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This year, revenue from the “big data” market is expected to reach $49 billion. The exponential growth of data from multiple sources is a challenge for marketers who seek to understand their customer data and employ it intelligently.
Companies that invest in resources that harness, unify, and act on their customer data have a distinct advantage over those that don’t. They’re leading the way in an era of big data by using artificial intelligence (AI) and machine learning (ML) to create personalized experiences for their customers across the entire breadth of the customer journey.
Recently, ClickZ spoke with Ronell Hugh, Head of GTM Strategy & Product Marketing for Adobe Experience Platform about Adobe’s latest innovation, Adobe Experience Platform Data Science Workspace and how global technology leader DXC is successfully using this new tool. Hugh explained,
“We’re seeing a trend where there’s a lot of new technology available to drive customer experience management, but only 31% of enterprises are adopting this new technology,”
“There’s a gap in terms of what organizations can do to drive these personalized experiences at scale. You must shift to a digital transformation strategy to accomplish this.”
Adobe launched Data Science Workspace this summer to address the problem of leveraging real-time data at scale. The tool leverages Adobe Sensei, an ML and AI technology, to create, train, and optimize ML models. Data Science Workspace simplifies the process of analyzing omnichannel data, making it easier to apply learnings across multiple channels more quickly.
The importance of unifying data
Customer experience management is top-of-mind for large enterprises that want to create impactful, personalized experiences across the entire buying cycle.
Adobe’s Experience Platform is the foundation for this type of customer data management. The platform aggregates multiple data types (behavioral, transactional, financial, operational, and third-party) into one location, then uses AI and ML to create real-time customer profiles that can be activated in a variety of ways.
Real-time data gives organizations a more comprehensive and accurate view of their customers, but it’s difficult to manage the data, unify it, and make it consistent. Enterprise organizations use the Adobe Experience Platform to deliver personalized experiences at scale. Hugh emphasized that it is an API-first system that allows companies to integrate all their technologies and, as such, it supports a wide variety of data tools in addition to Adobe’s own cloud applications. Hugh stated that,
“The whole point of this is to have a centralized platform,”
“It’s an open environment with connectors that can work in any ecosystem including any non-Adobe product. We have connectors that allow you to bring this data into the platform in real-time.”
The Data Science Workspace enables companies to leverage machine learning by creating their own models or using models that Adobe provides to them. Both B2B and B2C customers get value from data unification and machine learning at scale.
DXC and Data Science Workspace
DXC, a leading global IT technology company, has over 130,000 employees in 70 countries. Like many large organizations, DXC accrues a large volume of data from multiple sources including social media, website visitors, various marketing initiatives and other tools.
“The taxonomy of the data is nuanced or different, so it can be hard to pinpoint the customer based on these identifiers,”
“DXC was able to unify and align the data and taxonomy within the Data Science Workspace which enabled them to build B2B profiles of their customers.”
Once the profiles were created, DXC could start building models to help increase personalization on the website, saving a significant amount of time and work in the process.
DXC identified areas of improvement on the website and devised the best path forward, optimizing users’ website experience by identifying common paths based on the specific profiles that were identified. They then directed visitors to the right contact within DXC for follow-up.
Customer experience management is a company-wide strategy
Customer experience management goes beyond the marketing department. It’s relevant across multiple touchpoints.
“Companies can see the value of this across multiple departments beyond marketing, including sales, IT and customer service,”
“They can build models to help predict the best places to help inform a customer’s journey and experience in terms of what their business can do.”
The ML models that are created in Adobe’s Data Science Workspace work together with Experience Platform’s robust reporting tools. In DXC’s case, using both tools together helped them pinpoint factors predictive of user bounces on the website such as geography and browser type. DXC used the ML model to route website visitors to the appropriate contact within the company, no easy feat for an organization of 100,000+ employees.
“When someone fills out the contact form, we want to send that submission straight to the right department, whether sales, human resources, public relations or IT,” says Christopher Marin, Director of Digital Marketing at DXC. “We built an ML model that predicts the best place to route an inquiry based on the form inputs — and then auto-generates executable code to make it happen in real-time.”