Creating Value From First-Party Data

Deep understanding of customer is key to providing exceptional customer experience. Historically most of the brands have been heavily dependent on purchased third-party data but the new paradigm of marketing has shifted focus on customer data ownership.

This article focuses on factors that have led to increased focus on first-party data, strategies to collect first-party data, and creating value from first-party data.

Types of data at play

While first-party data is useful for targeting existing customers/prospects, second-party data helps to expand the targeting reach to a new audience of potential customers.

Why first party data is the new focus area

Marketers have long relied 3rd party cookies build audiences and expand outreach but with growing public privacy concerns and new data protection laws, the days of traditional 3rd party cookies are numbered.

Every other country is coming up with laws for processing personal data with emphasis on user consent.

Business areas most likely to be impacted in absence of third-party cookies :

• Ad personalization for acquisition campaigns due to limited browsing & behavioral data
• Ad frequency management due to loss of cross-platform frequency capping which could lead to overserving ads to customers
• Website personalization based on DMP-based 3rd party cookies
• Marketing KPIs might need some rethinking in absence of most display/programmatic view through conversion data

?It’s certainly a big disruption for digital advertising to absorb. The new paradigm of digital advertising will require brands to take full ownership of their data, right from acquisition to activation.

Emerging solutions for cookieless world:

• Universal IDs (common identifiers used by different platform on top of other ID)
• User Identity Graphs (combines both PII and Non-PII identifiers)
• Data Clean Rooms (multiple parties can combine data without revealing user-level info)
• Contextual Targeting (focuses on search terms & site content to place ads)

?First-party data is key for all emerging ID-based solutions.

Moreover, the impending ban on third-party cookies by Google (who controls more than 50% of the global web traffic) has also shifted focus of marketers towards first-party data.

First party data strategy

Sitting on customer data with no potential for activation doesn't serve any purpose to brands instead it increases cost. Hence, it is important to build and nurture sources of robust sources of first-party data.

1. Defining right value exchange for customers to share their personal data. Examples of approaches or incentives used by brands to gather first-party data include personalized rewards & recommendations, free access to a service, expedited checkout options etc.
2. Updating technology set-up e.g.- Tag management platforms to measure conversions using first-party cookies and identifiers and AI/ML solutions to model non-consenting user conversions.
3. Data partnerships to leverage second-party data to augment first-party data to build comprehensive portraits of customers. Insights on audience media consumptions helps brands identify right partners to get complementary data.

Touchpoints to collect first party data:

• Website or Mobile App
• CRM
• Transactions (attached to customer ID or Promotional codes)
• Marketing campaigns
• Customer Surveys
• Customer Feedbacks
• Online Chats
• Customer Services
• Social Media Accounts

Creating value from first-party data

Customers today interact with brands through multiple channels, and if those interactions are not tracked and associated with single unified profile of each consumer then it results in multiple identities of same consumer, and losing track of consumer before finalization a sale. On the flip side, unified ID (accomplished through Identity Resolution solutions) for every customer empowers brands to better segment and target customers by understanding consumer’s buying journey and their propensity to buy.

ID resolution solution uses Deterministic matching as well as Probabilistic matching to create unified ID.

360 Customer view is method of combining all disparate first-party data as well as other company-wide to make to much richer.

Map of customer journey helps effectively analyze attribution techniques and ultimately optimize ROI for different marketing techniques.

Multi-channel measurement of customer behavior helps brands deliver consistent brand experience across channels that encourage conversion.

To create value from the collected first party data, businesses need to invest in tech-stack that could –

360 degree customer data along with right tech-stack equips brands with predictive capabilities to create value for their customer.

Examples of Customer Analytics use-cases include -

• Customer segmentation
• Churn Analysis
• Improving Customer Lifetime Value (CLV)
• Propensity to buy
• Next-best action recommendations
• Identifying upsell/cross-sell opportunities
• Demand Forecasting
• Price Optimization