Today, Adobe announced Customer Journey Analytics in Adobe Analytics. It taps the power of Adobe Experience Platform, which standardizes and stitches together customer data from across an organization and opens up new creative ways to understand insights across online, offline and third-party channels. The easy to use, the interactive user interface enables anyone in an organization to work with data, not just the trained data scientist. AI and machine learning through Data Science Workspace in Adobe Experience Platform provide a helping hand with predictive capabilities and automation.
From the start, Adobe developed the Customer Journey Analytics interface with cues taken directly from Photoshop. Both are rooted in the concept of layers: With Photoshop, images and graphics are sourced, edited and layered on top of one another to create a new visual. In Customer Journey Analytics, the layers are data sets instead. Brands can curate metrics such as orders, conversion and visits—across different channels with Adobe Experience Platform—and drag-and-drop layers of data together to uncover new insights about how customers engage with the brand. It provides many different lenses into the overall customer journey.
With Customer Journey Analytics, teams could bring in new data sets such as in point-of-sale systems and call centers to produce insights that are better aligned with how consumers interact. It helps to close a creativity gap seen in data analysis as well, empowering individuals to be more inventive in the way they combine, edit and experiment with different layers of data—a creative process that is familiar to any user of Photoshop. Brands can begin to support decision-making with more comprehensive insights and avoid falling one step behind the customer.
With Customer Journey Analytics, brands are able to:
Answer complex questions: Being able to layer and curate omnichannel data means that brands can compare customer segments, analyze fallout behavior, uncover high performing journeys, and more. Unlike traditional dashboards with limited interactivity, users can dig into layered data sets and present collections of insights for different audiences in real time. In the retail industry, brands can bring together physical stores and e-commerce data and insights. As one example, a brand could uncover the types of digital experiences on specific days that are most likely to drive foot traffic and purchase in offline store—and double down on those efforts.
Allow anyone in an organization to work with data: Customer Journey Analytics is robust for data scientists, but accessible to a broad set of business users such as a marketer or product manager. A new reporting engine helps foster a more data-driven culture, giving any individual a visual and creative way to query data specific to their role. A hotel chain for instance, could help UI teams understand what contributes to customer fallout on the web. The availability of Query Service though Adobe Experience Platform delivers flexibility for more technical audiences to query data sets using SQL and supports integrations with BI tools such as Microsoft Power BI.
Leverage the power of AI and ML: With Adobe Sensei, brands can counteract resource constraints that are typical of most data science teams. Pre-built AI/ML models in Adobe Experience Platform can be trained over time to make better predictions on activities happening across the customer journey, suggest recommendations on best next steps or automate cumbersome processes. A subscription service…Read more
One persistent barrier that brands face as they work to make the customer journey more engaging, with higher levels of personalization, is siloed data. At most companies, marketing data has been centralized in corporate data lakes for storage, but integrating that data is a problem that impacts the data’s usefulness.
Data silos make it nearly impossible to develop a holistic view of the customer journey or interactions across channels and systems. Marketers have longed for a way to link data across the entire process and so achieve a single, omni-channel, holistic perspective of the customer experience, but siloed data make that much too difficult. A single dashboard? Sure, just don’t think about modifying it.
As Nate Smith, group manager for Adobe Analytics, observes, “Marketers often had to guess how channels or activities interacted with each other based on static data that was difficult to manipulate.”
When guesswork enters the picture, confidence in the insights from data analytics disappears. And when guesswork could be eliminated, timeliness was lost.
As Smith notes, “Gaining insight through analytics required that marketers and other LOB staff funnel requests through the data science or BI team, and they then spent much of their time wrangling the data into usable form.”
A single analysis under those conditions could take days or even a week. That meant the marketing team had better know exactly what it was looking for in the data, because a do-over would mean doubling the time the analysis would take. If the marketers wanted iterative analysis, or a new spin on the analysis, the entire process had to start all over again.
Empowering marketers, data analysts, and IT
The new releases of Adobe Analytics and the Adobe Experience Platform are changing the game, putting new abilities into marketers’ own hands and providing analyses that are both more reliable and timelier. Now all customer experience and journey data, from all channels, is integrated and normalized within the Adobe Experience Platform. Data can be interrogated in real time to support iterative and ad hoc analysis. The availability of omni-channel data gives marketers a truly holistic view of a customer that enhances that customer’s experience. For data analysts and the IT organization, it will help minimize reporting needs and remove some implementation barriers, helping brands realize their analytics investments more quickly.
What does that mean in concrete terms? Consider a customer who does some online research on new golf clubs. In the old world of disaggregated data, it’s likely that the marketing systems of one of the golf club brands that the customer showed interest in would issue a digital coupon to that customer—after he had made a purchase. For the customer, it was a negative experience, since he was left with the feeling that he had overpaid. With Adobe’s new features, the coupon can be delivered sooner in the decision process, resulting in the positive customer experience that everyone is hoping for…Read more
Adobe Inc. today added a new tool to its Adobe Analytics offering that’s meant to give companies more advanced insights into their customer’s behavior.
The new offering, Customer Journey Analytics, draws on data from multiple enterprise systems to try to provide users with better perspectives on how customers engage with their brand.
Adobe reckons that’s something most companies struggle with. It says most customer journeys are complex interactions that span both digital and physical touchpoints, and that the data on these tends to be scattered across numerous information technology systems. As a result, most companies’ customer journey data is incomplete, which means few insights can be drawn from it.
Customer Journey Analytics in Adobe Analytics is Adobe’s attempt to fix this problem. The service draws on the Adobe Experience Platform that creates individual profiles for each customer and tracks their interactions with the brand. It stitches together the data from every interaction customers have with a company, providing a more complete picture of their behavior.
The new service also takes a cue from the “underlying logic” of Photoshop, enabling layers of multichannel data to be stacked on top of each other to create new perspectives on customer engagement. In turn, that enables employees to get creative with their customer data, mixing and matching different kinds of information to discover more insights.
Simply put, Adobe aims to make it easier for companies to curate and explore their customer data in a way that provides some interesting benefits.
The company said the services enables brands to compare customer segments, analyze fallout behavior and uncover high-performing journeys, among other things. For instance, retailers can start to understand how physical stores and e-commerce interact.
Adobe has also thrown in a bunch of pre-built machine learning models that can be trained on Customer Journey Analytics’ data. They allow users to create predictive models, provide recommendations on next best steps and automate some of their more cumbersome processes. For instance, a subscription service could see when segments of users are likely to deactivate their membership as well as figure out content or promotions to keep them…Read more
Adobe is applying the layered approach and ease of use of products like its Adobe Photoshop to its new Adobe Customer Journey Analytics solution. Announced today, Adobe Customer Journey Analytics helps businesses and brands access layers of multi-channel customer data to be curated and stacked on top of each other to uncover new perspectives into how customers engage with a brand. The new capability in Adobe Analytics uses the Adobe Experience Platform, which can piece together customer data from across the enterprise, and opens up new ways to understand insights across online, offline, and third-party channels.
Adobe Customer Journey Analytics is the latest move by Adobe in bolstering its position in the business analytics and solutions space since it purchased web analytics solution provider Omniture in 2009. Adobe has been acquiring various web analytics, content management system (CMS), advertising technology, and marketing tech companies. Last year, Adobe spent $6.43 billion in software acquisitions, mostly to enhance its various marketing and business solutions. Tools such as Adobe Customer Journey Analytics are the result of Adobe’s various acquisitions and integrations.
Adobe said in a statement that its solution helps to close a creativity gap in data analysis by “empowering individuals to be more inventive in the way they combine, edit, and experiment with different layers of data—a creative process that is familiar to any user of Adobe Photoshop.” …Read more