Martech selection – purchasing, updating, and eventually retiring marketing software – is a critical and complex task for ambitious marketing teams. Every organization has to strike balances: between best-of-breed and integrated stacks; between current needs and future desires; between “sky’s-the-limit” transformed customer experiences and concrete limits on tech budgets, personnel costs, and organizational change. Customer engagement software will help brands to compete with a personalized, omnichannel customer experience, but making sure all the pieces work together for both the marketing team and the target customers can be fraught. A reading of the tea leaves for what might be needed in a year or two in response to evolving customer expectations is as much a part of the calculation as what’s needed today. Application rationalization – defining what the new customer engagement software will be used for and deciding what it will displace and what it will interface with – makes choices much harder. Further complicating matters, the balancing act must also consider corporate goals along with marketing goals, recognizing that the two may often be – if not in juxtaposition – at least not perfectly aligned.
Assembling the right martech stack when the end goal is a personalized CX is like trying to hit a moving target. The number of channels and data sources are expanding, customer behaviors are changing and expectations for a holistic experience are deepening. Customers make no distinction between interactions with marketing, service, a call center, billing or another department. The experience a brand delivers must be seamless, and a martech stack must reflect this new reality. Siloed data and a network of unintegrated point solutions are chief culprits in creating a disjointed customer experience that will alienate customers. According to research from PwC, 88 percent of consumers would increase their likelihood of a purchase with a more personalized experience. Conversely, 52 percent are less likely to engage with a brand because of a poor digital experience.
Omnichannel vs. Multichannel
With consumers crystal clear that they will not tolerate a subpar experience, having a customer engagement application for each channel is no longer sustainable. The technology itself, however, is just one consideration for successful application rationalization. People and process issues must also be taken into account. A company that consolidates its martech stack and successfully eliminates data siloes between channels will still introduce friction into a customer experience if the teams that manage those channels continue to operate independently. A team of call center agents blind to the activities of the team managing email campaigns may be without pertinent information when fielding a customer inquiry, for instance. And lack of coordination may be exacerbated when goals and KPIs are not aligned across teams and channels. For instance, reducing Average Handle Time (AHT) in the call center has been used as a success metric, but this may be directly opposed to understanding customer needs and working to resolve any questions or issues.
Consolidating technology, people and processes to better meet the expectations of an always-on, connected consumer reflects an understanding that becoming omnichannel is different than merely being multichannel. The former implicitly recognizes that the consumer is in charge of a nonlinear, nonsequential customer journey. Interacting with a customer with precision and relevance requires collecting and acting on customer data in real time. A single view of the customer that is updated and accessible in real time helps ensure a frictionless experience. With a single view, every customer-facing team has the same updated, real-time view of where the customer is right now in a unique customer journey and can deliver a next-best action that is true to the customer’s current situation. A multichannel approach, by contrast, may optimize for a specific channel but without integrating the technology, people and processes it will be hamstrung – always one step (or more) behind a customer likely to flit between channels.
Measurement Dimensions to Consider
Turning toward the technology part of application rationalization, every company faces the problem of obsolescence, which applies to both software and the corporate and/or marketing goals that were in vogue at the time the software was implemented.
An honest accounting of technology needs that will meet customer expectations for personalized experiences today – and hopefully in the future – will first determine what its new CX goals are, and try to align what matters to the customer with what matters to the C-suite. A customer, for instance, will not have the slightest interest in a corporate objective to reduce churn, but a delightful experience may produce an identical result.
To align what may be competing objectives, it becomes important to identify key metrics and determine how to measure those on a consistent basis, meaning that there is assurance that measurements are an “apples to apples” comparison both over time and on a channel-by-channel basis.
Another element of measurement, particularly important with the moving target of a personalized CX, is measuring a default state against a proposed possible outcome – a wide lens approach to a/b testing that encompasses the totality of goals that pertain to customer experience. A product recommendation engine optimized for a personalized approach, for example, would presumably be required to produce a result at least marginally better than recommending the top 10 best-sellers.
Not All CDPs Are the Same
Application rationalization is never routine when it comes to customer engagement technology, as Scott Brinker’s iconic Martech 5000 graphic makes clear. As of April, there were 8,000 solutions listed – a 13.6 percent increase since 2019. With such an over-populated and diverse landscape, a rationalization or acquisition team has to look hard at team and corporate goals when assessing technology needs – and projecting how those needs will impact people and processes.
In the crowded customer data platform (CDP) market, especially, the task will require that a company have detailed descriptions of intended use cases, as well as a firm understanding of the distinctions among various CDPs. The CDP Institute provides a handy guide on CDP basics, and its RealCDP™ Initiative offers a set of five features a “real” CDP must include. Is a CDP that promises data orchestration, for example, really just segmenting an audience, moving customer data into one channel or another and then “orchestrating” an experience for the segment within that one channel? This distinction of how much of this “last mile to the customer” is orchestrated and automated by an engagement platform cuts to the core of what it means to be omnichannel vs. multi-channel.
A real time component, as mentioned above, is another key distinction. Another is the determination for how to bring customer data together to form a single customer view, which entails questions related to probabilistic and deterministic matching, householding, and other data quality considerations. There are also a host of non-functional requirements related to privacy, compliance, auditability, latency, scale, timeliness, etc.
Each of these considerations should balance corporate goals and customer-focused goals, delivering a superior customer experience that meets the lofty expectations of today’s always-on, connected consumers. Customers demand excellence, which makes a detailed application rationalization of a customer engagement landscape worthy of the exercise.