Excelling in Individualised Consumer Journeys: Four Case Studies of Companies Setting the Standard

What can we learn from the leaders in personalisation?

Consumers are getting less loyal: they are always looking for a better offer or a service that fits their needs better. Whatever your business does well, it must also master the art of engaging customers. The route to achieving this is through individualised consumer journeys. In this article, we’ll take a close look at four companies that have excelled in leveraging behavioural data and digital touchpoints to create personalised experiences for their customers. In each example, we will explore how these companies set themselves apart by understanding and meeting customer needs at every interaction.

Case Study 1: Target's Circle Rewards Program - Personalization Powerhouse

Challenge: To stand out and build customer loyalty, Target has relied on competitive prices and a vast product selection. They have also sought to understand and meet individual customer needs.

Solution: Target Circle, a loyalty program launched in 2018, leverages customer data to deliver a personalised experience across all touchpoints - in-store, online, and mobile app.

Personalisation in Action:

• Targeted Promotions: Circle analyses past purchases and browsing behaviour to send customers personalised coupons and discounts. For example, a customer who frequently buys baby food would receive targeted discounts on diapers or wipes, increasing customer satisfaction and driving sales of relevant products.

• Recommendations: Target's recommends products based on past purchases and browsing behaviour. For example, a customer who buys running shoes might see recommendations for athletic gear, or workout playlists curated by Spotify (a Target partner).

• Surprise Offers: Circle occasionally offers members surprise deals based on their preferences. This strengthens the customer-brand relationship and keeps customers engaged.

• Personalised Shopping Experiences: In-store, Circle members can scan product barcodes to access product information, reviews and recommendations for complementary items.

Results:

Increased Sales: Target has reported a significant increase in sales directly attributable to personalised offers and recommendations within the Circle program.

Customer Loyalty: Circle members spend significantly more than non-members, showcasing the program's effectiveness in building loyalty.

Deeper Customer Insights: By analysing customer behaviour within the Circle program, Target gains valuable insights into customer preferences, allowing them to tailor offers and marketing more effectively.

Case Study 2: Booking.com - Tailoring Travel Dreams

Challenge: Travel booking platforms are flooded with options, making it overwhelming for customers to find the perfect trip. Standing out requires going beyond basic search functionalities.

Solution: Booking.com, a leading online travel agency, utilises user data and machine learning to curate personalised travel experiences across its platform.

Personalisation in Action:

• Smart Search: Booking.com's search algorithms consider past booking history, browsing behaviour, and even social media logins (if allowed) to personalise search results. Imagine a user who frequently travels for work being presented with hotels offering business amenities like airport shuttles or co-working spaces first.

• Dynamic Recommendations: Beyond search results, Booking.com recommends flights, destinations, and activities aligned with a user's travel preferences. A user who loves exploring historical sites might see recommendations for walking tours or museums in their chosen destination city.

• Price Tracking and Alerts: Booking.com allows users to set price alerts for specific destinations or hotels. This empowers budget-conscious travellers and ensures they get the best deals on their desired trips.

• "Genius" Program: Booking.com offers a loyalty program called "Genius" that provides exclusive benefits like free breakfast or airport transfers at select hotels. These benefits are chosen based on a user's past booking behaviour, further enhancing the travel experience.

• Personalized Inspiration: Booking.com utilises travel blogs, articles, and user reviews to inspire users and curate personalised "Travel Lists" with destinations and activities that might interest them.
  

Results:

Increased Conversions: Personalised recommendations lead to users finding trips that better suit their needs, resulting in higher booking conversion rates.

Improved User Satisfaction: A tailored travel experience reduces decision fatigue and fosters customer satisfaction.

Valuable Customer Data: By analysing user behaviour, Booking.com gains insights into travel trends and preferences, allowing them to improve platform features and forge strategic partnerships with travel providers.

Case Study 3: Mint.com's Adaptive Financial Coaching - Tailored Steps to Financial Fitness

Challenge: Unless you are a finance expert, personal finance can be complex with traditional budgeting apps only offering advice that doesn't account for individual circumstances. The holy grail is actionable, personalised guidance that adapts to a user's financial situation over time.

Solution: Mint.com, a personal finance app, leverages data analysis and machine learning to go beyond basic budgeting tools and offer a personalised financial roadmap for each user.

Personalisation in Action:

• Goal Setting and Tracking: Mint helps users define financial goals and analyses spending habits to suggest realistic budgeting strategies.

• Automated Insights and Alerts: Mint analyses income and expenses to automatically categorise transactions, identify areas for improvement, and send personalised alerts. For example, a user who overspends on dining out relative to their income might be recommended to set a budget for eating out.

• Adaptive Budgeting: As users track their spending and income, the app automatically adjusts category allocations to reflect real-time financial situations. If a user receives a pay rise, Mint might automatically increase their savings goals and adjust spending allocations accordingly.

• Personalised Tips and Resources: Based on user data and goals, Mint offers targeted tips and educational resources. For example, a user with credit card debt might receive recommendations for balance transfer offers.

• Goal-Based Progress Tracking: Mint keeps users motivated by visually tracking progress towards financial goals.

Results:

Improved Financial Behaviour: Mint users credit personalization with helping them to make better financial decisions and achieve their financial goals faster.

Increased User Engagement: Adaptive advice engages users at times of change.

Valuable Financial Data: By analysing user spending habits gives insights into broader financial trends, allowing Mint to update their platform and consider new financial products.

Case Study 4: Netflix's Algorithmic Playground - Curating the Perfect Watchlist

Challenge: With an expanding library, streaming services face the challenge of helping users discover content they'll truly enjoy. Getting this wrong risks decision fatigue and user churn.

Solution: Netflix leverages sophisticated algorithms and user data to curate personalised content experiences for each subscriber.

Personalisation in Action:

• Recommendation Engine: Netflix analyses a user's watch history, ratings, and browsing behaviour to recommend content that aligns with their preferences. Users who enjoy historical dramas might see recommendations for documentaries about similar eras.

• Personalised Rows: The Netflix home screen displays curated rows of shows and movies specifically tailored to each user. Categories include "Because you watched [show title]," "Trending on Netflix for you," and "New releases we think you'll love." These rows reduce the friction of searching for something to watch.

• Hidden Gems and Genre Explorations: The algorithms explore user preferences and recommend hidden gems or shows from different genres that might pique their interest. This helps users discover new favorites and broaden their viewing horizons.

• "Continue Watching" and "Play Something" Features: These features leverage a user's current progress and viewing habits to suggest content that they're likely to continue watching or enjoy based on their recent choices.

• A/B Testing and User Feedback: Netflix continuously tests different curation methods and refines their algorithms based on user feedback and engagement metrics.

Results:

Increased Watch Time: Personalised recommendations result in higher overall watch time. Reduced Churn: Matching users to content they love reduces churn and keeps subscribers engaged.

Data-Driven Content Acquisition: Analysing user viewing habits means that Netflix can prioritise acquiring content that aligns with subscriber preferences.

What do these examples have in common?

These four very different businesses have a number of things in common:

• Advanced Data Analytics: Each company invests in advanced analytics and AI capabilities to derive meaningful insights from complex datasets.

• Real-Time Personalisation: By leveraging real-time data, they deliver timely and relevant interactions that resonate with customers.

• Enhanced Customer Experience: Personalised experiences enhance satisfaction, loyalty, and advocacy among customers.

• Compliance and Trust: Upholding data privacy regulations and transparent data practices build trust and credibility with customers.

These case studies illustrate how companies are innovatively using data to create individualised consumer journeys. By prioritising customer preferences and behaviours, these businesses not only enhance engagement and satisfaction but also drive growth and competitive advantage in their respective markets.

Want to learn more about using data to create individualised consumer journeys? Join us at the Personalisation Summit - where consumer brand leaders explore best practices and innovations in leveraging customer data for personalised consumer journeys that build loyalty and drive business growth. Sound of interest? Download the event agenda here

Return to Home