Today’s current business climate is one of unprecedented change and a seemingly endless need for adaptation. The organizations which are charging forward and thriving—and the ones who will continue to do so—embrace technology to help drive a more customer-focused strategy. The question now becomes: How can you deliver on the promise of a customer-centric approach? The best way is through data analytics. Using this approach can help companies, and their leaders, plan for new challenges and opportunities, now and in the future.
As we have all experienced, consumers’ expectations are higher than ever before. They demand next-level convenience, product offerings, and customer service. So companies are working harder to anticipate what they want, when they want it, and how they want it. But, of course, consumers are not all cut from the same cloth. They all have different needs, ideas of what they value, and how they behave. This is where data analytics can be used to help implement strategies that target consumers and deliver a customized experience that speaks to their needs—and spurs action and engagement for an organization.
Recently, a popular basketball franchise realized it was falling behind. It needed a new way to engage with fans, one that was frictionless. They started by reimagining the consumer experience with their organization. What did the journey look like at every touchpoint? How could they make the experience and interaction better? The answer was to expand the franchise’s digital footprint. By doing so, they were able to bring fans closer to the action while still helping their bottom line—maximizing attendance and growing revenue. A new state-of-the-art CRM system and digital repository that reduced redundancy and inaccuracy in marketing messages to fans was created. This new CRM was integrated into the team’s mobile app, which opened up a clear avenue to track purchasing decisions and customer behavior.
Now, the capability existed to monitor attendance as well as merchandise, food and beverage purchases. With this information, the organization can now easily adjust prices in real time to make sure no seat is left empty. And, with an AI platform integration, fans are able to find the shortest lines for concessions, bathrooms, and even parking spaces through the app.
Enterprise data quality
Janet Balis, EY Americas CMO Practice Leader, sees a trend like in the sports’ franchise case study above. “The customer experience has more choices and optimization points than ever before and the only way to enhance it is by using more advanced technology,” she says. Data analytics can play a big part in moving the needle. How data is handled and the quality of it is extremely important. Enterprise data (data retrieved from ERP and CRM systems) must be part of a systematic approach, “one that powers the effort and takes into account the different parts of the operating and capability models that are supported by data preparation efforts,” says Balis.
Carrier, the maker of indoor air-quality systems, had a legacy system that was clearly holding back the company’s growth and transformation. Its systems relied on manual processes that caused inefficiencies along many parts of the supply chain. In order to correct this outdated strategy, they used a database management system and EY technologist to integrate multiple ERP systems from around the world. This allowed all data to be in the cloud, on a single platform, which in turn let Carrier and its customers easily access needed information to make better-informed decisions. By developing this solid foundation of data, Carrier now has a holistic view of its customers’ needs, which it can use to identify new opportunities to add value and drive growth, including the development of a new D2C business.
In terms of quality, it is important to look at data derived from both internal and external sources. Data quality is a foundation that, if not solid, can negatively affect a business in both the long and short term. For example, it can prohibit organizations from reacting to new market opportunities, negatively affect cost reduction programs, hinder meeting compliance requirements, and surface challenges in using predictive analysis.
Companies that successfully use data analytics outperform their peers by up to 20%*. When looking to achieve good data quality, a cleaning service such as the one developed by Ernst & Young LLP can be helpful. Initially there is a data health assessment, followed by a road map, which outlines various recommended data cleansing initiatives. The data cleansing and data quality monitoring services are also integrated in the clients’ end-to-end analytics solutions to provide continuous cleansed data for the life of the analytics initiatives.
Once data quality is established, the focus should then turn to effective data management capabilities such as process, governance, and the right technology architecture. “The right talent model and a data-driven culture are endemic,” says Balis. “If you do that right, you can move yourself from having the right sources of data to being in a position to take action.”
Effective data lake mining
More and more, businesses are acknowledging that they must employ artificial intelligence (AI) and machine learning algorithms to help them capitalize on smart opportunities. However, these tools require copious amounts of data in order to be used effectively. This is where data lakes—repositories that store large amounts of structured and multi-structured data—come in. They allow for data to be securely stored and analyzed. The datasets in the lakes are accessed by various people within the organization who can then apply their preferred analytic tools, like machine learning, to sift through and find the right information for their department’s project. Being able to collect and analyze datasets in one centralized location is changing the way organizations strategize.
Micro-segmentation
Micro-segmentation is a way to develop a focused approach to serve customers better. Rather than just looking at broad target groups, smaller (or micro) groups can be identified based on interests, purchase and search behavior, lifestyle, and more. This is culled from the information a company has readily available on its internal systems and layered with external data (free or purchased). “By not only using your data but using other data sources, you can gain a more complete picture of how you interacted with a customer in the past and how you will interact with them in the future,” says Brian Moore, Principal, Technology Consulting, Ernst & Young LLP. From there, it is pivotal that a relevant and timely communication strategy for these micro-segments is developed in order to create a more personalized consumer experience.
A leader in the cruise industry is doing this well. Working in tandem with Ernst & Young LLP, they developed a customer personalization engine using data analytics. This advanced system allows guests to have mobile control over many different touchpoints in their cruising experience. It started with facial recognition technology deployed in the terminal for faster boarding. Then through the personalization engine, an app was created—one which uses AI to learn and track passenger preferences from the moment they step onboard. This information is then used to provide recommendations for available activities and programs based on passengers’ behavior.
While data can be an extremely useful tool in developing and growing business, the importance of the human components—employees’ skills and customers’ wants and needs—must be taken into account, even when assembling a more aggressive data-driven approach for a customer-centric strategy. “It’s not just about data and technology but also about the people, which companies sometimes forget,” says Balis.
It is commonly thought that through data analytics the impossible can be made possible. The technology surrounding the way it’s collected, stored, organized and used is constantly advancing. This will help the companies who use it right to gain the competitive advantage and radically change how business is done.
Sources: EY and Xplenty survey; Business Services Week
Technology in Action continues on Wired with additional stories of innovative ideas to drive business forward, including expert tools to handle challenges facing CIOs today as well as tips on how to be an effective tech leader.
Disclaimer: The views expressed by the authors are not necessarily those of Ernst & Young LLP or other members of the global EY organization.
This story was produced by WIRED Brand Lab for EY.
