Build Brand Property with Customer Touch Points

Leveraging First Party Data for Personalised Journeys and Increased ROI: Single Source of Truth

Customer loyalties are changing.?72% of consumers?admit they’ve changed their shopping behaviours or brand preferences since the pandemic hit, while?86%?say they’re now willing to pay more for a better customer experience. This means that there’s a growing opportunity for brands that are ready to go the extra mile to keep consumers happy to capitalise and grab market share.

This indicates that every interaction between a brand and its audience holds immense value. These interactions, known as customer touchpoints, are the cornerstones of building lasting relationships and driving business growth. By strategically leveraging the data gleaned from these touchpoints, businesses can personalise the customer journey, forge brand loyalty, and ultimately boost their return on investment (ROI).

Google’s announcement that it would be?phasing out third-party cookies?by 2023 was—and still is—seismic. With retailers less able to track consumer habits across the internet, they’ll likely turn increasingly to first-party consumer data to fill this void, with a greater focus on leveraging owned channels rather than walled gardens.

Demystifying Customer Touchpoints and Their Landscape

Customer touchpoints encompass every single interaction a customer has with your brand, from awareness to post-purchase engagement. These interactions can be broadly classified into three stages:

• Pre-purchase:?This stage includes touchpoints that introduce potential customers to your brand. Examples include online advertisements, social media interactions, website visits, content marketing materials, and influencer endorsements.
• Purchase:?This stage encompasses touchpoints that facilitate the buying process itself. Examples include product pages, shopping carts, checkout experiences, in-store purchases, customer support interactions during purchase, and loyalty programmes.
• Post-purchase:?This stage encompasses touchpoints that occur after a customer has made a purchase. Examples include product reviews, customer service interactions, warranty registrations, loyalty programme rewards, email marketing campaigns, and subscription renewals.

By mapping these touchpoints, businesses can create a comprehensive customer journey map, visualising the entire customer experience. This map serves as a roadmap for optimising interactions and strategically collecting valuable customer data.

The Power of Data: Transforming Customer Interactions into Insights

Every customer touchpoint generates valuable data. This data can include demographics, purchase history, browsing behaviour, website interactions, search queries, email engagement, app usage, and social media activity.

A composable CDP can be a powerful tool to unlock the value hidden within all that customer data mentioned. Here's how:

• Unified Customer View: Traditionally, customer data is scattered across various systems (CRM, marketing automation, website analytics, etc.). A composable CDP acts as a central hub, ingesting data from all these sources and stitching them together to create a single, unified profile for each customer. This 360-degree view gives you a complete understanding of their preferences, behaviour, and journey with your brand.
• Segmentation and Targeting: With a unified view, you can leverage the CDP to segment your customers into highly specific groups based on demographics, purchase history, interests, and more. This allows for much more targeted marketing campaigns. Imagine sending personalised email recommendations based on a customer's recent browsing behaviour or tailoring social media ads to their specific needs.
• Personalisation Across Channels: A composable CDP can integrate with various marketing channels like email, SMS, social media, and your website. This enables you to deliver personalised experiences throughout the customer journey. For example, a customer who abandons their cart might receive a follow-up email with a special discount, while a loyal customer might be offered exclusive early access to a new product launch.
• Customer Lifetime Value (CLTV) Prediction: By analysing purchase history and engagement data, the CDP can help you predict a customer's future value. This allows you to prioritise high-value customers and tailor your marketing efforts accordingly. You can invest more resources in nurturing relationships with customers predicted to have a higher CLTV.
• Improved Customer Journey: With a deeper understanding of your customers, you can use the CDP to identify pain points and areas for improvement throughout their journey. This can lead to a more seamless and enjoyable experience, ultimately boosting customer satisfaction and loyalty.

Composability Advantage:

• A composable CDP offers a modular design, allowing you to integrate different best-of-breed solutions for specific needs. This flexibility ensures you can leverage the strengths of various tools while maintaining a unified customer data platform.

By implementing a composable CDP and effectively leveraging customer data, you can gain a significant competitive advantage. You'll be able to deliver a more personalised and relevant customer experience, leading to increased customer satisfaction, loyalty, and ultimately, business growth.

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Data-Driven Cohorts and Personalised Marketing Strategies

One of the most powerful applications of customer data is the creation of customer cohorts. By segmenting customers based on shared characteristics and behaviours identified through touchpoint data, businesses can create targeted marketing campaigns. These cohorts can be based on demographics, purchase history, interests, engagement levels, or any other relevant data point.

For example, a clothing retailer might create a cohort of customers who have purchased activewear in the past month. This cohort can then be targeted with email campaigns promoting a new line of athletic apparel, personalised recommendations based on their purchase history, or exclusive discounts.

Commerce Data: The Personalisation Engine

Commerce data, specifically information gathered during the purchase stage, offers a goldmine of insights for personalising the customer journey. Browsing behaviour, abandoned carts, product reviews, and purchase history all paint a vivid picture of customer intent and preferences. This data can be used to personalise product recommendations, showcase relevant upsell and cross-sell opportunities, and tailor messaging based on individual customer needs.

Imagine a customer browsing a travel website who has repeatedly viewed packages to Europe. By leveraging this data, the website can personalise the user experience by featuring prominent European vacation deals, highlighting relevant blog posts about European travel destinations, or even offering a discount on European travel insurance.

The ROI of Personalisation: Statistics Speak Volumes

The benefits of personalisation are undeniable. According to McKinsey & Company: [invalid URL removed], personalisation can generate up to a 15% increase in conversion rates and a 10% lift in sales. Additionally, a Salesforce: https://www.salesforce.com/ study (https://www.salesforce.com/) found that 73% of customers expect companies to use their personal information to provide them with targeted experiences. This data underscores the crucial role personalisation plays in customer satisfaction, loyalty, and ultimately, ROI.

Case Study: Building Brand Loyalty with First-Party Data

First-party data can be incredibly powerful for marketers, but it’s something that’s probably been a touch overlooked during the cookie era. But, with third-party cookies becoming less attractive and consumers now simultaneously more wary of privacy concerns and more keen to receive personalised content, first-party data is proving its worth.

Brands have realised they’ll need to reassess and revamp their approach to marketing, and sportswear giant Nike is, unsurprisingly, ahead of the curve. Wasting no time in seizing the first-party initiative, Nike is trialling a new algorithm—dubbed a?‘dedication core'—that re rewards its loyal customers.

The tool uses first-party data collected from customers to understand what they like and what’s going to keep them happy. Nike can then use this learning to provide offers, deals and content they?know?will be well received and more likely to drive conversions.

The algorithm measures product affinity and has been used in tandem with the brand’s SNKRS app to offer exclusive access to limited-release products. The tool recognises user engagement across various channels, including live streams and social post interactions, and ultimately creates a loyalty score. Customers then receive exclusive rewards and offers relative to their score.

This initiative is a great example of a brand listening to calls for greater levels of personalisation from customers and actively seeking ways to utilise data to improve the overall brand experience and strengthen customer relationships.

Nike is far from alone in using first-party data to give back to customers. Take North Face’s XPLR Pass, for example, which provides members with exclusive discounts and access to unique events. Or beauty colossus Sephora, which uses its ‘Beauty Insider’ loyalty programme to let consumers redeem points for real-world charity donations. The key for brands is understanding what will delight customers and using the right touch points and channels to communicate.

Building First-Party Data: The Key to Sustainable Growth

With privacy regulations and third-party cookie deprecation, building a robust first-party data strategy is crucial. This involves collecting and utilising data directly from your customers through touchpoints you control, such as your website, app, and email marketing campaigns.

As long as you’re speaking on a one-to-one basis to your customers and sending genuinely valuable content, you’ll see results. Create an emotional connection with your consumers, treat them as individuals, and go above and beyond to deliver on promises.

Nike’s approach to using first-party data is impressive and worth noting as a benchmark. Regardless of their scale, all brands have the ability to capture consumer data and use it effectively, and as we move away from cookies, more and more retailers undoubtedly will.

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