standing on top of a stack of containers
The customer experience stack has undergone transformations in the last 15 years and will continue to change in the future. One thing remains constant though: the focus on the customer PHOTO: hawjin jami

The biggest change in customer experience since the mid-20th century undoubtedly has been the introduction of choice. Gone are the days when consumers in certain areas had just a single department store, bank or car dealership to choose from, and only one telephone provider to choose. People have so many options today that they are often afflicted with “analysis paralysis” or “FOBO” — fear of better options. 

The question now becomes, how do consumers traverse the market to make the right decisions for their customer experiences? It can be difficult. As a marketer, my answer is this: Marketers should help consumers by providing offers they simply can’t refuse — offers that are delivered at the appropriate time with the correct variables. However, marketers can only deliver such offers if they have solid, modern and complete customer experience (CX) technology stacks inside their organizations.

The customer experience stack has evolved over the past 15 years, and I believe there are signs of how it will continue to evolve over time. A close look at the elements of the CX stack from the ground up — the data, the analytical methods and techniques, and the interfaces or applications that sit at the very top of the stack — all reveal the changes of recent years and provide hints of what's to come. 

More and Better Data

The data environment of earlier CX stacks consisted primarily of first-party data that failed to provide a realistic look at an organization’s customer base because it was incomplete and inconsistent. As a result, organizations rarely had a realistic view of customers that could support sound marketing decisions. Data is the foundation and most important component of the CX stack, and poor underlying data was causing CX programs to fail left and right.

We have certainly seen a change in this area. Organizations are now leveraging owned (first-party), earned (third-party) and bought/paid-for data to augment data from traditional sources. Additionally, thanks to the advent of applications that collect or “scrape” data off new and emerging channels such as mobile apps, devices and vehicles, marketers today have more data than ever. Data management, data quality and big data cluster computing applications like Spark allow organizations to store and transform data into structures that prepare it for analysis. Data volumes today are large and robust — providing the fuel and a solid base that CX stacks need to operate.

Advances in Analytics

The analytics component of customer experience stacks should be approached from two different vistas: methods of performing analysis via analytical providers and the analytical techniques that are being used inside of CX stacks.

In the past five years, we have seen the emergence of many new analysis methods. Previously, analysis was performed in siloed development or test environments, often by aging applications. We weren’t quite sure if the results were correct. Analytic code bases were closed and expensive, and analysis methods were cryptic.

The pendulum has now swung in the other direction. Citizen data scientists are using open-source environments like R or Python to perform analysis. Applications like those are cost-effective, easy to obtain and easy to learn and use. Libraries from H2O or TensorFlow can be imported into those open-source environments, and analysts and data scientists can leverage analytical work previously performed by others to advance the analytical maturity inside their organizations.

Additionally, new analytical techniques are being inserted into CX stacks. We have moved from basic segmentation and targeting techniques to advanced predictive and prescriptive models that are leveraging artificial intelligence and machine learning algorithms. Organizations are starting to experiment with deep learning; they are using neural networks and decision trees to guide customers on journeys. Internet of things analytic tools are being placed at or on the “edge,” allowing brands to easily analyze the behavior of devices, vehicles and objects in many different environments.

Techniques such as geospatial analysis and geofencing are allowing brands to deliver offers based on present or predicted future locations. Complex optimization scenarios allow brands to test and simulate potential business decisions or tradeoffs (such as offer volume to ROI) before pushing CX programs into the market. These are just a few of the techniques that were not present in CX stacks just 10 years ago. CX stacks will benefit from the continued evolution of analytical methods and techniques from providers and the open-source community.

New Interfaces and Applications Emerge

Traditionally, CX stacks have been made up of what I see as core components plus additional or auxiliary functionality. The core components are the ones that people are most familiar with: customer relationship management (CRM) systems, campaign management tools, email and SMS marketing systems, customer service/contact center applications, marketing resource management (MRM) tools, and marketing automation and lead nurturing systems, plus a content repository or content management system (CMS) of some form.

Over the past 10 years, the focus with these core components has been ease of use and support for collaboration. However, with the emergence of newer additions to the CX stack — such as web and social analytics, social publishing, demand-side platforms and programmatic media, and paid and organic search — providers of large commodity solutions are being forced to shift gears. The newer CX offerings complement the core functionality of the big commodity systems and are commonly (though not always) more niche in nature. These newer systems in some cases only serve one marketing channel or address one touchpoint. And some new offerings are built for just a subset of a particular channel — for instance, a tool may be designed to just monitor the social media channel rather than offering full social publishing capabilities.

A Look at the Future

As the CX stack evolves, I believe that the systems that integrate well with new data sources, are easy to use and solve one or many problems in a clear manner will be the ones that are going to thrive in the CX stacks of the future. Some of the newer components of the CX stack — social publishing and web analytics, for example — will continue to mature. The commodity systems will become more commoditized and consolidated, just like the large mature software applications of the past. As a result, I think we will see the freemium/open-source CX ecosystem further evolve. Moreover, the number of smaller vendors entering the CX and marketing technology markets is only going to increase. As these changes take hold, it will be interesting to watch the movements of the big providers of cloud-based marketing tools: Will they attempt to guard their positions, or will they embrace the new CX stack entrants?

As for the overall customer experience, companies will find that their ability to deliver critical marketing messages at the point of need will continue to advance. Thanks to the ready availability of a wealth of high-quality data, the continued evolution of analytical techniques, and the emergence of tightly integrated CX applications, brands will become even better at identifying who their customers are, where they are, and what they may need or desire next. No longer will marketers have to guess when and where consumers interacted with them last.

I encourage brands to continue this journey toward customer intimacy and delight, because the customer experience will be sole differentiator — over even product and service quality — in the very near future.