August 24, 2023
Part two of a three-part series on customer acquisition. Here we explore new data-driven approaches. Parts one and three clarify common misunderstandings associated with online cookies and look at the future of marketing campaigns.
There is some concern among marketers that third-party cookies will be missed. More likely is that the fate of cookies will be comparable to the use of a Rolodex for customer relationship management (CRM). Useful until something better comes along.
The irony with cookies is that they were originally designed to protect user privacy. But things did not evolve as originally intended when savvy marketers realized that third-party cookies, referring to cookies not coming directly from the website a user is visiting, could track users across websites.
Speculation that the demise of third-party cookies spells a similar fate for the Data Management Platforms (DMPs), traditionally used by marketers and media agencies to handle third-party cookies, is perhaps overly dismissive. It conflates a DMP’s capabilities with its sources. The data source may need changing, but the need for a DMP may remain.
Third-party cookie data adds breadth to businesses’ in-depth first-party customer data. But it is liable to confuse personalization with relevance. For example, a consumer who has recently replaced their worn-out power drill or applied for a new credit card will be unlikely to respond to more advertisements for power drills or credit cards.
Independently anonymized global transaction data provides a more informative source of breadth than third-party cookies. Instead of culling data from abstract browsing habits across disconnected devices and channels, it focuses on actual spending habits irrespective of devices and channels. The data may be segmented based on customer type to define audiences based on industry category, spend amount, and spatial and temporal data.
What does this mean for Customer Data Platforms (CDPs)?
A common story is that CDPs, whose focus is on first-party customer data from within a business, will oust DMPs, whose focus is on third-party cookie data from outside a business.
There are two problems with the narrative: it puts too much faith in CDPs to conduct effective customer acquisition on their own; it ignores the shift of DMPs from cookie data to transaction data.
The real story is one of CDPs and DMPs working together. The collaboration is not new. What is new is the use of global transaction data instead of cookies, and a growing awareness of the potential of CDPs as they assume a more prominent role.
CDP data comes from sources such as members of retailers’ loyalty programs or logged-in customers of financial institutions. CDPs consolidate data across multiple devices and interactions, add any relevant CRM data, and then conduct test-and-learn modeling to define “audiences” based on which approaches appeal to which customers.
The approach works well with known customers. But it helps little with anonymous customers who do not at a minimum accept optional first-party cookies or register site preferences.
A solution comes from combining deep audiences, defined by first-party CDP data, with broad audiences, defined by anonymous global transaction data. The two datasets are known as “seed” audiences and “reference” audiences. A DMP can then conduct lookalike modeling by predicting which traits of existing customers will best apply to which potential customers currently transacting elsewhere.
Questions like “How do my customers spend with me?” then become, “How do my customers spend elsewhere, and how can I attract them and others like them?” The answers may be off-the-shelf and tied to specific industries or seasonal trends, or they may be bespoke.
The additional insights should allow for more effective customer acquisition campaigns.
Read part three, Customer acquisition beyond traditional marketing campaigns, to find out how to further improve by looking beyond a campaign mindset. Or download the consolidated report: Customer acquisition's three-act play.
