Understanding the Challenges of Customer Experience Convergence
Customer experience used to be the marketing team’s responsibility. Now, however, customers increasingly expect to be recognized and engaged with their context and channel choice along a growing number of digital and physical touchpoints during the marketing, sales, commerce, service, and product stages of their journeys. Meeting these expectations requires businesses to rethink nearly everything, including how they leverage customer data across the customer journey, the skills required to deliver experience convergence, the technology required, and the way organizational structures must evolve to keep up.
Why implement experience convergence if there’s so much work and change involved? With 96% of customers (B2C and B2B) saying that “excellent customer service builds trust,” creating a seamless experience across the customer journey is critical for long-term loyalty. Stronger customer connection is the main motive for working toward a new CX paradigm that, perhaps surprisingly, evokes the person-to-person, local customer service of the pre-internet past.
Personalization at scale works well now–except when it doesn’t
In that era–and still now in local shops with regular customers and attentive staff–shop owners and employees often knew their clients by name, knew something about their preferences and needs, and were perceptive enough to know when someone might need help or appreciate a customer service flourish to raise their mood on a difficult day.
Technology solved the scale problem by helping businesses aggregate and segment customer data to provide generalized experiences at scale, and this approach has helped brands reach many more customers than they ever would have in the pre-digital world. However, the individual gets lost in these experiences. That can lead brands to create unintentionally frustrating experiences for some individual customers–experiences that can erode their relationship. For example, many of us have had the experience of being followed around the internet by targeted ads for products or services after we’ve already purchased them or after we’ve had a negative customer service experience with the brand. What would otherwise be effective personalization becomes annoying messaging that indicates the brand doesn’t really recognize us at all. At a time when 73% of consumer and business customers say they “expect companies to understand my unique needs and expectations,” it would be better for these brands to be able to immediately switch off ads for products that have already been bought and to pause ads when the customer has an unresolved or recent negative experience.
If a brand delivers consistent experiences that reaffirm their recognition of the customer, they’re in a better position to drive loyalty and conversions. For example, a customer who is wrapping up an excellent customer service experience might afford a potential selling opportunity at this point, because they’re already feeling especially good about the brand or product.
In our digital era, it’s simply not been possible, until recently, for a brand to know thousands or millions of customers personally, especially if they’ve never had in-person contact with them.
Convergent CX technology requires new data organization strategies
Now, a new generation of technology offers a way to create consistent CX by unifying data and processes in a new way, to recreate the shopkeeper-customer style of relationship without sacrificing scale. However, it’s incredibly challenging to deploy the technology required for successful experience convergence, because it requires changes in the way companies handle data, structure their organizations, and select talent. Right now, the vast majority of organizations are fragmented, with teams operating mostly in silos with their own data. To converge CX, companies need to stitch together their product, marketing, sales, and service experiences. That in itself is complicated and requires collaboration that many companies aren’t used to doing.
Because of the complexity involved, many of the companies that are forerunners in experience convergence are still at the experimentation stage. They may have purchased a customer data platform (CDP) and a journey orchestration platform to sit on top of the CDP, but it’s still rare to see customer journey orchestration at scale. What’s more common is for companies at the CDP and orchestration platform stage to stand up a few key use cases where it’s relatively easy to bring in data from different sources without stressing the platforms. This is a wise approach because there’s so much data to sort through that unifying absolutely everything may be unnecessary and impossible. Rather than try to bring every piece of data about every customer into the CDP, it’s important to focus only on the data that’s required for activation and for this, timeliness and latency are top priorities. This is how companies can avoid advertising products that customers have just purchased, and how they can identify upsell opportunities in real time during a positive customer service experience.
Once the relevant data and its sources are identified, the next step is to think about how that data should be architected. During this part of the planning process, it’s important to keep in mind the role of different data storage solutions. In general, data lakes are optimized for analytics and CDP platforms for activation. So, relevant activation data for creating delightful customer experiences belongs in the CDP, while the data lake is a more cost-effective and scalable place to store full sets of customer 360 data.
CX convergence requires new skills and collaborations
Rethinking data is one part of the complex convergence challenge. Rethinking the way individuals and teams work is another. Managers need to have the full customer journey view and they need to know which algorithms can support that journey, so there’s a growing need for data scientists and tech skills.
This is increasingly driving a skills deficit in marketing, with just 44% of firms saying they have the data science or AI/machine learning skills they need.
But driving end-to-end experiences requires bringing together multidisciplinary teams from IT, sales, product, commerce, service, and marketing. As with data, the challenge here is to discern the right skills and roles for these teams rather than expecting everyone to do everything. There are different options for organizing these teams (rather than the traditional siloes) including customer journey based although there may be redundancies if the structure is too rigid because many basic capabilities are often similar at different journey points. Most companies are adopting a more incremental approach, using temporary co-located teams based on pods or scrum type methodologies and focusing them on specific use cases. This allows for experimentation and learning that can make it easier to ramp up the number and complexity of journey teams over time.
Starting small and scaling up slowly seems to be the overarching theme with customer experience convergence, and it may be the only way to handle the changes required in terms of data, technology, processes, and people’s team assignments. The payoff can be a more accurate and up-to-date understanding of each customer, so that they feel recognized and delighted at every touchpoint, and more loyal to the brands that reliably provide that recognition and delight.
Duncan Steels is a Vice President and practice lead for Capgemini frog Customer Transformation practice. Duncan brings over 20 years of experience leading the development and execution of customer experience driven business strategies and transformations. He has delivered multiple customer experience-based strategies and digital transformations across commercial organizations for Capgemini in a variety of sectors. Prior to joining Capgemini in 2015, Duncan worked in a variety of consulting leadership roles in the professional services, life sciences, financial services, retail/consumer packaged goods (CPRD) and insurance sectors.