How to Create Personalized Customer Experiences: Best Practices and Real-World Results

Finding new ways to build and sustain customer relationships is crucial for every brand. Smart marketing leaders use personalization to pivot in real-time, keep costs down and remain sensitive to customers’ needs. This kind of precise targeting with relevant personalization is only possible when you’re able to gather and use customer data at the most granular level. But with the right technology, strategy and access to data it’s possible to create 360-degree customer views, deliver personalized recommendations and automate marketing campaigns to drive better outcomes for your business and your customers.

It all begins with data analytics, AI and automation tools.

Using AI, Data Analytics and Automation to Create Context

Effective use of analytics, AI and automation allows you to capitalize on data, build insights and drive results. It makes your business more customer-centric and data-driven, paving the way for better experiences and more relevant offerings.

Personalization with AI and ML

Artificial intelligence (AI) and machine learning (ML) allow retailers, mass media and entertainment companies to personalize the content they recommend to customers. For example, the popular streaming service Discovery+ uses Amazon Personalize to deliver personalized content experiences to individual viewers in real time. Technologies like machine learning and natural language processing (NLP) empower AI-enabled chatbots to understand and respond to customer queries based on context. Companies without the resources to hire a significant number of customer representatives can use these chatbots to provide prompt responses to service questions.

The impact of data analytics

Data helps you understand who your customers are, how they shop, what they buy and how they like to engage, making it easier to serve and retain them. When Starbucks had to rely on its mobile app and drive-through windows to serve customers during the lockdown, they used predictive analytics to process customer data. The data included the location, time and details of purchases. This helped Starbucks personally connect with customers and serve them better. Aberdeen’s research confirms that employing predictive analytics to foresee customer needs can increase organic revenue by 21% year-on-year, compared to the industry average of 12% in the absence of predictive analytics.

Customizing experiences with automation

Big Data and machine learning algorithms help you create detailed profiles of users. They can also help automate the customization of offerings to those individuals. For example, you can automatically push personalized content and offers to your customers via their mobile devices based on their location. You can also tailor content on your website to match the user’s language, local time zone and currency. Automated customer support systems such as self-service portals, ticketing systems and AI-enabled chatbots can take on a lot of the heavy lifting as you provide instant, personalized responses to your customers.

How to Create and Deliver Personalized Solutions

As you build out your personalization strategy and technology suite, there are six areas of focus you should incorporate. These are customer segmentation, personalized recommendations, 360-degree customer views, CRM integration, campaign automation and hyper-personalization.

Customer segmentation

Segmentation refers to identifying similar groups of potential customers based on information gathered from sources like websites, mobile apps, virtual events, ads, contact forms, email and web chats. According to Salesforce, marketing campaigns that are personalized to segmented audiences can generate an increase in revenue of around 760%.

Here are some examples of typical customer segments and some of the traits they share

How segmentation helps your business

Segmentation allows you to organize and manage customer relationships by making it easier to personalize your marketing, services and sales efforts according to the needs of specific groups. It increases conversions and boosts your customer loyalty.

Customer segmentation also enables you to do the following:

• Create targeted campaigns that resonate with specific segments

• Understand and address the challenges experienced by your segments

• Identify who your most valuable customers are and why

• Reach out to customers through their preferred channels

• Discover new opportunities for product, service and support

• Improve your customer service and support efforts

Personalized recommendations

92% of customers are influenced by personalized product recommendations in their shopping carts. If you offer suggestions based on preferences and online behavioral data, customers are more likely to buy from you. By displaying products they’ve previously viewed or bought, you’ll increase your conversion rate and average order value, reduce cart abandonment and improve user experiences. For example, a customer who purchased an item of clothing in three different colors is more likely to buy the same item in a new color.

How recommendation engines help your business

Recommendation engines are machine learning programs that analyze user and product data to derive actionable insights and personalize offers to customers. They use a vast array of data, including customers’ search queries, purchase histories, items in their shopping cart, social media behavior, demographic details and location to provide specific suggestions. Personalized product recommendations help you do the following:

• Enable your customers identify what they need to buy

• Tailor recommendations and highlight relevant products

• Encourage shoppers to make repeat purchases in the future

• Cross-sell and up-sell based on user preferences

Customer 360

A 360-degree customer view, sometimes called a Customer 360, gives you a single unified understanding of your customers by aggregating relevant data from multiple sources into a centralized location. Data points gathered include website visits, purchases, data from forms, contextual information from social channels, customer support tickets, helpdesk interactions, emails and more.

How 360 customer views help your business

360-degree views of your customers provide actionable insights that help you deliver hyper-personalized experiences with relevant content. Some of the benefits of a 360-degree view include the following:

• Refined customer segments – Build more specifics into your customer segments by including factors like customer satisfaction or purchase frequency.

• Streamlined communication – A single, shared view of each customer helps you break down silos to enable seamless communication between your different teams.

• Operational efficiency – Your sales and support teams can quickly respond to inquiries and resolve issues in real time without asking customers to repeat the information they’ve already provided in other channels. This improves omnichannel efficiency, increasing customer satisfaction and reducing churn.

• Predictive analysis – A 360-degree customer view improves your ability to anticipate customers’ needs through predictive analysis. You’ll know how to make the right offer or deliver the right content at just the right time.

CRM integration

Integrate your CRM suite with your sales and marketing automation solutions, e-commerce applications, ERP software, customer communication management systems and other crucial business software.

CRM integration examples and benefits

Integrating other systems – like your solutions related to social media, payments, scheduling, etc. – with your CRM offers many benefits.

• Syncing the data you receive through custom forms and surveys (using tools such as Survey Monkey or Typeform) with the lead data in your CRM will help your sales team easily refer to and analyze data when they prepare for sales meetings.

• Integrating meeting software, like Zoom or Teams, with your CRM and calendar app can facilitate one-click meetings from any preferred channel – like your email, calendar, CRM or chat application.

CRM integration increases productivity and improves turnaround time. It provides enhanced visibility into customer interactions across multiple channels and helps you adopt a more holistic approach to business management.

Campaign automation

The automation of email campaigns, including customer profiling, targeting and personalization using dynamic content, is used widely today. Emails that are personalized and automatically triggered generate 75% of email revenue.

How campaign automation boosts personalization

Here’s how automating your campaigns can help you personalize experiences at scale:

• Your team can create more personalized content by using segmentation capabilities and reporting.

• Automation lets you target your persona on multiple channels, such as search ads, email campaigns or social media.

• It simplifies the process of getting the right content to the right buyer at the right time.

• Automation personalizes your lead nurturing process, helps with lead scoring and grading and tracks your entire engagement with the customer.

• It analyzes visitor data to trigger the automatic assignment of qualified leads to the right sales representatives and further personalize the customer journey.

Hyper-personalization

Hyper-personalization has changed the formerly product-centric field of marketing. It allows you to evolve from user-based to usage-based segmentation by leveraging Big Data. Hyper-personalization takes personalized marketing and service to a much higher level by customizing offerings, content and experiences at the individual level.

Common examples of hyper-personalization include purchase recommendations based on the customer’s preferences and purchase history and the retargeting mechanism used to display ads on the user’s screen in real-time.

Boost your customer engagement with hyper-personalization

Adapt your service, relationships and overall customer experience to specific customers’ context through hyper-contextualization. With Big Data, algorithms and predictive models, you can improve direct targeting at an individual level. This will enable you to create positive and impactful experiences and boost customer engagement and trust.

Hyper-personalized marketing also maximizes your revenue through dynamic pricing; it reduces customer acquisition and retention costs and helps make the most of in-the-moment customer journeys.

According to Deloitte, well-executed hyper-personalization can deliver 8X the ROI on your marketing spend and lift your sales by more than 10%. Hyper-personalization pushes data collection and customer interaction beyond the point of sale (PoS) by combining data and technology.

Real-World Examples of Personalized Customer Experiences

FinTech

FinTech companies are personalizing services through Banking-as-a-Service (BaaS) platforms, digital-only banks (or neo-banks) such as Chime, Varo, Starling Bank and Atom Bank – as well as AI-powered cybercrime and fraud prevention solutions. The Credit Union of Texas saw a 300% rise in home equity and mortgage applications after displaying personalized CTAs to their website visitors. American Express improved conversation rates by 3X and lowered customer acquisition costs by 6X by sending out personalized videos (informative, self-help hacks, etc.) to their customers along with their monthly credit card statements.

Retail

Retailers can deliver hyper-personalized shopping experiences through virtual try-ons, 3-D product configurators, interactive product visualizations, improved in-store experiences, VR simulations and contactless payments. Virtual try-ons are a highly immersive experience for customers and offer personalized product recommendations based on a consumer’s attributes. With a virtual try-on solution for in-store and online users, we’ve seen consumer wellness brands boost their conversion rates by 9%.

Healthcare

In healthcare, personalization efforts are built on data consolidation from multiple healthcare devices, tools, wearables, paper forms and systems. Use cases include personalized diet and nutrition recommendations and suggesting personalized treatments. Data allows caregivers to prescribe medication and care plans based on a patient’s individual data and medical history.

The University of Colorado used AI and ML technologies to help personalize tumor treatment. They searched massive public DNA databases to gather common cell mutations that are treatable, which enabled researchers to narrow their focus on rarer mutations. This in-depth classification allowed clinicians to prescribe personalized drugs to patients based on their specific mutations. Advancements like this are expected to create significant breakthroughs on a person-to-person level in healthcare.

Personalize with Material

Personalization is a dynamic differentiator that can help you align your business goals with customer expectations. But meeting consumer needs in a personal, meaningful and timely way is only possible through the strategic use of data and technology. This takes expertise and experience – both of which Material has. If you’re interested in taking your personalization efforts to the next level, we can help you build multi-layered personalization based on your unique needs.

Contact us for a personalized consultation.