What’s Next in Customer Data Management for Consumer Marketers?

Consumer marketers have weathered a whirlwind set of years. Challenging events such as COVID-19, economic doldrums, and the loss of data from third-party cookies have taken place hand-in-hand with the emergence of new opportunities from Generative AI and predictive analytics. Each is individually and collectively upending the traditional marketing playbook. That disruption is manifesting in some concrete ways. They include reduced returns on ad spending, increased customer acquisition costs, and customer loyalty that is tightly discount dependent. These challenges are real, but they are not the whole story. On the positive side, marketers also have more options today with customer data management to help them understand their customers and deliver better experiences.

But what kind of data and how? Here, we explore the options, first by highlighting the long history of customer data in marketing.

From In-Store Customer Data to the Digital Era

Gathering data on customers is a practice as old as business itself. During the time when brick-and-mortar commerce was the only option, local businesses kept ledgers documenting which customers bought what. Word-of-mouth recommendations or complaints, or requests for specialized products or services, helped merchants adapt to customer needs. The alternative to adapting is to be passed over for a more responsive provider.

As mass-market commerce got underway, retailers had the ability to gather in-store data through cash register receipts and, later, point-of-sale systems. Advanced marketers would leverage this data to inform staffing, window displays, merchandising, and other operational requirements. Some engaged in early versions of segment marketing based on demographics such as socio-economic status, gender, and age, etc.

That era is long gone, however. We now know that the advent of the internet brought about not just more digital channels through which customers could interact and transact. It also brought more methods for gathering customer information. Third-party cookies and other tracking methods, as well as first-party data collection approaches, allowed marketers to gather customer data as an artifact of digital engagement. Brands have also been able to more easily run surveys through website pop-ups or via the IVR system in their contact center. Add in social sentiment gathering and analysis, and marketers have far more data on their customers now then they ever had in the past.

The goal of collecting all of this data is to better inform marketing campaigns, promotions, and programs. With data, brands are better able to personalize offers and messages, time those offers for when customers may be open to them, match them with complementary products, and deliver more relevant and value-added customer service to drive loyalty. But can all that data really help marketers do that at scale?

3 challenges limiting marketing ROI from customer data

A few common challenges stymie efforts to take advantage of all that data to improve marketing performance. They include:

  • Siloed data sources and ownership

As channels proliferate, so too do the sources and forms of customer data. This creates a data management challenge. As marketers struggle to access, organize, clean, and de-duplicate data and then run analysis on it. Likewise, if the data systems connected to the contact center are siloed from the data systems connected to the e-commerce website, brands will need to invest in modern data management approaches in order to make data assets available to marketing teams.

  • Too many irrelevant data points

Just because it is possible to collect more customer data than in the past does not mean that data is relevant or could be used to drive business value. On the contrary, the expense of collecting, clearing, storing and analyzing data can quickly exceed the return on the investment. Even in cloud environments, undisciplined data collection, storage, and movement can quickly lead to ballooning data infrastructure costs.

  • Data privacy challenges

A number of governments have passed legislation specifying a range of requirements and permissions around customer data collection and management. While those policies specifically apply in the European Union through GDPR and California through CCPA, they affect any business serving customers domiciled in those regions. That is true even if the business itself does not have a physical presence there.

Nor is regulation the only customer privacy concern that brands have to contend with. Studies show that one-in-three consumers will not share their data for any reason. A larger share don’t trust brands to use their data ethically. Those issues raise ethical data use as a differentiator for brands.

3 ways marketers can increase the value from consumer data

These challenges are not insurmountable. They do, however, require focus and investment in customer data assets and infrastructure. To start, consider these three opportunities to improve access and usability of customer data:

Opportunity 1: Keep it simple

Marketers have grand ambitions for delivering personalized and seamless omnichannel experiences—all informed by data. Those are important ambitions. But they require significant investments in data maturity and enabling technology, both of which can take years to deliver ROI.

There are other options. E-commerce companies can already add value and personalized elements to the e-commerce experience by leveraging web session data. Session data includes information about the customer’s device and browser, as well as what they looked at and for how long.  Persado, a Generative AI company dedicated to helping marketers deliver the best message to motivate customer action, uses session data to enable Dynamic Motivation, a personalized e-commerce experience. When applied to the online shopping cart, Dynamic Motivation can increase revenue by an average of between 3-5%.

Opportunity 2: Define your goals—and the data you need to realize them

Few brands can afford to simply collect data for the sake of having it. It is too expensive, inefficient, and too likely to lead to disappointing or undefinable ROI. A stronger approach is to set strategic marketing goals and define the customer data you need to reach them. Keep track of results. If experience shows that you need different or additional sources, add them within the context of a disciplined strategy.

Marketers will increasingly have to engage in this expertise of data identification in partnership with IT and with the office of the chief data officer (or chief data and analytics offers, depending on the title in your organization). Despite decades-long trends toward business units spending more on IT, Gartner finds that customer data management is nonetheless reverting to be increasingly under the purview of the IT team

Opportunity 3: Invest in technology to gain a secure and holistic view of the customer

There is a reason why customer data platforms (CDPs), to name one example of a high-profile data management technology, have gained so much attention in recent years. They promise to enable marketers to consolidate customer data in one place from multiple sources to create a single view of the customer. Expectations are high for this single view to enable personalization, omnichannel marketing, advanced customer experiences, and other strategic goals.

That promise has not yet been realized—though expectations are that they will. The Gartner Hype Cycle for Digital Marketing 2023 places CDPs in the trough of disillusionment, which is the phase of evolution when many organizations have invested in them, but yet to see promised benefits. Gartner predicts they will reach the plateau of productivity within the next two-to-five years.

The CDP vendor market includes dozens of options. They include CDP functionality included in major marketing technology suites like Adobe Experience Cloud and Salesforce Data Cloud for Marketing, data cloud platforms like Snowflake Data Cloud, or stand-alone CDPs like Optimove

The Persado Motivation AI enterprise Generative AI solution can integrate with your CDP or any customer data sources to inform and optimize AI-generated campaign language for top performance. Reach out to set up your risk-free trial today.

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