While Chapter 4 discussed how to align people, processes, and tools for a successful CDP implementation, you learned in Chapter 5 that not all organizations have reached a sufficient level of marketing maturity to benefit from a CDP. This final chapter of the report starts with recommendations for advancing toward a more data-driven, customer-first marketing strategy—regardless of maturity or technology used. It closes with a brief overview of what you’ve learned and where to go from here.
As has been stressed throughout the report, a change in marketing is more than just a change in technology. A successful move to a unified customer experience takes strong cultural realignments. This section offers recommendations for providing more customer-centered marketing, regardless of current data-driven marketing maturity:
Chapter 4 briefly discussed MLOps as a practice of continuously deploying, integrating, and adapting machine learning algorithms to power customer personalization. This field borrows heavily from the agile software development framework, which was popularized by the 2001 Manifesto for Agile Software Development. Agile software development emphasizes collaboration between cross-functional teams and continuous product improvement and iteration. This is to be contrasted with traditional, so-called waterfall software development, where software is built and delivered in discrete stages of the life cycle with little iteration.
While agile can be used in any implementation or project, adapting a CDP is especially suited to the practice. As mentioned in Chapter 4, it’s best to operate cross-functionally across IT, marketing, and analytics to deliver a unified customer experience. And while a CDP is designed to integrate any type of customer data, agile practices suggest starting small and iterating. It’s constantly iterative.
The key here is not to try to boil the ocean. Even if you start with only a few data sources, there’s still a lot of value in your CDP. You can then add data sources as you grow and evolve the program. You might think of it as a “crawl-walk-run” approach. You can use Agile methods to iterate and constantly improve on delivering a unified customer experience through your processes and tools:
For reasons explained in Chapter 5, customer-first marketing must necessarily be data-driven marketing. Individuals across the organization must be comfortable collecting, analyzing, and reporting on data to drive customer experiences. But many may be wary of these tasks: a 2020 report from consultancy Accenture and software company Qlik found that only 21% of employees report feeling confident in their data literacy skills.
Establishing formalized analytics training programs and communities of practice for all roles and levels serves to promote and institutionalize data literacy in an organization. With this shared knowledge basis, cross-functional teams are better able to use data together to deliver superior customer experiences. This article in McKinsey Quarterly illustrates examples of organizations who have benefited from establishing an “analytics academy” to help educate and prepare individuals across the workforce for AI-infused marketing analytics and personalization.
As organizations advance their data-driven marketing maturity, they tend to move from monolithic, single-channel campaigns to microtargeted, omnichannel ones. In the same spirit of agile development, leaders must be comfortable with releasing minimally viable marketing offerings into production and iterating over time given resources and needs. At the same time, a faster learning rate means a faster failure rate, so culturally the organization should be comfortable with these advantages and disadvantages of business experimentation. Data-driven marketing maturity also means that data is no longer left to the experts, so decisions can no longer be left to the “highest-paid person’s opinion.” Everyone in the organization should feel empowered to speak freely and make their case through data and experimentation.
When it comes to marketing campaigns, experimentation can only work with rapid and frequent feedback from customers. This feedback can be both quantitative and qualitative, in the form of customer satisfaction, product surveys, and more. User testing tools can also validate and gather early data on new features.
Regardless of the instrument’s use, customer-first organizations must make it easy for customers to get in touch. This means making it easy to find resources such as a contact page, frequently asked questions, or a telephone number to call. Many organizations have begun to use chat or chatbot features to lower the barrier and cost of providing quick customer communication touchpoints.
As in the use of chatbots, being customer-centric doesn’t necessarily mean providing human interaction at every touchpoint. Artificial intelligence can be used as a frictionless medium to handle common customer service procedures or gather information about a case before passing it to a human representative. Customer experience consultancy Servion predicts that by 2025, three quarters of customer service interactions will be driven by AI-powered tools like chatbots and voice command.
Chapter 4 pointed out that when an organization adopts a CDP, its marketing metrics should emphasize long-term retention over onetime conversions. This approach can be followed by any organization looking to put the customer experience first.
The late Tony Hsieh, CEO of Zappos, offered a master class here. The online shoe retailer famously placed no time limits on how long call center representatives spend with customers. The company even posted on its blog details about a phone call that lasted over 10 hours. In a video included with the post, Zappos employee Steven Weinstein explained that while the sale was completed quickly on the call, he stayed on the line to speak with the customer about everything from food to travel.
To many organizations, the call center is an expense to be minimized and outsourced. A 10-hour phone call would have no place in this environment. Writing in Harvard Business Review, Hsieh explained the unique Zappos policy like this: “A lot of people may think it’s strange that an internet company would be so focused on the telephone, when only about 5% of our sales happen by phone. But we’ve found that on average, our customers telephone us at least once at some point, and if we handle the call well, we have an opportunity to create an emotional impact and a lasting memory.”
Hsieh understood that in an omnichannel context, each customer has their own journey. While long sales calls with customers may be expensive, they are relative to the high cost of constantly acquiring and converting short-lived leads. Continuing on this strategy, Hsieh wrote: “Our philosophy has been that most of the money we might ordinarily have spent on advertising should be invested in customer service, so that our customers will do the marketing for us through word of mouth.”
It’s well known that retaining a customer is less expensive and more beneficial than landing a new one. Consider how you can align your marketing strategies and metrics around that truism.
Direct response marketing has come a long way since the same Sears, Roebuck and Company catalog landed on every doorstep. Powered by a proliferation in devices and channels, today’s consumers interact with brands in unique ways—and expect brands to offer personalized experiences based on those touchpoints. Earlier marketing technologies, like customer relationship management and digital marketing platform systems, tended to focus on specific engagement points and channels, often at the customer acquisition and conversion stages. While still valuable technologies, the customer data platform adds to the marketing stack by unifying customer data across platforms and touchpoints. This aids in personalization of experiences, and ultimately, retention.
Regardless of the tools used, however, every organization must chart its course on the road toward being customer first. By assessing your organization’s current maturity in Chapter 5 and adopting the practices listed in Chapter 6, you will be on your way to designing a customer-first organization.