 5am. ‍Based on the hypothesis that these people were potentially having trouble sleeping, an overlay appears during these hours showcasing the brand’s pillow mist spray. This product was designed to aid a restful night’s sleep.

4. PetPlate

DTC pet food brand PetPlate includes a colorful, personalized insert welcoming a new customer’s dog to “the PetPlate family.” This insert provides customized feeding instructions, customer service contact information and details on how to receive a discount when you refer a friend.

5. Prose

Personalization begins right at the beginning of the customer journey for DTC custom hair care brand Prose. When a user lands on the website, they’re prompted to fill out an online consultation. This consultation collects key data around their lifestyle, dietary habits, geographic location, stress levels, and more. From there, using a proprietary algorithm that was built in-house, Prose uses this information to create individualized products that address the shopper’s hair care needs and concerns. Each product comes in a bottle marked with the customer’s name. 

Potential Pitfalls

Everything we do as marketers has impact, so this overview wouldn’t be complete without looking at risk factors. emarketer.com reminds us that data collection comes with challenges around data security. 78% of consumers worldwide are increasingly protective of their private data, per a July 2023 Salesforce survey. Hyper-personalization can also be intrusive: Almost half (46%) of consumers worldwide think promotions based on their activity within 2 minutes of visiting a website or app is “creepy,” per the Marigold and Econsultancy survey.

AI also has drawbacks. Quality issues and plagiarism are potential weaknesses of AI, according to 65% of US and UK content and creative professionals in an October 2023 survey by Ascend2 and Canto.

Retailers must balance hyper-personalization with privacy by implementing robust data privacy policies to keep customer data safe and comply with privacy laws and regulations. Data clean rooms can be used to share data securely with third parties without revealing any personally identifiable information.

emarketer.com also suggests giving customers a voice and establish preference centers so customers can manage their communication preferences and feel in control of the data they’re sharing. Retailers should also track and measure consumer sentiment to make sure hyper-personalization is improving—not undermining—customer satisfaction and trust.

In summary, here are some hyper-personalization best practices for small businesses:

• Understand your customer. Immerse yourself in customer data, leveraging AI whenever possible.
  
• Implement robust data privacy practices.
  
• Communicate tactfully, not excessively. Aim for relevant and occasional engagement, such as promotions or limited-time offers.
  
• Remember that personalization revolves around the customer. Rather than focusing on your own business objectives, keep the emphasis on fulfilling the customer’s needs and desires.
  

Anything to add? Feel free to comment below, we’d love to hear your thoughts!