How are leading marketers using first-party data to drive business results?
Inspired by a recent paper by Meta and Deloitte, this article discusses the importance of first-party data in a privacy-first world and how marketers are using it to improve ad targeting, personalisation, and measurement. It also provides recommendations on how to enable these use cases and a case study of a fashion brand that successfully used first-party data with the help of analytic partner.
As third-party cookie depreciation looms, businesses are turning to first-party data to understand and engage with their customers in a privacy-first way. A recent Gartner survey of marketing leaders found that 82% of marketing leaders are prioritising first-party data to create immediate value for customers, such as strengthening signal resilience and future proofing their data sources (1). But first-party data is more than just a defensive strategy. Businesses are also using it to drive better business results through a variety of use cases such as improved ad targeting, personalisation, and measurement and optimisation (2, 3). Those that learn to harness first-party data will have a significant advantage, because understanding and increasing customer value leads to increased profitability.
What does a strong first-party data strategy look like?
Better Ad Targeting
Identifying the most profitable customers early on and understanding what makes a customer loyal allows businesses to maximise profits and minimise losses by avoiding customers who are unlikely to be profitable in the long run. This can be done by using first-party data to 'bolster connections with existing customers and identify new audiences to reach' e.g. Audience Exclusions, Deterministic Customer Segmentation, Model-Based Targeting.
With that in mind, think about about the following questions:
How do you currently use customer insights to acquire the best possible new customers? e.g. do they share common characteristics and behaviours that you can optimise for on ad platforms?
How do you maximise the long term value of your existing customers? e.g delivering timely and optimal messages to low and high churners or to free trial users encouraging them to become paying customers.
Better Personalisation
According to Deloitte, customers are '69% more likely to purchase form a brand that provides personalised, frictionless experience throughout their purchase journey' (3). Businesses can use past behaviour from first-party data to build tailored omni-channel experience across digital and offline touch points via Dynamic Creative Optimisation, Omni-channel Personalisation, Custom Product Recommendations.
Better Measurement & Optimisation
Marketers face the constant challenge of proving how their marketing activities drive incremental business outcomes. They can incorporate first-party data into their measurement strategies to provide accurate visibility into the performance of their marketing efforts. e.g. Server-to-Server Connections, Granular Marketing Mix Modelling, Cloud Environment for Data Collaboration. Deloitte found the measurement front-runners to be 44% more likely to beat their revenue goals.
How do you get started?
Here are the paper's recommended actions:
Ad targeting
Ensure you have proper permissions to collect, share, and use customer data for marketing initiatives
Centralise your customer data via a customer data platform to enable seamless activation and optimisation across channels
Leverage machine-learning to build robust audience models to identify high- value prospects at scale
Personalisation
Take advantage of ad-serving tools in marketing platforms like dynamic creative optimisation to serve tailored messaging to customers
Ensure you have a holistic view of the customer across Ad/Martech platforms
Partner with store merchandising teams to inform product assortment for personalised digital content
Measurement & Optimisation
Establish server-to-server connections to ensure high-quality data gets shared with marketing partners
Leverage a model-based measurement approach such as granular marketing mix modelling to understand omni-channel impact
Pilot data cloud environment solutions to analyse first-party data and enrich your customer insights and better understand marketing performance.
Marketers who are new to first-party data may find the initial steps to be daunting. While using first-party data can provide significant benefits, it requires a number of enablers to be in place, such as a customer-centric philosophy, data unification, technology infrastructure, and sophisticated analytic resources. These enablers can be costly, but they are essential for reaping the full benefits of first-party data (3, 5).
Business will find themselves better equipped with some enablers than others. Some lack the infrastructure (unique customer identifiers, Customer Data Platforms etc.) and others might lack the technical and analytics skills to activate a use case like modelling user data (statisticians, data scientists, data engineers). Should you want to evaluate the incremental value of your new high-value based audiences, then you’ll also need to integrate with, and experiment on, advertising platforms - which in our opinion is often the hardest part of the process.
A case study on how partners can help
Starting out with first-party data can be challenging, but there is a growing ecosystem of partners who can help you bring your first-party data use cases to life. A good partner will have the experience and expertise to help you avoid common pitfalls and achieve your goals.
To give one example from the paper, we see a fashion brand with a ‘niche target audience who wants to expand to new customers and drive them to their online and brick-and-mortar stores’ (3). The in-house data science team worked alongside an analytic partner to:
Evaluate their customer profiles and assigning scores based on life stage, shopping behaviour, and purchase history
Upload first-party data into a cloud environment for secure data collaboration with an ad platform provider to glean additional insights
Activate audience segments based on purchase category and high-propensity lifetime value across several media channels, including paid social and programmatic
Use dynamic creative optimisation tools to personalise messaging and products by segment
Test new audience targets against standard audiences to identify incremental lift.
As a result, the experiment demonstrated how the ‘new first-party audiences drove higher engagement and return visits compared to standard audiences, paving the path forward for the brand to build relationships with new customers’. If this kind of lifetime value use case excites then check out a similar paper: ‘Predicting lifetime value: How adopting customer lifetime value strategies leads to profitable growth’.
Collecting, managing, and using first-party data in a privacy-centric way can lead to better business outcomes. It can be used for a variety of purposes, such as improving ad targeting and personalisation, and better measurement and optimisation. However, activating these use cases may require technical capabilities that your organisation does not currently have. In these cases, it is worth reaching out to a partner for support.
No matter where you are in your journey, there are actions you can take to improve. Read the paper to learn more about what those are.
References:
Want to pull ahead of the pack? Ramp up data-driven capabilities. by Deloitte Digital
5 Steps to Redefine Performance in a Privacy-First World by Meta
Marketing measurement in a world of change by Deloitte Digital