Why digital transformation is failing CX – and how it can be saved

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80% of enterprises across all industries are struggling to make headway with their customer experience initiatives. So what is going wrong? And how can customer engagement platforms help?

While growth, operational efficiency, and cost reduction remain the top three drivers of digital transformation initiatives identified in Ovum's ICT Enterprise Insights 2018/19 – Global: ICT Drivers and Technology Priorities research, customer experience improvement is the leading strategy to achieve these aims for around half of the 4,899 enterprises surveyed.

However, around 80% of enterprises across all industries are struggling to make headway with their customer experience initiatives, and there are several reasons for this.

Departmental silos, poor data quality, an inability to surface relevant data and apply real-time analysis, and a lack of understanding of the current art of the possible from a technology standpoint have all contributed to this lack of progress. Trying to solve the challenge one department at a time or by integrating point solutions is a recipe for delay, hidden costs, and, above all, disappointment for customers.

In this summary of the Ovum research report The Critical Role of the Customer Engagement Platform for Growth, I’m going to share advice to steer the deployment of technology in your CX initiatives wisely, and also look at why many digital transformation projects related to CX are failing – and how they can be rectified.

Four critical attributes of customer experience

Figure 1 below highlights the four core attributes required to deliver a positive and relevant customer experience. By focusing on these you can ensure you get the balance right with CX initiatives and deploy your technology investment wisely.

CX attributes


Recognise the customer

Customer and persona (if not yet a customer) recognition is essential to form the basis of any personalisation.

In B2B environments, this is typically less of a challenge than in high-volume B2C settings, although anyone interacting with the customer – for example, when the customer seeks – help must recognise the customer. In some industries, such as retail banking, recognition is achieved through the login and authentication process, whereas commerce customers may browse for some time before declaring their identity, if at all.

The underlying data about customers, such as their history as well as their live interactions, must be unified to determine their contextual needs. In high-volume B2C environments, customer data management is not just challenging, but also critical. Customer recognition is an important first step in developing a longer-term relationship, and it goes deeper than just identity, to the previous history with that customer and recognition of implied intent, based on the customer's interaction journey.

Protect the customer

Protecting customers starts with protecting information about them and being completely transparent as to the intended use of that information. This includes cybersecurity, protection from fraudulent use of their data, respect for their privacy, permission to use their information, and giving customers control over their information, not just to comply with any regulation such as the EU's General Data Protection Regulation (GDPR), but, above all, to foster trust. Inappropriate content must also be shielded from minors.

A permission-based approach to gathering and using customer data is essential to create transparency and foster trust, and with almost weekly reports in the media of major failures, there is now heightened sensitivity to this critical attribute.

Orchestrate the experience

Customer journeys are less predictable than most CX planners would like. Rather than a series of linear and logically organised interactions to achieve an obvious aim, they can be chaotic and may start from any point, device, social network, deliberate search, or response to a campaign.

The customer experience challenge is to orchestrate relevant content, advice, and offers or respond in the most relevant way. In a high-volume B2C setting, rules-based approaches are ineffective. This is where machine learning and automation have a major role to play. The ideal is that every interaction journey, however chaotic, will be dynamically supported at each step. Sometimes this will require human interaction, but increasingly, customers like to find their own solutions or products without the need for human guidance or, as they might see it, interference.

This creates two major challenges in high-volume B2C environments:

  • Continuity of experience across multiple channels or devices, including physical locations.
  • Real-time prediction to trigger the right action.

The first of these challenges requires technology and process support for omnichannel customer journeys. The entire value chain or network may be involved, which is why this is so complex and progress to omnichannel is glacially slow.

The second challenge is to surface relevant data, perform machine learning analysis on the fly, and trigger the most relevant action, content, or guidance, based on the customer's individual context, and better still to preempt potential issues before they become a problem for the customer. Classic relational databases are not equipped to do this, in part because of unacceptable latency, and because they are designed for structured transactional data, not the chaotic unstructured data that surfaces during customer interactions. That is why, in these chaotic environments, graph databases, data lakes, and data pipes are being used to feed AI with relevant and real-time data.

However, even equipped with Big Data technologies and good data management disciplines, most vendors are still at the early stages of providing algorithmic omnichannel support. Again, this is no surprise, as the low-hanging fruit for AI is to provide in-application support for end users, such as micro-segmentation, attribution for marketing, propensity to buy and guidance in sales, and contextual ranking of FAQs in self-service portals.

The customer experience challenge is to orchestrate relevant content, advice, and offers or respond in the most relevant way.

To cover the length, breadth, and innumerable permutations of chaotic omnichannel customer journeys, ML will have to be connected, drawing on real-time data wherever it resides or is being created, and permeating every interaction point. Outputs from one set of algorithms will be inputs to another, communicating with each other like fireflies in the night, creating a digital neural network. As a challenge, from an AI perspective, it is akin to the driverless car.

In the meantime, we are likely to see a combination of localised ML allied to rules-based approaches to trigger the most relevant action, across the more well-trodden customer journeys, such as basket abandonment on a commerce site and propensity to churn. Connected AI is on the horizon, but it is unlikely to be commonplace for several years, until vendors have done more to accommodate complex use cases and near-autonomous reactions become trusted.

The traditional mechanisms for adaptation are the Voice of the Customer/Employee (VoC/VoE), use of sentiment analysis from social networks or instant post-purchase customer feedback, and the monitoring of review sites and analysis of calls between customers and agents in the care centre. These techniques are still of great value, particularly in surfacing systemic weaknesses or triggering a rescue action if a customer's low score indicates a potential defection.

However, being able to sense and adapt at any point in the customer's interaction journey demands advanced and connected ML to deliver dynamic orchestration.

Why digital transformation is failing CX

52% of enterprises reported being at the early stages or had not even started their omnichannel customer engagement transformation initiatives despite declaring the critical importance of these initiatives to their businesses, and less than 10% believe they are on top of omnichannel, the remainder making some modest progress.

So why is progress so painfully slow?

From an IT perspective, one of the reasons is that far too many firms are still banking on yesterday's tools, most notably CRM, to provide the underlying solution. They continue to invest in point solutions to provide the answers and use CRM or subsets such as customer service, marketing automation, and sales force automation. These tactical approaches, often driven by individual lines of business, merely perpetuate fragmentation, organisational silos, and a broken customer experience. Like the Gordian knot, they are devilishly difficult to unpick and adapt, creating a barrier to change.

This is why a platform approach – among other considerations, such as a clearsighted strategy for customers – is essential. The right lens is not that of the CMO or sales, but from the perspective of the customer. To succeed, the enterprise must act as a coherent, connected, and informed system of value creation and delivery, with the customer at the center of all thinking and action. Firms that get this right will enjoy growth and persistent customer relevance. Those that take a fragmented approach to the customer will fail and lose relevance – the route to oblivion.

In recent years, line-of-business heads have been the main sponsors of CRM applications, with little regard for customer experience or adjacent departments that might be impacted.

When evaluating platforms, look for a unified environment that supports a coherent enterprise and demand to know how customer interactions can be supported, especially when their infinite variety of journeys cannot be second-guessed. Customer journey mapping is great for building consensus across departments, but it is at best a proxy for reality, and customers, whether individuals or members of a decision-making unit, have a habit of acting in less predictable ways.

We continue to stress the critical importance of taking a coherent and holistic approach to customer engagement if the customer experience is to be significantly improved.

In recent years, line-of-business heads have been the main sponsors of CRM applications such as marketing automation, service automation, and sales force automation, with little regard for customer experience or adjacent departments that might be impacted. As enterprises seek to open up online routes to market, a more strategic approach to commerce applications has been taken, where more of the C-suite has been involved in the decision-making, as the impact is felt across multiple departments, including marketing, sales, billing, supply, logistics, and after-care service.

It has taken a while, but Ovum has detected, at least anecdotally, that now customer experience is seen more as a collective concern, and that both commerce and former CRM applications and engagement systems must be approached more thoughtfully and collaboratively to create an interconnected foundation for growth.

Fear of potential lock-in to a single vendor is being trumped by the need for more rapid development, more seamless integration, and lower costs. Platforms are now seen as a better way to break down organisational barriers and take advantage of AI that can span multiple departments and support customers throughout their near-infinite customer journey permutations. Taking an outside-in view from the customer's perspective makes sense, and a mechanism for orchestrating the experience, irrespective of channel, supports the case for an integrated platform rather than a hodgepodge of disparate vendor solutions that will only reinforce organisational silos.

The solution?

What is required is a unified and connected customer engagement platform (CEP) to act as the membrane between the enterprise and its customers. The aim is to orchestrate relevance throughout all customers' interaction journeys, turning the traditional value chain on its head: to become a demand chain, or more accurately, demand network, with the customer as the catalyst and value co-creator through consumption.

Ovum signaled this emerging category in its 2016 Trends to Watch: CRM report and again the following year, culminating in the Ovum Decision Matrix: Selecting a Customer Engagement Platform, 2018–19 in August 2018.

The anatomy of a CEP consists of six enabling technology layers, culminating in a seventh orchestration layer.

[Click to enlarge]

customer engagement platform

These layers are illustrative, and the configuration of vendor CEPs will differ, but they should contain these building blocks. In August 2018, Ovum assessed 10 vendor CEPs and found that dynamic orchestration of the customer experience is still a way off for the majority. To a great extent, the low-hanging fruit of functional support – for example, to support sales, make some simple product recommendations, or tee up the right recommendations to a service agent – were in evidence. The leaders have made some progress toward cross-departmental ML support, but more needs to be done. The direction of development travel is, however, encouraging.

While we have seen a rise in the number of chief digital officers and chief customer officers entering the C-suite in large enterprises, many will be unaware of the emerging CEP category. Modern CIOs who act as key advisors on the enabling technology available must also learn about this critical category. Ultimately, it is the CEO's responsibility to create a vision and chart a course toward a customer-centered enterprise that is able to sense, respond, and adapt at the right frequency to ensure persistent customer relevance.

Leading customer engagement platforms provide a mechanism for removing departmental and data silos that plague so many organisations today. They provide real-time insight into customers’ needs, behaviours, and intent, and they can trigger the most relevant action, content, recommendations, and guidance at every interaction moment. Customers may interact with many different parts of the value chain or value ecosystem in the course of their many different interaction journeys. By deploying the right CEP, not only will digital transformation progress faster, but the enterprise will be able to present the coherent organisational face today's customers demand.

While we have seen a rise in the number of chief digital officers and chief customer officers entering the C-suite in large enterprises, many will be unaware of the emerging CEP category.

The traditional feedback and the more modern feedback loops can also work in conjunction with a CEP to provide a complete picture of customer journey traffic, its consequences, and behavioural changes – for example, adoption of a new or more convenient channel.

CEPs provide a foundation for a more consistent omnichannel customer experience. They also provide a highly adaptable platform for continuous change. Once the basic consistency is in place, CEPs can be augmented with applications and technologies that engage customers at a more emotional level – such as augmented reality, connected IoT in products, subscription-based products-as-a-service, and other emerging technologies that can excite customers and increase the value they receive.

By using a customer engagement platform as the mechanism to dynamically orchestrate relevance at every interaction point, the enterprise has a much better chance of creating a platform for growth, enhancing its reputation and adapting business models to pursue new opportunities.

A change in approach is needed

While the levers of profitable growth are timeless, what needs to change is how enterprises engage with their customers and, more importantly, how they enable customers to engage with them. Digital transformation progress for many organisations is far too slow, which is an existential risk.

CEPs are an emerging category of primarily, but not exclusively, advanced and extended CRM solutions incorporating commerce and providing hybrid systems of engagement and record. This means they are less understood by enterprises than the traditional CRM applications or distinctly separate customer care or commerce solutions. There is a major understanding gap between the art of the possible today, with too many influencers and decision-makers locked into legacy CRM thinking. The risk is that investment decisions might be made on the basis of yesterday's art of the possible, not today's.

The race is on to focus digital transformation on better ways to compete for customers, new and existing, and to build enduring and mutually beneficial relationships to deliver profitable growth. To succeed, every customer interaction, whether digital or in person, must be supported. Rather than cobble together a series of departmental functional systems, over multiple years, leading companies are investing in CEPs integrated into their entire value chain.

This goes well beyond the narrow transactional CRM systems environment. Competition to develop these platforms is fierce, and innovation is accelerating. CEPs are a mechanism for orchestrating the entire customer experience, and it is critical that they are fully understood by both business and IT, as they offer a faster track to successful customer-aligned transformation.

 

 

About Jeremy Cox

Jeremy Cox

Jeremy Cox is a Principal Analyst in Ovum's Customer Engagement team, helping enterprises develop omnichannel customer engagement capabilities to deliver positive customer experiences.

He leads research and insights into CRM and customer engagement platforms (CEPs) and their potential for spearheading customer-driven business transformation (the customer-adaptive enterprise).

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