All Posts

Measuring Digital Marketing Maturity in a Complex Environment

As technologies evolve and processes are digitized, the marketing and customer experience function is being transformed.  Whether this transformation is effective depends a great deal on digital maturity. Digital maturity contains multiple dimensions, including processes, governance, core expertise, organizational design, and technologies/infrastructure. Therefore, organizations need to measure maturity in many different areas. 

It is Not About the Technology

Technology has never been a matter of procuring a tool and having the IT organization turn it on or configure it. There has always been a need for change management, training, process refinement, and organizational design.  This is truer today than ever before.  Increasingly, configuration is non-technical and more a matter of defining how a department or function handles tasks and manages information. 

Scaling Leads to Complexity

The problem is as the scale increases, complexity increases.  A process for a $1 billion company can be significantly different than that of a $500 million company.  There are more stakeholders, more products, more customers, and more interrelationships of other functions or processes.  Technology to support complex, cross functional deployments (as customer experience programs tend to be) requires a range of underlying capabilities that need to be developed or outsourced in parallel with the deployment of a given tool. 

Defining Maturity

Does the marketing organization set strategy and rely on agencies for execution?  Or is it the other way around where the agency develops the creative strategy and the marketing organization executes? Maturity can be defined in the ways the organization handles data, in how it develops strategy, how it executes across various campaigns, in the core technology infrastructure, in how decisions are made and resources deployed or in how the customer is engaged throughout their lifecycle. 

Data, Data Everywhere

At the heart of all digital capabilities lies data – customer data, product data, and process data.  Content is a form of data and digital engagement, digital marketing and customer experience is achieved through manipulation of these data constructs.  How well the organization manages and manipulates that data to present its value proposition, products and services determines success or failure in the marketplace. 

OK It is Partly About the Technology

High functionality websites that contain complex customer-facing content require the choreography of data from a range of departments and functions.  Consider a modern ecommerce site many core technologies and structures sit behind the scenes to enable a high quality customer experience.  Many of these form the backbone or foundation of more sophisticated technologies. 

Product information management (PIM) systems are a good example.  Without a capable PIM, it is not possible to stand up quality ecommerce functionality.  Everything depends on product data.  Product data tools require good product data hygiene and appropriate data modeling skills, product onboarding processes, data integration, and so on.  The same can be said for digital asset management (DAM) systems.  These systems handle non-text assets such as images and video in the context of products and marketing content.  High-profile data breaches highlight the sophistication with which the security aspect of data must be addressed.

Serving the Customer

All of this functionality is to serve the customer of course.  In order to do so effectively, clean, harmonized customer data and sophisticated attribute models for personalization are essential.  A range of customer data related processes need to be considered across different dimensions: from customer data models, to master data management, data cleansing and updates and data enrichment and integration with external sources.

Taking Stock

These infrastructure elements form the foundation upon which to build the digital experience, and each can be graded according to current state and maturity.  Infrastructure alone does not provide functionality.  With a solid foundation in place, however, other aspects of digital maturity can be modeled and measured.  A customer journey-centric view considers each stage of the customer lifecycle and how well that stage is being served by various tools, processes, and capabilities. 

Setting the Bar

Frequently the benchmark for maturity is the functionality offered by competitors; however, some industries look to other sources for inspiration. For example, B2B organizations are looking to the consumer marketplace for the types of approaches that will best serve their customers, rather than considering peers that may be behind the times. This is particularly true in industry sectors that have not been early adopters of digital marketing. Companies also benchmark against themselves, correlating increases in revenues, NPS, and other metrics with their marketing campaigns and digital strategies. 

WATCH: Taking Digital Customer Engagement to the Next Level

Seth Earley
Seth Earley
Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.

Recent Posts

[Earley AI Podcast] Episode 26: Daniel Faggella

Human Cognitive Science Guest: Daniel Faggella

[RECORDED] Master Data Management & Personalization: Building the Data Infrastructure to Support Orchestration

The Increasing Criticality of MDM for Personalization for Customers and Employees Master data management seems to be one of those perennial, evergreen programs that organizations continue to struggle with. Every couple of years people say, “we're going to get a handle on our master data” and then spend hundreds of thousands to millions and tens of millions of dollars working toward a solution. The challenge is that many of these solutions are not really getting to the root cause of the problem.  They start with technology and begin by looking at specific data elements rather than looking at the business concepts that are important to the organization. MDM programs are also difficult to anchor on a specific business value proposition such as improving the top line. Many initiatives are so deep in the weeds and so far upstream that executives lose interest and they lose faith in the business value that the project promises. Meanwhile frustrated data analysts, data architects and technology organizations feel cut off at the knees because they can't get the funding, support and attention that they need to be successful. We've seen this time after time and until senior executives recognize the value and envision where the organization can go with control over its data across domains, this will continue to happen over and over again. Executives all nod their heads and say “Yes! Data is important, really important!” But when they see the price tag they say, “Whoa hold on there, it's not that important”. Well, actually, it is that important. We can't forget that under all of the systems, processes and shiny new technologies such as artificial intelligence and machine learning lies data. And that data is more important than the algorithm. If you have bad data your AI is not going to be able to fix it. Yes there are data remediation applications and there are mechanisms to harmonize or normalize certain data elements. But looking at this holistically requires human judgment: understanding business processes, understanding data flows, understanding dependencies and understanding of the entire customer experience ecosystem and the role of upstream tools, technologies and processes that enable that customer experience. Until we take that holistic approach and connect it to business value these things are not going to get the time, attention and resources that they need. In our next webinar on March 15th, we're going to take another look at helping organizations connect master data to the Holy Grail of personalized experience. This is an opportunity to bring your executives to a webinar that will show them how these dots are connected and how to achieve significant and measurable business value. We will show the connection between the data, the process that the data supports, business outcomes and the and the organizational strategy. We will show how each of the domains that need to be managed and organized to enable large scale orchestration of the customer and the employee experience. Please join us on March 15th and share with your colleagues - especially with your leadership. This is critically important to the future of the organization and getting on the right track has to begin today.

[Earley AI Podcast] Episode 25: Michelle Zhou

Data Tells the Story Guest: Michelle Zhou