As consumers and professional buyers engage, interact, and purchase from varied channels, businesses struggle to attain a 360-view of customer data. The average enterprise business uses over 200 applications across their organization, lacking a central source to feed data into, and derive meaningful insights from. Simply put, data silos wreak havoc on the ability to be agile, data-driven, and ultimately, customer-obsessed. To be a success in our hypercompetitive global marketplace, businesses must invest in structural changes to their technology infrastructure, processes, and develop a culture hyperfocused on turning data into insights to deliver best-in-class customer experiences.
Zoovu’s Chief Strategy Officer, Rodney Rodriguez, spoke with Forrester Analyst Michelle Beeson, who focuses on Digital Business, to dive deeper into these challenges following a joint webinar on Readying Your Data Foundations for Customer Experience Excellence. In this conversation, both Rodriquez and Beeson provide their perspective on the importance of data-driven customer experiences and what the anecdote to bad data and poor customer experience is.
Ready Your Data Foundations for Customer Experience Excellence
1. What does data-driven customer experience actually mean?
Michelle Beeson (MB): In a hypercompetitive business environment and the post-pandemic world, applying data and analytics at every chance to differentiate products and customer experiences is a prerequisite for success. The trouble is most firms are feasting on data, but they’re starving for insight.
Data-driven businesses bring insights, not just data, into every decision.
They make data widely available, systematically convert that data into insight, and act on it in their customers’ moments of need, across the entire customer lifecycle. For these firms, digital insights and what they do with them are their secret weapon to creating excellent customer experiences, disrupting markets, and gaining market share.
Rodney Rodriguez (RR): Data-driven customer experience excellence is about learning. It’s a concept often overlooked, there is a hyper-focus on pivoting to the next trend or emerging channel, but if you aren’t taking the time as a business to learn about the context of customer experiences, you will never achieve customer experience excellence. Learning about context requires observing conversational behavioral trends and implementing new language characteristics, like messaging interfaces and search queries.
To adopt a data-driven approach to customer experience, you need to build a library of insights and increase knowledge of how customers search and engage with your brand or products.
This allows you to build better conversations with customers and understand the underlying intent and context of where they are in the path to purchase. The result is helping customers make confident and informed decisions based.
2. From a team structure perspective, what organizational roles are needed to drive a data-driven CX?
RR: Data is a component in every business function -product, marketing, sales, service, finance- because every function deals with specific data points that may pertain to a customer. From an optimal team structure perspective, each team needs its own subject matter expert who can extract and make sense of the data. While there are no doubt data analysts and scientists help propel things, you need a strong leader that sees the big picture and how the KPIs of each function ladder up to top enterprise-level objectives.
A stronger leader is equipped to form correlations from data points in other functions to develop strategies that help other parts of the organization.
There’s been an emerging trend of technology functions and the Center of Excellence (CoE) being responsible for setting global analytics strategy and reinforcing the urgency and importance of being data-driven across their organization. This will become the industry standard in years to come.
3. How can brands and retailers audit their people, processes, and technology to identify silos impacting the ability to merge data and use it to optimize CX?
MB: That is a lot to consider all at once. Setting up the technology foundation, restructuring teams, evolving processes, and transforming cultural norms to become an insights-driven business isn’t easy. Systems of insight come together under the sponsorship of a business leader such as a chief data or analytics officer, and they are more than technologies — they represent a business capability composed of people, processes, and technology.
Certainly, maturity assessments can help to identify strengths and gaps. For example, Forrester’s digital intelligence maturity assessment helps identify strengths and gaps across five dimensions of maturity: strategy, measurement, data and technology, optimization, and people. However, at the very first, firms need to start by understanding what data they have, where it is, and who is responsible for it.
In other words, identify and inventory your current silos and data constraints so that you understand the various types to which you have access and their locations.
Then establishing an effective digital intelligence strategy will encompass a longer-term commitment to technical and organizational change.
4. What is the importance of data-driven CX for achieving digital maturity?
MB: Being an insights-driven business is a fundamental part of digital maturity, as data is the driver of operational and customer experience improvement and excellence. What is more, it is a driver of revenue growth: Data and analytics decision-makers who claim that their firms have advanced insights-driven business capabilities are 5.5 times more likely than firms that are still at the beginner stage to report that their firm’s annual revenue growth by 20% or more. Insights-driven businesses analyze data to derive insights that inform business decision-making, experiences, and innovation continuously and at the scale necessary to give them the leap over their competitors.
5. What types of data and digital intelligence play a role in driving CX excellence in digital commerce?
MB: More successful insights-driven businesses, systematically applying data and analytics, and intelligence to actions that matter, everywhere in the firm. “Everywhere in the firm” is key and means that there are many different types of data that feed into this process: customer data, business performance data, operational data, and more. We often focus on customer data as the driver for creating more relevant/better customer experiences, but personalization requires more than customer data and insights e.g., product data and content, and more.
6. Conversational commerce seems to be another buzzword for chatbots, what other conversational experiences should my brand consider?
RR: Let’s put this myth to rest: conversational experiences are not limited to chatbots and messaging interfaces. Wherever you can query to get a result, that’s a conversational opportunity. Think about product finders: these are solutions that can put customers through a guided question-and-answer flow to recommend the right product. That’s a conversation.
Conversational experiences within site search have always existed, for many, their first experience with a search engine was Ask Jeeves, you had to pose a question to retrieve an answer.
There’s always been value in it but the technology wasn’t sophisticated enough. Now we have intelligent site search that integrates autocomplete, semantic knowledge, and visual components to enhance the search bar. It’s an incredibly exciting evolution in technology that serves both the customer and business with better experiences and understanding and creates an improved relationship between the two.
7. Are there any examples of brands that you see as the pinnacle of data-driven omnichannel CX excellence?
I don’t think there is anyone example of a brand doing everything perfectly. However, it is true that digitally native businesses (think Netflix and the like) are more mature when it comes to being in-sights driven. One example of an insights-driven business is StitchFix. Stitch Fix ships clothing to customers based not only on sophisticated algorithms but also on feeding what its employees know back into its algorithms.
It uses a range of data (customer behavior, sales, returns, etc.) to improve customer experience and business operations. Thus, it can sell clothes in a highly personalized way and more efficiently than its competitors. It also understands the role of culture change. Its Chief Algorithms Officer Eric Colson (who learned his skills at Netflix) told Forrester that improving Stitch Fix’s systems with insights is never an ROI-based decision. The firm’s founder understands that it competes on insights and ensures that a significant portion of its staff and investment is focused there.
